Disaster Prediction and Risk Management Using Machine Learning and Data Science Techniques for Improved Forecasting
Keywords:
Necessitating effective; Lack scalability; Machine learning (ML); Convolutional neural networks (CNNs); Support vector machines (SVMs); Robust frameworks.
Abstract
Landslides pose enormous dangers to human lives, infrastructure, and the environment; therefore, it is necessary to have technologies that are capable of detecting and monitoring them effectively. Landslide detection methods that have been used traditionally frequently rely on the manual interpretation of satellite images or field surveys. These methods are not only time-consuming and expensive, but they also lack the potential to scale. Over the course of the past few years, the development of machine learning (ML) techniques has provided extremely promising options for automating the processes involved in landslide detection. The purpose of this work is to provide a comprehensive analysis of current developments in the detection of landslides through the application of Machine Learning techniques. The research presents an overview of the various machine learning algorithms that are applied for the detection of landslides. These algorithms include convolutional neural networks (CNNs), support vector machines (SVMs), decision trees, and ensemble management techniques. This article analyzes new advancements in model construction and optimization strategies, as well as highlighting the advantages and disadvantages of each methodology. The integration of data from multiple sources, transfer learning, and the development of robust frameworks for operational landslide monitoring and early warning systems are some of the potential areas for future research that are investigated in this study.A substantial amount of promise exists for the application of machine learning techniques to improve the effectiveness and precision of landslide detection and monitoring activities.
Landslides pose enormous dangers to human lives, infrastructure, and the environment; therefore, it is necessary to have technologies that are capable of detecting and monitoring them effectively. Landslide detection methods that have been used traditionally frequently rely on the manual interpretation of satellite images or field surveys. These methods are not only time-consuming and expensive, but they also lack the potential to scale. Over the course of the past few years, the development of machine learning (ML) techniques has provided extremely promising options for automating the processes involved in landslide detection. The purpose of this work is to provide a comprehensive analysis of current developments in the detection of landslides through the application of Machine Learning techniques. The research presents an overview of the various machine learning algorithms that are applied for the detection of landslides. These algorithms include convolutional neural networks (CNNs), support vector machines (SVMs), decision trees, and ensemble management techniques. This article analyzes new advancements in model construction and optimization strategies, as well as highlighting the advantages and disadvantages of each methodology. The integration of data from multiple sources, transfer learning, and the development of robust frameworks for operational landslide monitoring and early warning systems are some of the potential areas for future research that are investigated in this study.A substantial amount of promise exists for the application of machine learning techniques to improve the effectiveness and precision of landslide detection and monitoring activities.
References
P. Pulivarthy, "Enhancing Data Integration in Oracle Databases: Leveraging Machine Learning for Automated Data Cleansing, Transformation, and Enrichment," International Journal of Holistic Management Perspectives, vol. 4, no. 4, pp. 1–18, Jun. 2023.
M. A. Al-Khasawneh, S. M. Shamsuddin, S. Hasan, and A. A. Bakar, "MapReduce a comprehensive review," in 2018 International Conference on Smart Computing and Electronic Enterprise (ICSCEE), July 2018, pp. 1-6.
S. Markkandeyan, S. Gupta, G. V. Narayanan, M. J. Reddy, M. A. Al-Khasawneh, M. Ishrat, and A. Kiran, "Deep learning based semantic segmentation approach for automatic detection of brain tumor," International Journal of Computers Communications & Control, vol. 18, no. 4, 2023.
M. A. Al-Khasawneh, A. Alzahrani, and A. Alarood, "Alzheimer’s Disease Diagnosis Using MRI Images," in Data Analysis for Neurodegenerative Disorders, Singapore: Springer Nature Singapore, 2023, pp. 195-212.
O. Ameerbakhsh, F. M. Ghabban, I. M. Alfadli, A. N. AbuAli, A. Al-Dhaqm, and M. A. Al-Khasawneh, "Digital forensics domain and metamodeling development approaches," in 2021 2nd International Conference on Smart Computing and Electronic Enterprise (ICSCEE), June 2021, pp. 67-71.
A. Thirunagalingam, "Unified Multi-Modal Data Analytics: Bridging the Gap Between Structured and Unstructured Data," International Journal of Innovations in Scientific Engineering, vol. 20, no. 1, pp. 25–35, 2024.
A. Thirunagalingam, "Enhancing Data Governance Through Explainable AI: Bridging Transparency and Automation," International Journal of Sustainable Development Through AI, ML and IoT, vol. 1, no. 2, pp. 1–12.
M. Kommineni, "Develop New Techniques for Ensuring Fairness in Artificial Intelligence and ML Models to Promote Ethical and Unbiased Decision-Making," International Journal of Innovations in Applied Sciences & Engineering, vol. 10, Special Issue, pp. 13, Aug. 2024.
M. Kommineni, "Investigate Methods for Visualizing the Decision-Making Processes of a Complex AI System, Making Them More Understandable and Trustworthy in Financial Data Analysis," International Transactions in Artificial Intelligence, vol. 8, no. 8, pp. 1–21, Jan. 2024.
B. Kumar, V. Padmanabha, P. Josephmani, and R. Dwivedi, “Utilizing packet tracer simulation to modern smart campus initiatives for a sustainable future,” in Proc. 2024 IEEE 12th Int. Conf. Smart Energy Grid Eng. (SEGE), 2024.
B. Kumar, “Harnessing core-accelerated machine learning for enhanced knowledge acquisition in system integration,” Int. J. Syst. Sci. Eng., 2026.
H. A. Al-Asadi, M. H. Al-Mansoori, M. Ajiya, S. Hitam, M. I. Saripan, and M. A. Mahdi, “Effects of pump recycling technique on stimulated Brillouin scattering threshold: A theoretical model,” Optics Express, vol. 18, no. 21, pp. 22339- 22347, 2010.
H. A. Al-Asadi, M. H. Al-Mansoori, M. I. Saripan, and M. A. Mahdi, “Brillouin Linewidth Characterization in Single Mode Large Effective Area Fiber through the Co-Pumped Technique,” International Journal of Electronics, Computer and Communications Technologies (IJECCT), vol. 1, no. 1, pp. 16-20, 2010.
H. A. Al-Asadi, M. H. Al-Mansoori, S. Hitam, M. I. Saripan, and M. A. Mahdi, “Particle swarm optimization on threshold exponential gain of stimulated Brillouin scattering in single mode fibers,” Optics Express, vol. 19, no. 3, pp. 1842-1853, 2011.
H. A. Al-Asadi, M. H. Al-Mansoori, S. Hitam, M. I. Saripan, and M. A. Mahdi, “Analytical study of nonlinear phase shift through stimulated Brillouin scattering in single mode fibre with pump power recycling technique,” Journal of Optics, vol. 13 no. 10, 2011.
H. A. Al-Asadi, M. H. Abu Bakar, M. H. Al-Mansoori, F. R. Mahamd Adikan, and M. A. Mahdi, “Analytical analysis of second-order Stokes wave in Brillouin ring fiber laser,” Optics. Express, vol. 19, no. 25, pp. 25741- 25748, 2011.
M. Al-Asadi, Y. A. Al-Asadi, and H. A. Al-Asadi, “Architectural Analysis of Multi-Agents Educational Model in Web-Learning Environments,” Journal of Emerging Trends in Computing and Information Sciences, vol. 3, no. 6, 2012.
M. A. Abed and H. A. Al-Asadi, “Simplifying Handwritten Characters Recognition Using a Particle Swarm Optimization Approach,” European Academic Research, vol 1, pp. 535- 552, 2013.
M. A. Abed and H. A. Al-Asadi, “High Accuracy Arabic Handwritten Characters Recognition using (EBPANN) Architecture,” International Journal of Advanced Computer Science and Applications (IJACSA), vol. 6, no. 2, pp. 145-152, 2015.
H. A. Al-Asadi and M. A. Abed, “Object Recognition Using Artificial Fish Swarm Algorithm on Fourier Descriptors,” American Journal of Engineering, Technology and Society, vol 2, no. 5, pp. 105-110, 2015.
V. Yadav, “The Role of Virtual Reality in Patient Education: Exploring how Virtual Reality Technology can be used to Educate Patients about Complex Medical Procedures or Health Conditions,” Progress in Medical Sciences, vol. 8, no. 3, pp. 1–5, May. 2024.
V. Yadav, “Blockchain for Secure Healthcare Data Exchange: Exploring the Potential of Blockchain Technology to Create a Secure and Efficient Data Exchange System for Healthcare Information”, Journal of Scientific and Engineering Research, vol. 11, no. 4, pp. 344–350, Apr. 2024.
V. Yadav, “Predictive Analytics for Preventive Medicine: Analyzing how Predictive Analytics is Utilized for Forecasting Patient Health Trends and Preventive Disease,” Progress in Medical Sciences, vol. 8, no. 4, pp. 1–6, Jul. 2024.
Vivek Yadav, “Cybersecurity Protocols for Telehealth: Developing new cybersecurity protocols to protect patient data during telehealth sessions”, N. American. J. of Engg. Research, vol. 5, no. 2, May 2024, Accessed: Oct. 27, 2024.
V.Yadav, “Ethical Implications of Al in Patient Care Decisions: A Study on the Ethical Considerations of Using Artificial Intelligence to Make or Assist in Patient Care Decisions,” Journal of Artificial Intelligence & Cloud Computing, vol. 3, no. 3, pp. 1–5, Jun. 2024.
V. Yadav, “Use of Augmented Reality for Surgical Training: Studying the effectiveness and potential of augmented reality tools in training surgeons,” Journal of Artificial Intelligence, Machine Learning and Data Science, vol. 1, no. 2, pp. 927–932, Apr. 2024.
V. Yadav, “Wearable Health Technology Data Privacy; Investigating the Balance between the Benefits of Wearable Health Devices and the Privacy Concerns they Raise,” International Journal of Science and Research (IJSR), vol. 11, no. 12, pp. 1363–1371, Dec. 2022.
V. Yadav, “Economic Impact of Telehealth Expansion: Analyse the Cost - Effectiveness and Long - Term Economic Implications of The Widespread Adoption of Telehealth Services Post Pandemic,” International Journal of Science and Research (IJSR), vol. 12, no. 6, pp. 2997–3001, Jun. 2023.
V. Yadav, “Healthcare Workforce Economics: Study the Economic Effects of the Changing Demographics of Healthcare Workers, Including the Rise of Gig Economy Roles in Healthcare,” Progress In Medical Sciences, pp. 1–5, Sep. 2022.
Vivek Yadav, “Value-Based Care and Economic Outcomes: Investigate the Correlation Between Value-Based Care Models and Economic Outcomes for Healthcare Providers and Patients”, Journal of Scientific and Engineering Research, vol. 10, no. 3, pp. 132–141, Mar. 2023.
H. A. Al-Asadi, “Energy Efficient Hierarchical Clustering Mechanism for Wireless Sensor Network Fields,” International Journal of Computer Applications, vol. 153, no. 10, pp. 42-46, 2016.
H. A. Al-Asadi, “Hybrid Clustering Methodology using Optical Communication in Wireless Sensor Networks,” International Journal on Advanced Science, Engineering and Information Technology, vol. 7, no. 1, 2017.
H. A. Al-Asadi, “Mobile Clustering Algorithm for Effective Clustering in Dense Wireless Sensor Networks,” European Journal of Advances in Engineering & Technology (EJAET), vol. 4, no. 1, pp. 1-6, 2017.
H. A. Al-Asadi, “Integrated Energy Efficient Clustering Strategy for Wireless Sensor Networks,” The Journal of Middle East and North Africa Sciences, vol. 3, pp. 8-13, 2017.
H. A. Al-Asadi, M. A. Al-Asadi, and N. A. Noori, “Optimization Noise Figure of Fiber Raman Amplifier based on Bat Algorithm in Optical Communication network,” International Journal of Engineering & Technology, vol. 7, no. 2, pp. 874-879, 2018.
H. A. Al-Asadi, and N. A. M. B. A. Hambali, “Experimental evaluation and theoretical investigations of fiber Raman amplifiers and its gain optimization based on single forward pump,” Journal of Laser Applications, vol. 26, no. 4, 2014.
H. A. Al-Asadi, “Nonlinear Phase Shift due to Stimulated Brillouin Scattering in Strong Saturation Regime for Different Types of Fibers,” Journal of Optical Communications (JOC), vol. 36, no. 3, pp. 211–216, 2014.
B. Kumar, H. Shaker, B. Al Ruzaiqi, and R. Al Balushi, “Design and implementation of a smart office network module using visual simulation tool,” J. Namib. Stud., vol. 34, Suppl. 2, pp. 2664–2676, 2023.
B. Kumar, “IoT-based smart greenhouse monitoring system using visual simulation tool,” Int. J. Sci. Math. Technol. Learn., vol. 31, no. 2, pp. 44–58, 2023.
K. Al Aufi and B. Kumar, “Security testing of Android application using Drozer,” in Proc. Int. Conf. Comput. Sci. Sustainable Technol., Springer CCIS, 2024, pp. 8–18.
B. Kumar, I. Al-Busaidi, and M. Halloush, “Healthcare information exchange using blockchain and machine learning,” in Proc. 1st Int. Conf. Innov. Inf. Technol. Business (ICIITB 2022), Springer, 2022, pp. 141–155.
B. Kumar, H. Shaker, and P. Josephmani, “Design and execution of secure smart home environments on visual simulation tool,” in Proc. 1st Int. Conf. Innov. Inf. Technol. Business (ICIITB 2022), Springer, 2022, pp. 200–218.
B. Al Barwani, E. Al Maani, and B. Kumar, “IoT-enabled smart cities: A review of security frameworks, privacy, risks, and key technologies,” in Proc. 1st Int. Conf. Innov. Inf. Technol. Business (ICIITB 2022), Springer, 2022, pp. 169–181.
Y. Al Balushi, H. Shaker, and B. Kumar, “The use of machine learning in digital forensics: Review paper,” in Proc. 1st Int. Conf. Innov. Inf. Technol. Business (ICIITB 2022), vol. 104, Springer, 2022.
M. Kommineni, "Study High-Performance Computing Techniques for Optimizing and Accelerating AI Algorithms Using Quantum Computing and Specialized Hardware," International Journal of Innovations in Applied Sciences & Engineering, vol. 9, no. 1, pp. 48–59, Sep. 2023.
M. Kommineni, "Investigate Computational Intelligence Models Inspired by Natural Intelligence, Such as Evolutionary Algorithms and Artificial Neural Networks," Transactions on Latest Trends in Artificial Intelligence, vol. 4, no. 4, p. 30, Jun. 2023.
M. Kommineni, "Investigating High-Performance Computing Techniques for Optimizing and Accelerating AI Algorithms Using Quantum Computing and Specialized Hardware," International Journal of Innovations in Scientific Engineering, vol. 16, no. 1, pp. 66–80, Nov. 2022.
M. Kommineni, "Discover the Intersection Between AI and Robotics in Developing Autonomous Systems for Use in the Human World and Cloud Computing," International Numeric Journal of Machine Learning and Robots, vol. 6, no. 6, pp. 1–19, Sep. 2022.
M. Kommineni, "Explore Scalable and Cost-Effective AI Deployments, Including Distributed Training, Model Serving, and Real-Time Inference on Human Tasks," International Journal of Advances in Engineering Research, vol. 24, no. 1, pp. 07–27, Jul. 2022.
M. Kommineni, "Explore Knowledge Representation, Reasoning, and Planning Techniques for Building Robust and Efficient Intelligent Systems," International Journal of Inventions in Engineering & Science Technology, vol. 7, no. 2, pp. 105–114, 2021.
A. Thirunagalingam, "AI-Powered Continuous Data Quality Improvement: Techniques, Benefits, and Case Studies," International Journal of Innovations in Applied Sciences & Engineering, vol. 10, no. 1, p. 9, Aug. 2024.
A. Thirunagalingam, "Bias Detection and Mitigation in Data Pipelines: Ensuring Fairness and Accuracy in Machine Learning," AVE Trends in Intelligent Computing Systems, vol. 1, no. 2, pp. 116–127, Jul. 2024.
A. Thirunagalingam, "Combining AI Paradigms for Effective Data Imputation: A Hybrid Approach," International Journal of Transformations in Business Management, vol. 14, no. 1, pp. 49–58, Mar. 2024.
A. Thirunagalingam, "Quantum Computing for Advanced Large-Scale Data Integration: Enhancing Accuracy and Speed," International Journal of Innovations in Applied Sciences & Engineering, vol. 9, no. 1, pp. 60–71, Sep. 2023.
A. Thirunagalingam, "AI for Proactive Data Quality Assurance: Enhancing Data Integrity and Reliability," International Journal of Advances in Engineering Research, vol. 26, no. 2, pp. 22–35, Aug. 2023.
A. Thirunagalingam, "Improving Automated Data Annotation with Self-Supervised Learning: A Pathway to Robust AI Models," International Transactions in Artificial Intelligence, vol. 7, no. 7, pp. 1–22, Jun. 2023.
A. Thirunagalingam, "Federated Learning for Cross-Industry Data Collaboration: Enhancing Privacy and Innovation," International Journal of Sustainable Development Through AI, ML and IoT, vol. 2, no. 1, pp. 1–13, Jan. 2023.
A. Thirunagalingam, “Transforming Real-Time Data Processing: The Impact of AutoML on Dynamic Data Pipelines,” FMDB Transactions on Sustainable Intelligent Networks., vol.1, no.2, pp. 110–119, 2024.
M. A. Al-Khasawneh, A. Alzahrani, and A. Alarood, "An artificial intelligence based effective diagnosis of Parkinson disease using EEG signal," in Data Analysis for Neurodegenerative Disorders, Singapore: Springer Nature Singapore, 2023, pp. 239-251.
V. Kumar, S. Kumar, R. AlShboul, G. Aggarwal, O. Kaiwartya, A. M. Khasawneh, et al., "Grouping and sponsoring centric green coverage model for internet of things," Sensors, vol. 21, no. 12, p. 3948, 2021.
A. M. Khasawneh, O. Kaiwartya, J. Lloret, H. Y. Abuaddous, L. Abualigah, M. A. Shinwan, et al., "Green communication for underwater wireless sensor networks: Triangle metric based multi-layered routing protocol," Sensors, vol. 20, no. 24, p. 7278, 2020.
M. A. Al-Khasawneh, W. Abu-Ulbeh, and A. M. Khasawneh, "Satellite images encryption review," in 2020 International Conference on Intelligent Computing and Human-Computer Interaction (ICHCI), December 2020, pp. 121-125.
S. A. A. Shah, M. A. Al-Khasawneh, and M. I. Uddin, "Review of weapon detection techniques within the scope of street-crimes," in 2021 2nd International Conference on Smart Computing and Electronic Enterprise (ICSCEE), June 2021, pp. 26-37.
I. M. Alfadli, F. M. Ghabban, O. Ameerbakhsh, A. N. AbuAli, A. Al-Dhaqm, and M. A. Al-Khasawneh, "Cipm: Common identification process model for database forensics field," in 2021 2nd International Conference on Smart Computing and Electronic Enterprise (ICSCEE), June 2021, pp. 72-77.
I. Ahmad, S. A. A. Shah, and M. A. Al-Khasawneh, "Performance analysis of intrusion detection systems for smartphone security enhancements," in 2021 2nd International Conference on Smart Computing and Electronic Enterprise (ICSCEE), June 2021, pp. 19-25.
M. Mahmoud and M. A. Al-Khasawneh, "Greedy Intersection‐Mode Routing Strategy Protocol for Vehicular Networks," Complexity, vol. 2020, p. 4870162, 2020.
A. Alarood, N. Ababneh, M. Al-Khasawneh, M. Rawashdeh, and M. Al-Omari, "IoTSteg: ensuring privacy and authenticity in internet of things networks using weighted pixels classification based image steganography," Cluster Computing, vol. 25, no. 3, pp. 1607-1618, 2022.
H. A. Sukhni, M. A. Al-Khasawneh, and F. H. Yusoff, "A systematic analysis for botnet detection using genetic algorithm," in 2021 2nd International Conference on Smart Computing and Electronic Enterprise (ICSCEE), June 2021, pp. 63-66.
O. Krishnamurthy and G. Vemulapalli, "Advancing Sustainable Cybersecurity: Exploring Trends and Overcoming Challenges with Generative AI," in Sustainable Development through Machine Learning, AI and IoT, P. Whig, N. Silva, A. A. Elngar, N. Aneja, and P. Sharma, Eds. Cham, Switzerland: Springer, 2025, vol. 2196, pp. 1-14.
G. Vemulapalli, "Self-service analytics implementation strategies for empowering data analysts," International Journal of Machine Learning and Artificial Intelligence, vol. 4, no. 4, pp. 1-14, 2023.
G. Vemulapalli, "Overcoming data literacy barriers: Empowering non-technical teams," International Journal of Holistic Management Perspectives, vol. 5, no. 5, pp. 1-17, 2024.
G. Vemulapalli, "Architecting for real-time decision-making: Building scalable event-driven systems," International Journal of Machine Learning and Artificial Intelligence, vol. 4, no. 4, pp. 1-20, 2023.
G. Vemulapalli, S. Yalamati, N. R. Palakurti, N. Alam, S. Samayamantri, and P. Whig, "Predicting obesity trends using machine learning from big data analytics approach," 2024 Asia Pacific Conference on Innovation in Technology (APCIT), Mysore, India, 2024, pp. 1-5.
G. Vemulapalli, "AI-driven predictive models strategies to reduce customer churn," International Numeric Journal of Machine Learning and Robots, vol. 8, no. 8, pp. 1-13, 2024.
G. Vemulapalli, "Cloud data stack scalability: A case study on migrating from legacy systems," International Journal of Sustainable Development Through AI, ML and IoT, vol. 3, no. 1, pp. 1-15, 2024.
G. Vemulapalli, "Operationalizing machine learning best practices for scalable production deployments," International Machine Learning Journal and Computer Engineering, vol. 6, no. 6, pp. 1-21, 2023.
G. Vemulapalli, "Optimizing NoSQL database performance: Elevating API responsiveness in high-throughput environments," International Machine Learning Journal and Computer Engineering, vol. 6, no. 6, pp. 1-14, 2023.
G. Vemulapalli, "Optimizing analytics: Integrating data warehouses and lakes for accelerated workflows," International Scientific Journal for Research, vol. 5, no. 5, pp. 1-27, 2023.
Y. F. Saputra and M. A. Al-Khasawneh, "Big data analytics: Schizophrenia prediction on Apache spark," in Advances in Cyber Security: Second International Conference, ACeS 2020, Penang, Malaysia, December 8-9, 2020, Revised Selected Papers 2, Springer Singapore, 2021, pp. 508-522.
S. A. A. Shah, M. A. Al-Khasawneh, and M. I. Uddin, "Street-crimes Modelled Arms Recognition Technique (SMART): Using VGG," in 2021 2nd International Conference on Smart Computing and Electronic Enterprise (ICSCEE), June 2021, pp. 38-44.
A. M. Alghamdi, M. A. Al-Khasawneh, A. Alarood, and E. Alsolami, "The Role of Machine Learning in Managing and Organizing Healthcare Records," Engineering, Technology & Applied Science Research, vol. 14, no. 2, pp. 13695-13701, 2024.
M. A. Al-Khasawneh, M. Faheem, A. A. Alarood, S. Habibullah, and E. Alsolami, "Towards Multi-Modal Approach for Identification and Detection of Cyberbullying in Social Networks," IEEE Access, 2024.
A. O. Alzahrani, M. A. Al-Khasawneh, A. A. Alarood, and E. Alsolami, "A Forensic Framework for gathering and analyzing Database Systems using Blockchain Technology," Engineering, Technology & Applied Science Research, vol. 14, no. 3, pp. 14079-14087, 2024.
M. A. Al-Khasawneh, M. Faheem, A. A. Alarood, S. Habibullah, and A. Alzahrani, "A secure blockchain framework for healthcare records management systems," Healthcare Technology Letters, IEEE, 2024.
P. Pulivarthy, "Enhancing Database Query Efficiency: AI-Driven NLP Integration in Oracle," Transactions on Latest Trends in Artificial Intelligence, vol. 4, no. 4, pp. 1–25, Oct. 2023.
P. Pulivarthy, "Gen AI Impact on the Database Industry Innovations," International Journal of Advances in Engineering Research, vol. 28, no. 3, pp. 1–10, Sep. 2024.
P. Pulivarthy, "Semiconductor Industry Innovations: Database Management in the Era of Wafer Manufacturing," FMDB Transactions on Sustainable Intelligent Networks, vol. 1, no. 1, pp. 15–26, Mar. 2024.
P. Pulivarthy, "Enhancing Dynamic Behaviour in Vehicular Ad Hoc Networks through Game Theory and Machine Learning for Reliable Routing," International Journal of Machine Learning and Artificial Intelligence, vol. 4, no. 4, pp. 1–13, Dec. 2023.
P. Pulivarthy, "Performance Tuning: AI Analyse Historical Performance Data, Identify Patterns, and Predict Future Resource Needs," International Journal of Innovations in Applied Sciences and Engineering, vol. 8, no. 2, pp. 139–155, Nov. 2022.
R. Rai, A. Shrestha, S. Rai, S. Chaudhary, D. K. Acharya, and S. Subedi, “Conversion of farming systems into organic biointensive farming systems and the transition to sustainability in agro-ecology: Pathways towards sustainable agriculture and food systems,” J. Multidiscip. Sci., vol. 6, no. 1, pp. 26–31, Jun. 2024.
S. Rai and R. Rai, “Advancements and practices in budding techniques for kiwifruit propagation,” J. Multidiscip. Sci., vol. 6, no. 1, pp. 26–31, Jun. 2024.
S. Rai and R. Rai, “Monkey menace in Nepal: An analysis and proposed solutions,” J. Multidiscip. Sci., vol. 6, no. 1, pp. 26–31, Jun. 2024.
K. Shrestha, S. Chaudhary, S. Subedi, S. Rai, D. K. Acharya, and R. Rai, “Farming systems research in Nepal: Concepts, design, and methodology for enhancing agricultural productivity and sustainability,” J. Multidiscip. Sci., vol. 6, no. 1, pp. 17–25, May 2024.
S. Rai and R. Rai, “Advancement of kiwifruit cultivation in Nepal: Top working techniques,” J. Multidiscip. Sci., vol. 6, no. 1, pp. 11–16, Feb. 2024.
S. Chaudhary, A. K. Shrestha, S. Rai, D. K. Acharya, S. Subedi, and R. Rai, “Agroecology integrates science, practice, movement, and future food systems,” J. Multidiscip. Sci., vol. 5, no. 2, pp. 39–60, Dec. 2023.
R. Rai, V. Y. Nguyen, and J. H. Kim, “Variability analysis and evaluation for major cut flower traits of F1 hybrids in Lilium brownii var. colchesteri,” J. Multidiscip. Sci., vol. 4, no. 2, pp. 35–41, Dec. 2022.
V. Y. Nguyen, R. Rai, J.-H. Kim, J. Kim, and J.-K. Na, “Ecogeographical variations of the vegetative and floral traits of Lilium amabile Palibian,” J. Plant Biotechnol., vol. 48, no. 4, pp. 236–245, Dec. 2021.
R. Rai and J. H. Kim, “Performance evaluation and variability analysis for major growth and flowering traits of Lilium longiflorum Thunb. genotypes,” J. Exp. Biol. Agric. Sci., vol. 9, no. 4, pp. 439–444, Aug. 2021.
R. Rai, V. Y. Nguyen, and J. H. Kim, “Estimation of variability analysis parameters for major growth and flowering traits of Lilium leichtlinii var. maximowiczii germplasm,” J. Exp. Biol. Agric. Sci., vol. 9, no. 4, pp. 457–463, Aug. 2021.
M. A. Al-Khasawneh, S. M. Shamsuddin, S. Hasan, and A. A. Bakar, "MapReduce a comprehensive review," in 2018 International Conference on Smart Computing and Electronic Enterprise (ICSCEE), July 2018, pp. 1-6.
S. Markkandeyan, S. Gupta, G. V. Narayanan, M. J. Reddy, M. A. Al-Khasawneh, M. Ishrat, and A. Kiran, "Deep learning based semantic segmentation approach for automatic detection of brain tumor," International Journal of Computers Communications & Control, vol. 18, no. 4, 2023.
M. A. Al-Khasawneh, A. Alzahrani, and A. Alarood, "Alzheimer’s Disease Diagnosis Using MRI Images," in Data Analysis for Neurodegenerative Disorders, Singapore: Springer Nature Singapore, 2023, pp. 195-212.
O. Ameerbakhsh, F. M. Ghabban, I. M. Alfadli, A. N. AbuAli, A. Al-Dhaqm, and M. A. Al-Khasawneh, "Digital forensics domain and metamodeling development approaches," in 2021 2nd International Conference on Smart Computing and Electronic Enterprise (ICSCEE), June 2021, pp. 67-71.
A. Thirunagalingam, "Unified Multi-Modal Data Analytics: Bridging the Gap Between Structured and Unstructured Data," International Journal of Innovations in Scientific Engineering, vol. 20, no. 1, pp. 25–35, 2024.
A. Thirunagalingam, "Enhancing Data Governance Through Explainable AI: Bridging Transparency and Automation," International Journal of Sustainable Development Through AI, ML and IoT, vol. 1, no. 2, pp. 1–12.
M. Kommineni, "Develop New Techniques for Ensuring Fairness in Artificial Intelligence and ML Models to Promote Ethical and Unbiased Decision-Making," International Journal of Innovations in Applied Sciences & Engineering, vol. 10, Special Issue, pp. 13, Aug. 2024.
M. Kommineni, "Investigate Methods for Visualizing the Decision-Making Processes of a Complex AI System, Making Them More Understandable and Trustworthy in Financial Data Analysis," International Transactions in Artificial Intelligence, vol. 8, no. 8, pp. 1–21, Jan. 2024.
B. Kumar, V. Padmanabha, P. Josephmani, and R. Dwivedi, “Utilizing packet tracer simulation to modern smart campus initiatives for a sustainable future,” in Proc. 2024 IEEE 12th Int. Conf. Smart Energy Grid Eng. (SEGE), 2024.
B. Kumar, “Harnessing core-accelerated machine learning for enhanced knowledge acquisition in system integration,” Int. J. Syst. Sci. Eng., 2026.
H. A. Al-Asadi, M. H. Al-Mansoori, M. Ajiya, S. Hitam, M. I. Saripan, and M. A. Mahdi, “Effects of pump recycling technique on stimulated Brillouin scattering threshold: A theoretical model,” Optics Express, vol. 18, no. 21, pp. 22339- 22347, 2010.
H. A. Al-Asadi, M. H. Al-Mansoori, M. I. Saripan, and M. A. Mahdi, “Brillouin Linewidth Characterization in Single Mode Large Effective Area Fiber through the Co-Pumped Technique,” International Journal of Electronics, Computer and Communications Technologies (IJECCT), vol. 1, no. 1, pp. 16-20, 2010.
H. A. Al-Asadi, M. H. Al-Mansoori, S. Hitam, M. I. Saripan, and M. A. Mahdi, “Particle swarm optimization on threshold exponential gain of stimulated Brillouin scattering in single mode fibers,” Optics Express, vol. 19, no. 3, pp. 1842-1853, 2011.
H. A. Al-Asadi, M. H. Al-Mansoori, S. Hitam, M. I. Saripan, and M. A. Mahdi, “Analytical study of nonlinear phase shift through stimulated Brillouin scattering in single mode fibre with pump power recycling technique,” Journal of Optics, vol. 13 no. 10, 2011.
H. A. Al-Asadi, M. H. Abu Bakar, M. H. Al-Mansoori, F. R. Mahamd Adikan, and M. A. Mahdi, “Analytical analysis of second-order Stokes wave in Brillouin ring fiber laser,” Optics. Express, vol. 19, no. 25, pp. 25741- 25748, 2011.
M. Al-Asadi, Y. A. Al-Asadi, and H. A. Al-Asadi, “Architectural Analysis of Multi-Agents Educational Model in Web-Learning Environments,” Journal of Emerging Trends in Computing and Information Sciences, vol. 3, no. 6, 2012.
M. A. Abed and H. A. Al-Asadi, “Simplifying Handwritten Characters Recognition Using a Particle Swarm Optimization Approach,” European Academic Research, vol 1, pp. 535- 552, 2013.
M. A. Abed and H. A. Al-Asadi, “High Accuracy Arabic Handwritten Characters Recognition using (EBPANN) Architecture,” International Journal of Advanced Computer Science and Applications (IJACSA), vol. 6, no. 2, pp. 145-152, 2015.
H. A. Al-Asadi and M. A. Abed, “Object Recognition Using Artificial Fish Swarm Algorithm on Fourier Descriptors,” American Journal of Engineering, Technology and Society, vol 2, no. 5, pp. 105-110, 2015.
V. Yadav, “The Role of Virtual Reality in Patient Education: Exploring how Virtual Reality Technology can be used to Educate Patients about Complex Medical Procedures or Health Conditions,” Progress in Medical Sciences, vol. 8, no. 3, pp. 1–5, May. 2024.
V. Yadav, “Blockchain for Secure Healthcare Data Exchange: Exploring the Potential of Blockchain Technology to Create a Secure and Efficient Data Exchange System for Healthcare Information”, Journal of Scientific and Engineering Research, vol. 11, no. 4, pp. 344–350, Apr. 2024.
V. Yadav, “Predictive Analytics for Preventive Medicine: Analyzing how Predictive Analytics is Utilized for Forecasting Patient Health Trends and Preventive Disease,” Progress in Medical Sciences, vol. 8, no. 4, pp. 1–6, Jul. 2024.
Vivek Yadav, “Cybersecurity Protocols for Telehealth: Developing new cybersecurity protocols to protect patient data during telehealth sessions”, N. American. J. of Engg. Research, vol. 5, no. 2, May 2024, Accessed: Oct. 27, 2024.
V.Yadav, “Ethical Implications of Al in Patient Care Decisions: A Study on the Ethical Considerations of Using Artificial Intelligence to Make or Assist in Patient Care Decisions,” Journal of Artificial Intelligence & Cloud Computing, vol. 3, no. 3, pp. 1–5, Jun. 2024.
V. Yadav, “Use of Augmented Reality for Surgical Training: Studying the effectiveness and potential of augmented reality tools in training surgeons,” Journal of Artificial Intelligence, Machine Learning and Data Science, vol. 1, no. 2, pp. 927–932, Apr. 2024.
V. Yadav, “Wearable Health Technology Data Privacy; Investigating the Balance between the Benefits of Wearable Health Devices and the Privacy Concerns they Raise,” International Journal of Science and Research (IJSR), vol. 11, no. 12, pp. 1363–1371, Dec. 2022.
V. Yadav, “Economic Impact of Telehealth Expansion: Analyse the Cost - Effectiveness and Long - Term Economic Implications of The Widespread Adoption of Telehealth Services Post Pandemic,” International Journal of Science and Research (IJSR), vol. 12, no. 6, pp. 2997–3001, Jun. 2023.
V. Yadav, “Healthcare Workforce Economics: Study the Economic Effects of the Changing Demographics of Healthcare Workers, Including the Rise of Gig Economy Roles in Healthcare,” Progress In Medical Sciences, pp. 1–5, Sep. 2022.
Vivek Yadav, “Value-Based Care and Economic Outcomes: Investigate the Correlation Between Value-Based Care Models and Economic Outcomes for Healthcare Providers and Patients”, Journal of Scientific and Engineering Research, vol. 10, no. 3, pp. 132–141, Mar. 2023.
H. A. Al-Asadi, “Energy Efficient Hierarchical Clustering Mechanism for Wireless Sensor Network Fields,” International Journal of Computer Applications, vol. 153, no. 10, pp. 42-46, 2016.
H. A. Al-Asadi, “Hybrid Clustering Methodology using Optical Communication in Wireless Sensor Networks,” International Journal on Advanced Science, Engineering and Information Technology, vol. 7, no. 1, 2017.
H. A. Al-Asadi, “Mobile Clustering Algorithm for Effective Clustering in Dense Wireless Sensor Networks,” European Journal of Advances in Engineering & Technology (EJAET), vol. 4, no. 1, pp. 1-6, 2017.
H. A. Al-Asadi, “Integrated Energy Efficient Clustering Strategy for Wireless Sensor Networks,” The Journal of Middle East and North Africa Sciences, vol. 3, pp. 8-13, 2017.
H. A. Al-Asadi, M. A. Al-Asadi, and N. A. Noori, “Optimization Noise Figure of Fiber Raman Amplifier based on Bat Algorithm in Optical Communication network,” International Journal of Engineering & Technology, vol. 7, no. 2, pp. 874-879, 2018.
H. A. Al-Asadi, and N. A. M. B. A. Hambali, “Experimental evaluation and theoretical investigations of fiber Raman amplifiers and its gain optimization based on single forward pump,” Journal of Laser Applications, vol. 26, no. 4, 2014.
H. A. Al-Asadi, “Nonlinear Phase Shift due to Stimulated Brillouin Scattering in Strong Saturation Regime for Different Types of Fibers,” Journal of Optical Communications (JOC), vol. 36, no. 3, pp. 211–216, 2014.
B. Kumar, H. Shaker, B. Al Ruzaiqi, and R. Al Balushi, “Design and implementation of a smart office network module using visual simulation tool,” J. Namib. Stud., vol. 34, Suppl. 2, pp. 2664–2676, 2023.
B. Kumar, “IoT-based smart greenhouse monitoring system using visual simulation tool,” Int. J. Sci. Math. Technol. Learn., vol. 31, no. 2, pp. 44–58, 2023.
K. Al Aufi and B. Kumar, “Security testing of Android application using Drozer,” in Proc. Int. Conf. Comput. Sci. Sustainable Technol., Springer CCIS, 2024, pp. 8–18.
B. Kumar, I. Al-Busaidi, and M. Halloush, “Healthcare information exchange using blockchain and machine learning,” in Proc. 1st Int. Conf. Innov. Inf. Technol. Business (ICIITB 2022), Springer, 2022, pp. 141–155.
B. Kumar, H. Shaker, and P. Josephmani, “Design and execution of secure smart home environments on visual simulation tool,” in Proc. 1st Int. Conf. Innov. Inf. Technol. Business (ICIITB 2022), Springer, 2022, pp. 200–218.
B. Al Barwani, E. Al Maani, and B. Kumar, “IoT-enabled smart cities: A review of security frameworks, privacy, risks, and key technologies,” in Proc. 1st Int. Conf. Innov. Inf. Technol. Business (ICIITB 2022), Springer, 2022, pp. 169–181.
Y. Al Balushi, H. Shaker, and B. Kumar, “The use of machine learning in digital forensics: Review paper,” in Proc. 1st Int. Conf. Innov. Inf. Technol. Business (ICIITB 2022), vol. 104, Springer, 2022.
M. Kommineni, "Study High-Performance Computing Techniques for Optimizing and Accelerating AI Algorithms Using Quantum Computing and Specialized Hardware," International Journal of Innovations in Applied Sciences & Engineering, vol. 9, no. 1, pp. 48–59, Sep. 2023.
M. Kommineni, "Investigate Computational Intelligence Models Inspired by Natural Intelligence, Such as Evolutionary Algorithms and Artificial Neural Networks," Transactions on Latest Trends in Artificial Intelligence, vol. 4, no. 4, p. 30, Jun. 2023.
M. Kommineni, "Investigating High-Performance Computing Techniques for Optimizing and Accelerating AI Algorithms Using Quantum Computing and Specialized Hardware," International Journal of Innovations in Scientific Engineering, vol. 16, no. 1, pp. 66–80, Nov. 2022.
M. Kommineni, "Discover the Intersection Between AI and Robotics in Developing Autonomous Systems for Use in the Human World and Cloud Computing," International Numeric Journal of Machine Learning and Robots, vol. 6, no. 6, pp. 1–19, Sep. 2022.
M. Kommineni, "Explore Scalable and Cost-Effective AI Deployments, Including Distributed Training, Model Serving, and Real-Time Inference on Human Tasks," International Journal of Advances in Engineering Research, vol. 24, no. 1, pp. 07–27, Jul. 2022.
M. Kommineni, "Explore Knowledge Representation, Reasoning, and Planning Techniques for Building Robust and Efficient Intelligent Systems," International Journal of Inventions in Engineering & Science Technology, vol. 7, no. 2, pp. 105–114, 2021.
A. Thirunagalingam, "AI-Powered Continuous Data Quality Improvement: Techniques, Benefits, and Case Studies," International Journal of Innovations in Applied Sciences & Engineering, vol. 10, no. 1, p. 9, Aug. 2024.
A. Thirunagalingam, "Bias Detection and Mitigation in Data Pipelines: Ensuring Fairness and Accuracy in Machine Learning," AVE Trends in Intelligent Computing Systems, vol. 1, no. 2, pp. 116–127, Jul. 2024.
A. Thirunagalingam, "Combining AI Paradigms for Effective Data Imputation: A Hybrid Approach," International Journal of Transformations in Business Management, vol. 14, no. 1, pp. 49–58, Mar. 2024.
A. Thirunagalingam, "Quantum Computing for Advanced Large-Scale Data Integration: Enhancing Accuracy and Speed," International Journal of Innovations in Applied Sciences & Engineering, vol. 9, no. 1, pp. 60–71, Sep. 2023.
A. Thirunagalingam, "AI for Proactive Data Quality Assurance: Enhancing Data Integrity and Reliability," International Journal of Advances in Engineering Research, vol. 26, no. 2, pp. 22–35, Aug. 2023.
A. Thirunagalingam, "Improving Automated Data Annotation with Self-Supervised Learning: A Pathway to Robust AI Models," International Transactions in Artificial Intelligence, vol. 7, no. 7, pp. 1–22, Jun. 2023.
A. Thirunagalingam, "Federated Learning for Cross-Industry Data Collaboration: Enhancing Privacy and Innovation," International Journal of Sustainable Development Through AI, ML and IoT, vol. 2, no. 1, pp. 1–13, Jan. 2023.
A. Thirunagalingam, “Transforming Real-Time Data Processing: The Impact of AutoML on Dynamic Data Pipelines,” FMDB Transactions on Sustainable Intelligent Networks., vol.1, no.2, pp. 110–119, 2024.
M. A. Al-Khasawneh, A. Alzahrani, and A. Alarood, "An artificial intelligence based effective diagnosis of Parkinson disease using EEG signal," in Data Analysis for Neurodegenerative Disorders, Singapore: Springer Nature Singapore, 2023, pp. 239-251.
V. Kumar, S. Kumar, R. AlShboul, G. Aggarwal, O. Kaiwartya, A. M. Khasawneh, et al., "Grouping and sponsoring centric green coverage model for internet of things," Sensors, vol. 21, no. 12, p. 3948, 2021.
A. M. Khasawneh, O. Kaiwartya, J. Lloret, H. Y. Abuaddous, L. Abualigah, M. A. Shinwan, et al., "Green communication for underwater wireless sensor networks: Triangle metric based multi-layered routing protocol," Sensors, vol. 20, no. 24, p. 7278, 2020.
M. A. Al-Khasawneh, W. Abu-Ulbeh, and A. M. Khasawneh, "Satellite images encryption review," in 2020 International Conference on Intelligent Computing and Human-Computer Interaction (ICHCI), December 2020, pp. 121-125.
S. A. A. Shah, M. A. Al-Khasawneh, and M. I. Uddin, "Review of weapon detection techniques within the scope of street-crimes," in 2021 2nd International Conference on Smart Computing and Electronic Enterprise (ICSCEE), June 2021, pp. 26-37.
I. M. Alfadli, F. M. Ghabban, O. Ameerbakhsh, A. N. AbuAli, A. Al-Dhaqm, and M. A. Al-Khasawneh, "Cipm: Common identification process model for database forensics field," in 2021 2nd International Conference on Smart Computing and Electronic Enterprise (ICSCEE), June 2021, pp. 72-77.
I. Ahmad, S. A. A. Shah, and M. A. Al-Khasawneh, "Performance analysis of intrusion detection systems for smartphone security enhancements," in 2021 2nd International Conference on Smart Computing and Electronic Enterprise (ICSCEE), June 2021, pp. 19-25.
M. Mahmoud and M. A. Al-Khasawneh, "Greedy Intersection‐Mode Routing Strategy Protocol for Vehicular Networks," Complexity, vol. 2020, p. 4870162, 2020.
A. Alarood, N. Ababneh, M. Al-Khasawneh, M. Rawashdeh, and M. Al-Omari, "IoTSteg: ensuring privacy and authenticity in internet of things networks using weighted pixels classification based image steganography," Cluster Computing, vol. 25, no. 3, pp. 1607-1618, 2022.
H. A. Sukhni, M. A. Al-Khasawneh, and F. H. Yusoff, "A systematic analysis for botnet detection using genetic algorithm," in 2021 2nd International Conference on Smart Computing and Electronic Enterprise (ICSCEE), June 2021, pp. 63-66.
O. Krishnamurthy and G. Vemulapalli, "Advancing Sustainable Cybersecurity: Exploring Trends and Overcoming Challenges with Generative AI," in Sustainable Development through Machine Learning, AI and IoT, P. Whig, N. Silva, A. A. Elngar, N. Aneja, and P. Sharma, Eds. Cham, Switzerland: Springer, 2025, vol. 2196, pp. 1-14.
G. Vemulapalli, "Self-service analytics implementation strategies for empowering data analysts," International Journal of Machine Learning and Artificial Intelligence, vol. 4, no. 4, pp. 1-14, 2023.
G. Vemulapalli, "Overcoming data literacy barriers: Empowering non-technical teams," International Journal of Holistic Management Perspectives, vol. 5, no. 5, pp. 1-17, 2024.
G. Vemulapalli, "Architecting for real-time decision-making: Building scalable event-driven systems," International Journal of Machine Learning and Artificial Intelligence, vol. 4, no. 4, pp. 1-20, 2023.
G. Vemulapalli, S. Yalamati, N. R. Palakurti, N. Alam, S. Samayamantri, and P. Whig, "Predicting obesity trends using machine learning from big data analytics approach," 2024 Asia Pacific Conference on Innovation in Technology (APCIT), Mysore, India, 2024, pp. 1-5.
G. Vemulapalli, "AI-driven predictive models strategies to reduce customer churn," International Numeric Journal of Machine Learning and Robots, vol. 8, no. 8, pp. 1-13, 2024.
G. Vemulapalli, "Cloud data stack scalability: A case study on migrating from legacy systems," International Journal of Sustainable Development Through AI, ML and IoT, vol. 3, no. 1, pp. 1-15, 2024.
G. Vemulapalli, "Operationalizing machine learning best practices for scalable production deployments," International Machine Learning Journal and Computer Engineering, vol. 6, no. 6, pp. 1-21, 2023.
G. Vemulapalli, "Optimizing NoSQL database performance: Elevating API responsiveness in high-throughput environments," International Machine Learning Journal and Computer Engineering, vol. 6, no. 6, pp. 1-14, 2023.
G. Vemulapalli, "Optimizing analytics: Integrating data warehouses and lakes for accelerated workflows," International Scientific Journal for Research, vol. 5, no. 5, pp. 1-27, 2023.
Y. F. Saputra and M. A. Al-Khasawneh, "Big data analytics: Schizophrenia prediction on Apache spark," in Advances in Cyber Security: Second International Conference, ACeS 2020, Penang, Malaysia, December 8-9, 2020, Revised Selected Papers 2, Springer Singapore, 2021, pp. 508-522.
S. A. A. Shah, M. A. Al-Khasawneh, and M. I. Uddin, "Street-crimes Modelled Arms Recognition Technique (SMART): Using VGG," in 2021 2nd International Conference on Smart Computing and Electronic Enterprise (ICSCEE), June 2021, pp. 38-44.
A. M. Alghamdi, M. A. Al-Khasawneh, A. Alarood, and E. Alsolami, "The Role of Machine Learning in Managing and Organizing Healthcare Records," Engineering, Technology & Applied Science Research, vol. 14, no. 2, pp. 13695-13701, 2024.
M. A. Al-Khasawneh, M. Faheem, A. A. Alarood, S. Habibullah, and E. Alsolami, "Towards Multi-Modal Approach for Identification and Detection of Cyberbullying in Social Networks," IEEE Access, 2024.
A. O. Alzahrani, M. A. Al-Khasawneh, A. A. Alarood, and E. Alsolami, "A Forensic Framework for gathering and analyzing Database Systems using Blockchain Technology," Engineering, Technology & Applied Science Research, vol. 14, no. 3, pp. 14079-14087, 2024.
M. A. Al-Khasawneh, M. Faheem, A. A. Alarood, S. Habibullah, and A. Alzahrani, "A secure blockchain framework for healthcare records management systems," Healthcare Technology Letters, IEEE, 2024.
P. Pulivarthy, "Enhancing Database Query Efficiency: AI-Driven NLP Integration in Oracle," Transactions on Latest Trends in Artificial Intelligence, vol. 4, no. 4, pp. 1–25, Oct. 2023.
P. Pulivarthy, "Gen AI Impact on the Database Industry Innovations," International Journal of Advances in Engineering Research, vol. 28, no. 3, pp. 1–10, Sep. 2024.
P. Pulivarthy, "Semiconductor Industry Innovations: Database Management in the Era of Wafer Manufacturing," FMDB Transactions on Sustainable Intelligent Networks, vol. 1, no. 1, pp. 15–26, Mar. 2024.
P. Pulivarthy, "Enhancing Dynamic Behaviour in Vehicular Ad Hoc Networks through Game Theory and Machine Learning for Reliable Routing," International Journal of Machine Learning and Artificial Intelligence, vol. 4, no. 4, pp. 1–13, Dec. 2023.
P. Pulivarthy, "Performance Tuning: AI Analyse Historical Performance Data, Identify Patterns, and Predict Future Resource Needs," International Journal of Innovations in Applied Sciences and Engineering, vol. 8, no. 2, pp. 139–155, Nov. 2022.
R. Rai, A. Shrestha, S. Rai, S. Chaudhary, D. K. Acharya, and S. Subedi, “Conversion of farming systems into organic biointensive farming systems and the transition to sustainability in agro-ecology: Pathways towards sustainable agriculture and food systems,” J. Multidiscip. Sci., vol. 6, no. 1, pp. 26–31, Jun. 2024.
S. Rai and R. Rai, “Advancements and practices in budding techniques for kiwifruit propagation,” J. Multidiscip. Sci., vol. 6, no. 1, pp. 26–31, Jun. 2024.
S. Rai and R. Rai, “Monkey menace in Nepal: An analysis and proposed solutions,” J. Multidiscip. Sci., vol. 6, no. 1, pp. 26–31, Jun. 2024.
K. Shrestha, S. Chaudhary, S. Subedi, S. Rai, D. K. Acharya, and R. Rai, “Farming systems research in Nepal: Concepts, design, and methodology for enhancing agricultural productivity and sustainability,” J. Multidiscip. Sci., vol. 6, no. 1, pp. 17–25, May 2024.
S. Rai and R. Rai, “Advancement of kiwifruit cultivation in Nepal: Top working techniques,” J. Multidiscip. Sci., vol. 6, no. 1, pp. 11–16, Feb. 2024.
S. Chaudhary, A. K. Shrestha, S. Rai, D. K. Acharya, S. Subedi, and R. Rai, “Agroecology integrates science, practice, movement, and future food systems,” J. Multidiscip. Sci., vol. 5, no. 2, pp. 39–60, Dec. 2023.
R. Rai, V. Y. Nguyen, and J. H. Kim, “Variability analysis and evaluation for major cut flower traits of F1 hybrids in Lilium brownii var. colchesteri,” J. Multidiscip. Sci., vol. 4, no. 2, pp. 35–41, Dec. 2022.
V. Y. Nguyen, R. Rai, J.-H. Kim, J. Kim, and J.-K. Na, “Ecogeographical variations of the vegetative and floral traits of Lilium amabile Palibian,” J. Plant Biotechnol., vol. 48, no. 4, pp. 236–245, Dec. 2021.
R. Rai and J. H. Kim, “Performance evaluation and variability analysis for major growth and flowering traits of Lilium longiflorum Thunb. genotypes,” J. Exp. Biol. Agric. Sci., vol. 9, no. 4, pp. 439–444, Aug. 2021.
R. Rai, V. Y. Nguyen, and J. H. Kim, “Estimation of variability analysis parameters for major growth and flowering traits of Lilium leichtlinii var. maximowiczii germplasm,” J. Exp. Biol. Agric. Sci., vol. 9, no. 4, pp. 457–463, Aug. 2021.
Published
2024-12-29
How to Cite
M. Gandhi, J. Jayaprakash, B. Vaidianathan, & P. Mahendran. (2024). Disaster Prediction and Risk Management Using Machine Learning and Data Science Techniques for Improved Forecasting. CENTRAL ASIAN JOURNAL OF MATHEMATICAL THEORY AND COMPUTER SCIENCES, 5(6), 643-658. Retrieved from https://cajmtcs.centralasianstudies.org/index.php/CAJMTCS/article/view/708
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