Rainfall Prediction Using Regression and Classification Analysis
AbstractThe use of logistic regression modeling for the purposes of prediction and forecasting has seen meteoric growth over the last ten years, as was suggested by our study. The occurrence of rainfall is among the most significant aspects of the climate system. It is common knowledge that changes in the frequency and severity of rainfall may have an effect on natural systems, agricultural systems, human systems, and even whole biological systems. Therefore, it is of the utmost importance to be able to forecast rainfall by determining the factors that are reliable predictors. In this article, an effort is made to forecast rainfall by using logistic regression. The results of this endeavor are presented. Despite the fact that this issue often escapes the attention of the analysts, it is abundantly clear that the meteorological data are frequently affected by significant recording inaccuracies. In this research, we have utilized fairly modern screening techniques to verify and rectify the climatic data that we use in our study. This is something that we have done in order to ensure the accuracy of the data. The suggested approach has an accuracy of 88%. Some keywords that go together with accuracy include machine learning, regression, and rainfall.
Kala, A., & Vaidyanathan, S. G. Prediction of rainfall using artificial neural network. 2018 International Conference on Inventive Research in Computing Applications (ICIRCA)
Grace, R. K., &Suganya, B. (2020, March). Machine Learning based Rainfall Prediction. 2020 6th International Conference on Advanced Computing and Communication Systems (ICACCS)
Ahmed, H. A. Y., & Mohamed, S. W. A. (2021, February 26). Rainfall Prediction using Multiple Linear Regressions Model. 2020 International Conference on Computer, Control, Electrical, and Electronics Engineering (ICCCEEE).
A. K. Velmurugan, K. Padmanaban, A. M. Senthil Kumar, H. Azath, and Murugan Subbiah , “Machine learning IoT based framework for analysing heart disease prediction,” AIP Conference Proceedings, vol. 2523, pp. 1-8, pp. 1-7, 2023.
K. Padmanaban, A. M. Senthil Kumar, H. Azath, A. K. Velmurugan, and Murugan Subbiah , “Hybrid data mining technique based breast cancer prediction,” AIP Conference Proceedings, vol.2523, no. 1, pp. 1-7, 2023.
H. Azath, A. K. Velmurugan, K. Padmanaban, A. M. Senthil Kumar, and Murugan Subbiah , “Ant based routing algorithm for balanced the load and optimized the AMNET lifetime,” AIP Conference Proceedings, vol. 2523, pp. 1-9, 2023.
M. Senthil Kumar, H. Azath, A. K. Velmurugan, K. Padmanaban, and Murugan Subbiah, “Prediction of Alzheimer's disease using hybrid machine learning technique,” AIP Conference Proceedings, vol. 2523, pp. 1-6, 2023.
V. Jaiganesh, S. Murugan, “PC based heart rate monitor implemented in xilinx fpga and analysing the heart rate,” Proceedings of the Third IASTED International Conference on Circuits, Signals, and Systems, pp. 319–323, 2005.
A. Balaji, V. P. Srinivasan, J. Rangarajan, V. Nagaraju, B. Bharathi and S. Murugan, “Smart Technique to Prevent Flood Disaster due to High Rainfall in Coastal Areas using IoT,” 2023 International Conference on Intelligent and Innovative Technologies in Computing, Electrical and Electronics, pp. 1252-1256, 2023.
P. Arul, M. Meenakumari, N. Revathi, S. Jayaprakash, and S. Murugan, “Intelligent Power Control Models for the IOT Wearable Devices in BAN Networks,” 2023 International Conference on Intelligent and Innovative Technologies in Computing, Electrical and Electronics, pp. 820-824, 2023.
Manish Kumar Goyal and Ashutosh Sharma. (2015) “Bayesian network model for monthly rainfall forecast,” IEEE, International Conference on Research in Computational Intelligence and Communication Networks (ICRCICN).
A.D Dubey. (2015) “Artificial neural network models for rainfall prediction in Pondicherry,” International Journal of Computer Applications, vol 120, no. 3.
D.R. Nayak, A. Mahapatra, and P. Mishra. (2013) “A survey on rainfall prediction using artificial neural network,” International Journal of Computer Applications, vol. 72, no. 16.
Pratyush, “Application of Artificial Neural Networks in Civil Engineering”, September 2016.
Sankhadeep Chatterjee, Subhodeep Ghosh, Subham Dawn,SirshenduHore and Nilanjan Dey, “Forest Type Classification: A Hybrid NN-GA Model Based Approach”, May 2016.
R Praveena, TR Ganesh Babu, M Birunda, G Sudha, P Sukumar, J Gnanasoundharam, Prediction of Rainfall Analysis Using Logistic Regression and Support Vector Machine, Journal of Physics: Conference Series.
R Praveena, DK Ravish, TR Ganesh Babu, J Preetha, Design and Development of Vibroarthogram Screening Device And Assessment Of Joint Motion In The Pursuit Of Signal Processing, ICTACT Journal On Image And Video Processing.
R Praveena T R Ganeshbabu, Determination of Cup to Disc Ratio Using Unsupervised Machine Learning Techniques for Glaucoma Detection,Molecular & Cellular Biomechanics
M Vanitha, TR Ganesh Babu, R Praveena, M Sathyapriya, Segmentation and classification of Gallstone in ultrasound images of gall bladder using Support Vector Machine, 13th International Conference on Computing Communication and Networking Technologies
Poovizhi S, Ganesh Babu TR, An efficient skin cancer diagnostic system using Bendlet Transform and support vector machine, Anais da Academia Brasileira de Ciências
This work is licensed under a Creative Commons Attribution-NonCommercial 4.0 International License.
Authors need to sign following agreement with International Journal of MC Square Scientific Research before publishing their articles:
- Authors need to return copyright form to Journal Editor-in-chief to proceed their articles for publication. Meantime, the journal licensed under a Creative Commons Attribution License, which permits other user to distribute the work with an acknowledgement of the authors for International Journal of MC Square Scientific Research.
- Authors are also able to share their separate, additional contractual arrangements for the non-restricted contribution of the journal with an acknowledgement of publication in International Journal of MC Square Scientific Research.
- Authors are allowed and encouraged to share their work during the submission process for increasing citation and exploring to increase the paper availability in worldwide way. The Effect of Open Access.