Call for Papers:Vol.10 Issue.6

Submission
Last date		 30-Dec-2024
Acceptance Status In One Day
Paper Publish In Two Days
Submit ManuScript

News & Updates

Submit Article

Dear Authors, Article publish in our journal for Volume-10,Issue-6. For article submission on below link: Submit Manuscript


Join As Board

Dear Reviewer, You can join our Reviewer team without given any charges in our journal. Submit Details on below link: Join As Board


Paper Publication Charges

IJARIIE APP
Download Android App

For Authors

Archives

IJARIIE Board

Downloads

Android App

Download IJARIIE APP

Authors

Title: :  A REVIEW ON RAINFALL PREDICTION USING MACHINE LEARNING ALGORITHMS: MLR AND ARTIFICIAL NEURAL NETWORK
PaperId: :  17279
Published in:   International Journal Of Advance Research And Innovative Ideas In Education
Publisher:   IJARIIE
e-ISSN:   2395-4396
Volume/Issue:    Volume 8 Issue 3 2022
DUI:    16.0415/IJARIIE-17279
Licence: :   IJARIIE is licensed under a Creative Commons Attribution-ShareAlike 4.0 International License.

Author NameAuthor Institute
Varsha T. PatilSharad Institute of Technology College of Engineering, Yadrav, Maharashtra
Susmita S. KoreSharad Institute of Technology College of Engineering, Yadrav, Maharashtra
Manik R. PatilSharad Institute of Technology College of Engineering, Yadrav, Maharashtra
Rucha S. UpadhyeSharad Institute of Technology College of Engineering, Yadrav, Maharashtra
Prachi P. LangdeSharad Institute of Technology College of Engineering, Yadrav, Maharashtra

Abstract

Computer Engineering
Rainfall prediction, Machine learning algorithms, MLR, Artificial Neural network
Rainfall is the main source of income for the majority of our country's economy. Agriculture is considered as the key source of income for the economy. A good estimate of rainfall is required to make proper agricultural investments. Rainfall forecasting is required for individuals living in coastal areas, in addition to agriculture. People living near the seaside are at a higher danger of heavy rain and flooding, therefore they should be aware of the weather forecast far in advance so that they can plan their stay accordingly. The prediction helps people in taking preventative steps, and it should also be accurate. Rainfall forecasting accuracy is important for countries like India, whose economy is heavily dependent on agriculture. To predict rainfall, a variety of machine learning models are used, including Multiple Linear Regression, Neural networks, K-means, Nave Bayes, and others. By extracting, training, and testing data sets and identifying and predicting rainfall, these systems accomplish one of these applications. This paper proposes a rainfall prediction model based on Multiple Linear Regression (MLR) and Artificial Neural networks for the given dataset. To identify the best technique to predict rainfall, study examined at both machine learning and neural networks, and the algorithm that gave the best results was employed in the prediction. Multiple meteorological parameters, such as humidity, minimum temperature, maximum temperature, pressure, cloud, wind, and so on, are included in the input data in order to estimate rainfall. The proposed model is validated using the Mean Absolute Error (MAE), accuracy, and correlation metrics. According to the results, the proposed machine learning model beats other algorithms in the literature.

Citations

Copy and paste a formatted citation or use one of the links to import into a bibliography manager and reference.

IJARIIE Varsha T. Patil, Susmita S. Kore, Manik R. Patil, Rucha S. Upadhye, and Prachi P. Langde. "A REVIEW ON RAINFALL PREDICTION USING MACHINE LEARNING ALGORITHMS: MLR AND ARTIFICIAL NEURAL NETWORK" International Journal Of Advance Research And Innovative Ideas In Education Volume 8 Issue 3 2022 Page 3651-3656
MLA Varsha T. Patil, Susmita S. Kore, Manik R. Patil, Rucha S. Upadhye, and Prachi P. Langde. "A REVIEW ON RAINFALL PREDICTION USING MACHINE LEARNING ALGORITHMS: MLR AND ARTIFICIAL NEURAL NETWORK." International Journal Of Advance Research And Innovative Ideas In Education 8.3(2022) : 3651-3656.
APA Varsha T. Patil, Susmita S. Kore, Manik R. Patil, Rucha S. Upadhye, & Prachi P. Langde. (2022). A REVIEW ON RAINFALL PREDICTION USING MACHINE LEARNING ALGORITHMS: MLR AND ARTIFICIAL NEURAL NETWORK. International Journal Of Advance Research And Innovative Ideas In Education, 8(3), 3651-3656.
Chicago Varsha T. Patil, Susmita S. Kore, Manik R. Patil, Rucha S. Upadhye, and Prachi P. Langde. "A REVIEW ON RAINFALL PREDICTION USING MACHINE LEARNING ALGORITHMS: MLR AND ARTIFICIAL NEURAL NETWORK." International Journal Of Advance Research And Innovative Ideas In Education 8, no. 3 (2022) : 3651-3656.
Oxford Varsha T. Patil, Susmita S. Kore, Manik R. Patil, Rucha S. Upadhye, and Prachi P. Langde. 'A REVIEW ON RAINFALL PREDICTION USING MACHINE LEARNING ALGORITHMS: MLR AND ARTIFICIAL NEURAL NETWORK', International Journal Of Advance Research And Innovative Ideas In Education, vol. 8, no. 3, 2022, p. 3651-3656. Available from IJARIIE, https://ijariie.com/AdminUploadPdf/A_REVIEW_ON_RAINFALL_PREDICTION_USING_MACHINE_LEARNING_ALGORITHMS__MLR_AND_ARTIFICIAL_NEURAL_NETWORK_ijariie17279.pdf (Accessed : ).
Harvard Varsha T. Patil, Susmita S. Kore, Manik R. Patil, Rucha S. Upadhye, and Prachi P. Langde. (2022) 'A REVIEW ON RAINFALL PREDICTION USING MACHINE LEARNING ALGORITHMS: MLR AND ARTIFICIAL NEURAL NETWORK', International Journal Of Advance Research And Innovative Ideas In Education, 8(3), pp. 3651-3656IJARIIE [Online]. Available at: https://ijariie.com/AdminUploadPdf/A_REVIEW_ON_RAINFALL_PREDICTION_USING_MACHINE_LEARNING_ALGORITHMS__MLR_AND_ARTIFICIAL_NEURAL_NETWORK_ijariie17279.pdf (Accessed : )
IEEE Varsha T. Patil, Susmita S. Kore, Manik R. Patil, Rucha S. Upadhye, and Prachi P. Langde, "A REVIEW ON RAINFALL PREDICTION USING MACHINE LEARNING ALGORITHMS: MLR AND ARTIFICIAL NEURAL NETWORK," International Journal Of Advance Research And Innovative Ideas In Education, vol. 8, no. 3, pp. 3651-3656, May-Jun 2022. [Online]. Available: https://ijariie.com/AdminUploadPdf/A_REVIEW_ON_RAINFALL_PREDICTION_USING_MACHINE_LEARNING_ALGORITHMS__MLR_AND_ARTIFICIAL_NEURAL_NETWORK_ijariie17279.pdf [Accessed : ].
Turabian Varsha T. Patil, Susmita S. Kore, Manik R. Patil, Rucha S. Upadhye, and Prachi P. Langde. "A REVIEW ON RAINFALL PREDICTION USING MACHINE LEARNING ALGORITHMS: MLR AND ARTIFICIAL NEURAL NETWORK." International Journal Of Advance Research And Innovative Ideas In Education [Online]. volume 8 number 3 ().
Vancouver Varsha T. Patil, Susmita S. Kore, Manik R. Patil, Rucha S. Upadhye, and Prachi P. Langde. A REVIEW ON RAINFALL PREDICTION USING MACHINE LEARNING ALGORITHMS: MLR AND ARTIFICIAL NEURAL NETWORK. International Journal Of Advance Research And Innovative Ideas In Education [Internet]. 2022 [Cited : ]; 8(3) : 3651-3656. Available from: https://ijariie.com/AdminUploadPdf/A_REVIEW_ON_RAINFALL_PREDICTION_USING_MACHINE_LEARNING_ALGORITHMS__MLR_AND_ARTIFICIAL_NEURAL_NETWORK_ijariie17279.pdf
BibTex EndNote RefMan RefWorks

Number Of Downloads



Save in Google Drive

Similar-Paper

TitleArea of ResearchAuther NameAction
Development of Wireless Sensor Network Protocol using Fuzzy logic and Optimization Routing AlgorithmComputer ScienceMs.Dimpal Patel Download
GreenTech Urbanism: The Role of IoT and Machine Learning in Environmental MonitoringComputer Science and EngineeringSowmya Shetty Download
SURVEY ON DETECTION OF PHISHING WEBSITE USING MACHINE LEARNINGComputer Science and EngineeringYawalkar Prasad Pramod Download
Enhancement of Health Data Accuracy Using Neural Network Algorithmneaural networkGautam Prakash Download
AI-BASED PLACEMENT PARTNER: ENHANCING CAREER PREPARATION THROUGH ADVANCED LEARNING TECHNOLOGIESComputer Science & EngineeringSaranya MK Download
ARTIFICIAL INTELLIGENCE IN HEALTH CARE - AN OVERVIEWComputer EngineeringPaleti Surekha Download
A Comparative Study of Maze-Solving Algorithms: Performance, Complexity, and Practical Applications in AI and RoboticsComputer EngineeringNakka Sai Magh Reddy Download
Encryption and Decryption WebsiteComputer Science and EngineeringGokul Kumar R Download
Digital BiomarkersComputer EngineeringHemakanth Sharma R Download
ENSURING FAIRNESS AND TRANSPARENCY IN AI SYSTEMS FOR HEALTHCARE AND CRIMINAL JUSTICE APPLICATIONSComputer EngineeringManu Gowda Download
Utilising AI for Deepfake Detection: Strategies, Issues and Future OpportunitiesArtificial intelligence Suhas LK Download
Cryptography-An OverviewComputer EngineeringPeram Bairaveswar Reddy Download
The Internet of Things (IoT) in Smart CitiesComputer engineeringRahul Malagitti Download
Cloud Computing - An OverviewComputer EngineeringHarshith Y Download
Operations of Artifical Intelligence in 5g NetworkingComputer Engineering Chethan K Download
12