Optimization Enabled Neural Network for the Rainfall Prediction in India

被引：0

作者：

Mukkala, Ananda R. Kumar ^{[1
]}

Reddy, S. Sai Satyanarayana ^{[1
]}

Raju, P. Praveen ^{[2
]}

Mounica ^{[2
]}

Oguri, Chiranjeevi ^{[2
]}

Bhukya, Srinivasu ^{[2
]}

机构：

[1] Sreyas Inst Engn & Technol, Dept CSE, Hyderabad 500068, India

[2] Sreyas Inst Engn & Technol, Dept ECE, Hyderabad 500068, India

来源：

ADVANCES IN COMPUTING AND DATA SCIENCES (ICACDS 2022), PT II | 2022年 / 1614卷

关键词：

NARX neural network; Rainfall prediction; Spotted hyena; Indian rainfall data; RMSE; MONSOON RAINFALL; SERIES;

D O I：

10.1007/978-3-031-12641-3_2

中图分类号：

TP18 [人工智能理论];

学科分类号：

081104 ; 0812 ; 0835 ; 1405 ;

摘要：

Rainfall prediction plays a major role in ensuring the livelihood of many people especially, for the farmers. Heavy and irregular flow of rainfall can cause flood, landslide and much other destruction. To prevent this, rainfall should be predicted in a periodic manner. As a contribution, the proposed Spotted Hyena based nonlinear autoregressive model (SH-NARX) prediction model effectively predicts the rainfall in a yearly, monthly and quarterly manner using the Indian rainfall dataset. The data is collected and trained using the NARX neural network, which is a non linear autoregressive network that is optimized using the spotted hyena optimization for rainfall prediction. The performance of the prediction model is analyzed based on RMSE and PRD that are minimal, highlighting the higher accuracy rates.

引用

页码：12 / 23

页数：12

共 50 条

[1] All India summer monsoon rainfall prediction using an artificial neural network
Sahai, AK
Soman, MK
Satyan, V
[J]. CLIMATE DYNAMICS, 2000, 16 (04) : 291 - 302
[2] All India summer monsoon rainfall prediction using an artificial neural network
A. K. Sahai
M. K. Soman
V. Satyan
[J]. Climate Dynamics, 2000, 16 : 291 - 302
[3] Ensemble Prediction of Monthly Mean Rainfall with a Particle Swarm Optimization-Neural Network Model
Jin, Long
Huang, Ying
Zhao, Hua-sheng
[J]. 2012 IEEE 13TH INTERNATIONAL CONFERENCE ON INFORMATION REUSE AND INTEGRATION (IRI), 2012, : 287 - 294
[4] Rainfall Prediction: A Comparative Study of Neural Network Architectures
Sardeshpande, Kaushik D.
Thool, Vijaya R.
[J]. EMERGING TECHNOLOGIES IN DATA MINING AND INFORMATION SECURITY, IEMIS 2018, VOL 1, 2019, 755 : 19 - 28
[5] Comparative Study of Neural Network Architectures for Rainfall Prediction
Manek, Aishwarya Himanshu
Singh, Parikshit Kishor
[J]. 2016 IEEE INTERNATIONAL CONFERENCE ON TECHNOLOGICAL INNOVATIONS IN ICT FOR AGRICULTURE AND RURAL DEVELOPMENT (TIAR), 2016, : 171 - 174
[6] Artificial Neural Network for Monthly Rainfall Rate Prediction
Purnomo, H. D.
Hartomo, K. D.
Prasetyo, S. Y. J.
[J]. 1ST ANNUAL APPLIED SCIENCE AND ENGINEERING CONFERENCE (AASEC), IN CONJUCTION WITH THE INTERNATIONAL CONFERENCE ON SPORT SCIENCE, HEALTH, AND PHYSICAL EDUCATION (ICSSHPE), 2017, 180
[7] Feed Forward Neural Network Modeling for Rainfall Prediction
Yasin, Hasbi
Warsito, Budi
Santoso, Rukun
[J]. 3RD INTERNATIONAL CONFERENCE ON ENERGY, ENVIRONMENTAL AND INFORMATION SYSTEM (ICENIS 2018), 2018, 73
[8] Rainfall Prediction using Hybrid Neural Network approach
Chatterjee, Sankhadeep
Datta, Bimal
Sen, Soumya
Dey, Nilanjan
Debnath, Narayan C.
[J]. PROCEEDINGS OF 2018 2ND INTERNATIONAL CONFERENCE ON RECENT ADVANCES IN SIGNAL PROCESSING, TELECOMMUNICATIONS & COMPUTING (SIGTELCOM 2018), 2018, : 67 - 72
[9] Artificial Neural Network for Markov Chaining of Rainfall Over India
Pabreja, Kavita
[J]. INTERNATIONAL JOURNAL OF BUSINESS ANALYTICS, 2020, 7 (03) : 71 - 84
[10] Monthly rainfall prediction using wavelet regression and neural network: an analysis of 1901–2002 data, Assam, India
Manish Kumar Goyal
[J]. Theoretical and Applied Climatology, 2014, 118 : 25 - 34

← 1 2 3 4 5 →