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Hemant Kumar Soni

Work place: Department of Computer Science and Engineering, Amity School of Engineering and Technology, Amity University, Gwalior, Madhya Pradesh, India

E-mail: hksoni@gwa.amity.edu

Website:

Research Interests: Computer systems and computational processes, Autonomic Computing, Data Mining, Data Structures and Algorithms

Biography

Hemant Kumar Soni received M.Sc. in Computer Science from Jiwaji University, Gwalior, Madhya Pradesh, India in the year 1996 and  M. Tech (IT) from Bundelkhand University, Jhansi, Uttar Pradesh, India in the year 2006. He is pursuing Doctoral degree in Computer Science and Engineering from Amity University Madhya Pradesh, Gwalior, India. He has 21 years of teaching experience for UG and PG courses in Computer Science and presently working as Head of the Department of Computer Science and Engineering at Amity University, Gwalior, Madhya Pradesh, India. His research interest in Data Mining and Soft Computing. He published many research papers in National, International Conferences and Scopus Indexed Journals. He is Reviewer of many referred journals. He received a Best Paper Award in an International Conference and organized number of National level events and conferences. He is a member of International Association of Engineers, Hongkong, Universal Association of Computer and Electronics Engineers (UACEE), The Institute of Research Engineers and Doctors, USA, Life Member of ISTE (Indian Society for Technical Education), India and Member of IAENG Society of Computer Science and Data Mining, Hong King.

Author Articles
Development and Analysis of Artificial Neural Network Models for Rainfall Prediction by Using Time-Series Data

By Neelam Mishra Hemant Kumar Soni Sanjiv Sharma A K Upadhyay

DOI: https://doi.org/10.5815/ijisa.2018.01.03, Pub. Date: 8 Jan. 2018

Time Series data is large in volume, highly dimensional and continuous updating. Time series data analysis for forecasting, is one of the most important aspects of the practical usage. Accurate rainfall forecasting with the help of time series data analysis will help in evaluating drought and flooding situations in advance. In this paper, Artificial Neural Network (ANN) technique has been used to develop one-month and two-month ahead forecasting models for rainfall prediction using monthly rainfall data of Northern India. In these model, Feed Forward Neural Network (FFNN) using Back Propagation Algorithm and Levenberg- Marquardt training function has been used. The performance of both the models has been assessed based on Regression Analysis, Mean Square Error (MSE) and Magnitude of Relative Error (MRE). Proposed ANN model showed optimistic results for both the models for forecasting and found one month ahead forecasting model perform better than two months ahead forecasting model. This paper also gives some future directions for rainfall prediction and time series data analysis research.

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