A Comparative Study Review of Soft Computing Approach in Weather Forecasting
Govind Kumar Rahul1, Madhu Khurana2

1Govind Kumar Rahul, M.Tech Student, ABES Engineering College Ghaziabad, MTU Noida, Uttar Pradesh, India
2Prof. Madhu Khurana, Assoc. Professor, ABES Engineering College Ghaziabad, MTU Noida, Uttar Pradesh, India
Manuscript received on November 01, 2012. | Revised Manuscript received on November 02, 2012. | Manuscript published on November 05, 2012. | PP: 295-299 | Volume-2 Issue-5, November 2012. | Retrieval Number: E1053102512/2012©BEIESP
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© The Authors. Published By: Blue Eyes Intelligence Engineering and Sciences Publication (BEIESP). This is an open access article under the CC BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/)

Abstract: In a developing country, like India where the agriculture & industries are base for the national economy, the weather conditions play leading role for their proper development and smooth running. Therefore having accurate weather forecasting information may allow farmers or industry managers to make better decisions on managing their farms. Soft computing using ANN is an innovative approach to construct a computationally intelligent system that is able to process non-linear weather conditions within a specific domain, and make prediction. A number of researches have been done or being done using Soft Computing Approach for forecasting. In this paper the presentation is all about to present the comparative study of several researches and some key findings that are initials for better start any soft computing model for prediction.
Keywords: Soft Computing, Artificial Neural Network (ANN), Back Propagation Algorithms, Multilayer Feed Forward Neural network (MLFFNN), Mean Square Error (MSE) etc.