Content area
Full text
Piyush Kapoor 1 and Sarabjeet Singh Bedi 2
Academic Editor:W.-L. Hwang and Academic Editor:G. A. Tsihrintzis
1, Kvantum Inc., Gurgaon 122001, India
2, MJP Rohilkhand University, Bareilly 243006, India
Received 7 June 2013; Accepted 19 August 2013
This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
1. Introduction
Weather forecasting is mainly concerned with the prediction of weather condition in the given future time. Weather forecasts provide critical information about future weather. There are various approaches available in weather forecasting, from relatively simple observation of the sky to highly complex computerized mathematical models. The prediction of weather condition is essential for various applications. Some of them are climate monitoring, drought detection, severe weather prediction, agriculture and production, planning in energy industry, aviation industry, communication, pollution dispersal, and so forth, [1]. In military operations, there is a considerable historical record of instances when weather conditions have altered the course of battles. Accurate prediction of weather conditions is a difficult task due to the dynamic nature of atmosphere. The weather condition at any instance may be represented by some variables. Out of those variables, one found that the most significant are being selected to be involved in the process of prediction. The selection of variables is dependent on the location for which the prediction is to be made. The variables and their range always vary from place to place. The weather condition of any day has some relationship with the weather condition existed in the same tenure of precious year and previous week.
A statistical model is designed [2] that could predict the rainfall and temperature with the help of past data by making use of time-delayed feed forward neural network. Artificial neural network was combined with the genetic algorithm to get the more optimized prediction [3]. An improved technique that uses artificial neural network with photovoltaic system was proposed by Isa et al. [4] that utilizes perceptron model with Levenberg Marquardt algorithm. Apart from neural network Fuzzy logic has also been being used in weather prediction models. The rainfall was classified into three fuzzy sets which can be predicted by making use of simple...