An Efficient Weather Forecasting System using Adaptive Neuro-Fuzzy Inference System

I. Kadar Shereef, Dr. S. Santhosh Baboo


Consistent weather prediction is very important for socio economic development and is necessary for food security of the human society. Because of time immemorial, human race has been absorbed by the increasingly changing and very much dynamic atmosphere around him and has provided significant efforts to recognize the controlling processes and attain better capabilities of weather forecasting. Temperature forecasts are performed by means of gathering quantitative data regarding the progress state of the atmosphere. The author in this paper utilized a neural network-based technique for determining the temperature in future. The Neural Networks package contains different training or learning methods. Fuzzy logic acts as a significant function in decision making procedure. Neuro-fuzzy systems are fuzzy systems which utilizes Artificial Neural Network for the purpose of identifying their properties (fuzzy sets and fuzzy rules) by processing the data. Neuro-fuzzy systems contain the influence of the two techniques: fuzzy logic and ANNs, by using the mathematical characteristics of ANNs in tuning rule-based fuzzy systems that approximate the way man processes the data. Because of these factors, this paper uses Adaptive Neuro-Fuzzy Inference System (ANFIS) for weather forecasting. The experimental result shows that the proposed technique results in better accuracy of prediction when compared to the conventional technique of weather prediction.



Keywords- Multi Layer Perception, Temperature Forecasting, Back propagation, Artificial Neural Network, Adaptive Neuro-Fuzzy Inference System.

Full Text:




  • There are currently no refbacks.

Copyright (c) 2016 International Journal of Advanced Research in Computer Science