Development of Temperature-based Weather Forecasting Models Using Neural Networks and Fuzzy Logic

In critical fields such as flight, agriculture, tourism, etc, forecasting is an important issue due to its effectiveness in human life to know what will happen for unpredictable situations and events. Weather forecasts provide critical information about future weather conditions. Actually, weather forecasting plays an important role in our daily life by predicting what the weather will be tomorrow and it is reflected in a wide area of applications in our life so, we can prevent huge damages by forecasting the coming of storms or typhoons or get benefits from the forecasting activities. The temperature warnings are important forecasts because they are used to protect life and property and to improve the efficiency of operations. We propose computer-based models for weather forecasting based on temperature to predict the daily temperature using two techniques, artificial neural networks and fuzzy logic. The main purpose from this study is to develop different weather forecasting models based on the two techniques over different regions. The developed models show that the objectives of the study were achieved successfully. Finally, the models have been tested and the results confirm that the proposed models are capable to forecast the daily temperatures.