Design and Development of Artificial Intelligence System for Weather Forecasting Using Soft Computing Techniques
نویسنده
چکیده
The main aim of this paper is to overcome the drawbacks of LIDAR which are non-linearity in climatic physics based on statistical modeling and evaluation. However, modeling is shown to be a successful method to forecast weather parameters by using different types of Soft Computing Techniques such as Neural Networks, Fuzzy Logic and Probability Theory which are suitable to these meteorological processes for prediction of an important weather parameter that is temperature. Design and development of different types of Soft Computing Techniques approaches in an agricultural systems based on objective of predicting the temperature (one day ahead forecasting of temperature from selected meteorological data) and tested using eighty years past data (meteorological data) and to evaluate the different types of Soft Computing Techniques which depicts that the performance. The results are carried out using MATLAB software.
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