Temperature and Relative Humidity forecasting based on Neuro-Fuzzy System

摘要

The Temperature and relative humidity forecasting is the application of science and technology to predict the state of the temperature forecasts are made by collecting quantitative data about the current state of the atmosphere. This paper utilizes intelligence system for one step time interval ahead prediction of an important weather parameter which is temperature and relative humidity. Our study are forecasting temperature model based on Intelligence system such as Neural network and our proposed neuro-fuzzy which trained and tested using one year past(2010) weather data. We compared our forecasting model with another intelligence system. The results show that our proposed neuro-fuzzy has minimum forecasting error and can be considered as a good method for temperature and relative humidity forecasting. Thus, our proposed temperature and humidity forecasting model can be applied to calculating cooling load of building for energy management.