Temperature Prediction Using a Neofuzzy Neuron Approach

In this paper it’s presented a temperature prediction application using a modified neofuzzy neuronbased approach. This approach is an easy and accurate method for obtaining prediction results using climatic measurements from the previous days. The variables used for building the model are Temperature, Humidity, Dew Point, Wind speed, Pressure, Rain and Solar Radiation. It’s also presented the obtained results for temperature prediction in Ibarra, Ecuador using three years data.