Introduction to artificial neural systems
Introduction to artificial neural systems
Neural network design
Neural Networks for Pattern Recognition
Neural Networks for Pattern Recognition
Intelligent weather monitoring systems using connectionist models
Neural, Parallel & Scientific Computations
Weather analysis using ensemble of connectionist learning paradigms
Applied Soft Computing
Application of soft computing models to hourly weather analysis in southern Saskatchewan, Canada
Engineering Applications of Artificial Intelligence
ASM'10 Proceedings of the 4th international conference on Applied mathematics, simulation, modelling
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This paper investigates the development of a reliable and efficient neuro-computing technique to forecast the peak weather in Vancouver, British Columbia, Canada. For developing the models, we used one year's data comprising of daily maximum temperature, wind-speed and visibility. This paper briefly explains how neural network models could be formulated using different learning methods and then investigates whether they can provide the required level of performance, which are sufficiently good and robust to provide a reliable model for practical peak weather forecasting. Experiment results demonstrate that neuro-forecast models show a very good prediction performance and the approach is effective and reliable.