A case-based reasoning approach to local-scale and short-term weather forecast

As an intelligent computing paradigm Case-Based Reasoning (CBR) techniques have been studied and adopted in weather forecast applications recently. Nonetheless, many subtle issues remain to be resolved for CBR to be a practical problem solver. This paper establishes a CBR system for local-scale and short-term weather forecast at an airport. We develop a strategy of knowledge guidance combined with nearest-similarity and design a heuristic similarity function accordingly. Real data based tests have shown the effectiveness and comparative advantages of the proposed method.

[1]  D. Singh,et al.  Improvement in nearest neighbour weather forecast model performance while considering the previous day's forecast for drawing forecast for the following day , 2006 .

[2]  Kan Li,et al.  Fuzzy case-based reasoning: weather prediction , 2002, Proceedings. International Conference on Machine Learning and Cybernetics.

[3]  Md. Nasir Sulaiman,et al.  An effective fuzzy C-mean and type-2 fuzzy logic for weather forecasting. , 2009 .

[4]  Mian M. Awais,et al.  Predicting weather events using fuzzy rule based system , 2011, Appl. Soft Comput..

[5]  Sai Ji,et al.  A Method of Weather Cases Generation Based on Similarity Rough Set , 2009, 2009 International Conference on Management and Service Science.

[6]  A. Sharma,et al.  A Weather Forecasting System using concept of Soft Computing: A new approach , 2006, 2006 International Conference on Advanced Computing and Communications.