Applying case-based reasoning: techniques for enterprise systems
Applying case-based reasoning: techniques for enterprise systems
An investigation of machine learning based prediction systems
Journal of Systems and Software - Special issue on empirical studies of software development and evolution
Dynamic Memory: A Theory of Reminding and Learning in Computers and People
Dynamic Memory: A Theory of Reminding and Learning in Computers and People
Multiperiod forecasting in stock markets: a paradox solved
Decision Support Systems - Special issue: Data mining for financial decision making
Evolving neural network for printed circuit board sales forecasting
Expert Systems with Applications: An International Journal
Expert Systems with Applications: An International Journal
Combining SOM and fuzzy rule base for sale forecasting in printed circuit board industry
ISNN'05 Proceedings of the Second international conference on Advances in Neural Networks - Volume Part III
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This paper proposes a hybrid system that is developed by evolving Fuzzy Case-Based Reasoning (FCBR) with Genetic Algorithm (GA), for reverse sales forecasting of returning books. FCBR systems have been successfully applied in several domains of artificial intelligence. However, in conventional FCBR method each factor has the same weight which means each one has the same influence on the output data that does not reflect the practical situation. In order to enhance the efficiency and capability of forecasting in FCBR systems, we connected the GAs method to adjust the weights of factors in FCBR systems, GAFCBR for short. The case base of this research is acquired from a book wholesaler in Taiwan, and it is applied by the hybrid system to forecast returning books. The results of the prediction of the hybrid system were compared with the results of a back propagation neural network (BPNN), a conventional CBR, and a multiple-regression analysis method. The experimental results show that the GAFCBR is more accurate and efficient when being applied to the forecast of the returning books than other methods.