DIGMAP-detector: an intelligent computerized tool to detect and predict digital map pattern
ACE'10 Proceedings of the 9th WSEAS international conference on Applications of computer engineering
Introducing an intelligent computerized tool to detect and predict urban growth pattern
WSEAS Transactions on Computers
Current trends on knowledge extraction and neural networks
ICANN'05 Proceedings of the 15th international conference on Artificial neural networks: formal models and their applications - Volume Part II
Hybrid recommendation approaches for multi-criteria collaborative filtering
Expert Systems with Applications: An International Journal
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This paper presents a novel supervised ART neural network named Impulse Force based ART (IFART) neural network. It enhances the prediction accuracy of the supervised ART neural network using Genetic Algorithm optimized Impulse Forces on attributes optimized by Genetic Algorithm, which identify the different effect of input attributes on category results. However, the IFART neural network is still a black box and difficult to understand, which is the disadvantage of artificial neural network. In this paper, a method to extract IF-THEN rules from the trained IFART neural network according to its architecture is proposed to interpret the neural network. Furthermore, the rules are refined in terms of their used frequency. Finally, IFART neural network is applied to predict the magnitude of earthquake.