Abstract
Fuzzy Cognitive Map (FCM), which was first proposed by Kosko in 1986, is a novel tool for knowledge description and management. In this paper, we propose a new approach to mine the FCMs on the basis of data resource. First, raw data stored in the databases is preprocessed and converted to a fixed interval. Then, we adopt a novel hybrid optimization algorithm DE-SQP to produce the optimal weight matrix, whose goal is to make the weights fit the historical data best. At last, we apply the proposed method to solve a real-world problem. The experimental results show that the method is effective and efficient to mine the casual relationships hidden in the data resources by using the hybrid algorithm DE-SQP and the construction of FCMs gets rid of the intervention of domain experts, which guarantees the objectivity and completeness of the FCMs.
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Shou, W., Fan, W., Liu, B. (2012). A Data-Based Fuzzy Cognitive Map Mining Method Using DE-SQP Algorithm. In: Xiao, T., Zhang, L., Fei, M. (eds) AsiaSim 2012. AsiaSim 2012. Communications in Computer and Information Science, vol 325. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-34387-2_5
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DOI: https://doi.org/10.1007/978-3-642-34387-2_5
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-642-34386-5
Online ISBN: 978-3-642-34387-2
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