Abstract
In this research a three staged hybrid genetic-fuzzy systems modeling methodology is developed and applied to an empirical data set in order to determine the hidden fuzzy if-then rules. The empirical data was collected in an earlier study in order to establish the relations among human capital, organizational support and innovativeness. The results demonstrate that the model based on the fuzzy if-then rules outperforms more traditional techniques. Furthermore, the proposed methodology is a valuable tool for successful knowledge management.
This work has been supported in part by the Andalusian Government (Spain) under grant P07-TIC-3185 and in part by The Scientific and Technological Research Council of Turkey under grant TUBITAK -2219.
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Kilic, K., Casillas, J. (2012). Hybrid Genetic-Fuzzy System Modeling Application in Innovation Management. In: Casillas, J., Martínez-López, F., Corchado Rodríguez, J. (eds) Management Intelligent Systems. Advances in Intelligent Systems and Computing, vol 171. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-30864-2_3
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DOI: https://doi.org/10.1007/978-3-642-30864-2_3
Publisher Name: Springer, Berlin, Heidelberg
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