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Memetic Framework Application—Analysis of Corporate Customer Attitude in Telecom Sector

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Artificial Intelligence and Evolutionary Algorithms in Engineering Systems

Part of the book series: Advances in Intelligent Systems and Computing ((AISC,volume 325))

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Abstract

Natural and cultural evolutionary processes shall be well implemented in the real-time applications by using memetic computing process. Popular researches based on the evolutionary processes have been dealing with the universal criteria. So the need for location-dependent population searches lead to the research based on the cultural traits of the individual, i.e., memetic computational applications. In the telecom sector, the decision-making process of the corporate customers is taken for study with the applications based on the memetic computation. This paper presents an innovative approach to analyze the customer attitude with objective, subjective, and inter-subjective criteria in the multi-attribute deterministic environment. The two metrics, viz. value of business (VOB) and number of services (NOS), are taken as reference using the memetic attributes. Experimental analysis shows that with respect to the telecom sector, memetic framework has improvised the corporate customer attitude toward the services in the betterment of customer relation management.

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References

  1. K.C. Tan, E.F. Khor, T.H. Lee, Multiobjective Evolutionary Algorithms and Applications. Advanced Information and Knowledge Processing (Springer, Berlin 2005)

    Google Scholar 

  2. X.S. Yang, Nature-Inspired Metaheuristic Algorithms (Luniver press, 2008)

    Google Scholar 

  3. Y. Jin, J. Branke, Evolutionary optimization in uncertain environments: a survey. IEEE Trans. Evol. Comput. 9(3), 303–317 (2005)

    Article  Google Scholar 

  4. K. Miettinen, Evolutionary Algorithms in Engineering and Computer Science Recent Advances in Genetic Algorithms Evolution Strategies, Evolutionary Programming (Wiley, Hoboken, 1999)

    MATH  Google Scholar 

  5. M. Mitchell, An introduction to genetic algorithms (complex adaptive systems). Bradford Book, Third Printing Edn. 55, 02146–1493 (1998)

    Google Scholar 

  6. R. Aunger, in Memes, ed. by A. Kuper and J. Kuper. The Social Science Encyclopedia, 3rd edn. (London, Routledge, 2004)

    Google Scholar 

  7. F. Heylighen, K. Chielens. Cultural evolution and memetics. Encycl. Complex. Syst. Sci.

    Google Scholar 

  8. D. Liu, K.C. Tan, C.K. Goh, W.K. Ho, A multiobjective memetic algorithm based on particle swarm optimization. IEEE Trans. Syst. Man Cybern. Part B Cybern. 37(1), 42–50 (2007)

    Article  Google Scholar 

  9. H. Ishibuchi, N. Tsukamoto, Y. Nojima, Diversity improvement by non-geometric binary crossover in evolutionary multiobjective optimization. IEEE Trans. Evol. Comput. 14(6), 985–998 (2010)

    Article  Google Scholar 

  10. F. Neri, S. Yang, Guest editorial: memetic computing in the presence of uncertainties. Memetic Comput. 2, 85–86 (2010)

    Article  Google Scholar 

  11. K. Morikawa, S. Ozawa, S. Abe, Tuning membership functions of kernel fuzzy classifiers by maximizing margins. Memetic Comput. J. 1(3), 221–228 (2009)

    Article  Google Scholar 

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Correspondence to V. Balakumar .

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Balakumar, V., Swarnalatha, C. (2015). Memetic Framework Application—Analysis of Corporate Customer Attitude in Telecom Sector. In: Suresh, L., Dash, S., Panigrahi, B. (eds) Artificial Intelligence and Evolutionary Algorithms in Engineering Systems. Advances in Intelligent Systems and Computing, vol 325. Springer, New Delhi. https://doi.org/10.1007/978-81-322-2135-7_22

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  • DOI: https://doi.org/10.1007/978-81-322-2135-7_22

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  • Publisher Name: Springer, New Delhi

  • Print ISBN: 978-81-322-2134-0

  • Online ISBN: 978-81-322-2135-7

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