Competence Sets Expansion Based on the Fuzzy Rough Neural Network

Junwen FENG

Abstract


Traditional competence sets analysis focuses on the expansion of the discrete competence sets, and focus on the uncertainty analysis. By means of uncertainty reasoning techniques and principles (probability reasoning, evidential reasoning, fuzzy reasoning, information reasoning, including degree reasoning, etc.), how to study competence expansion under uncertain circumstances, that is one of the issues of competence expansion theory. About competence expansion question under the indefinite situation, papers formerly mainly studied that the enterprise’s obtained competence or actual requisite competence is indefinite, did not solve that both are indefinite, precisely based on this goal, this article studies the enterprise competence expansion process under this kind of situation by using the fuzzy rough neural network method, solves fuzzy market demand and rough technology competence and so on uncertainty influence factors, helps decision-maker to expand enterprise technology competence to the needed technology competence of enterprise technology innovation question satisfaction solution.

Key words: Enterprise management decision; Fuzzy rough neural network; Competence sets expansion


Keywords


Enterprise management decision; Fuzzy rough neural network; Competence sets expansion

Full Text:

PDF

References


AN, Z. L. (2009). Modern Enterprise Management Innovation and Analysis. China Business, 2, 45-60.

FENG, J. W. (1999). Competence Set Analysis. Journal of Management Sciences in China, 2(2), 77-83.

FENG, J. W. (2000). New Field for Behavior and Decision Science Research Habitual Domain Analysis. Systems Engineering and Electronics, 22(3), 77-83.

FENG, J. W. (2001). Organization Habitual Domains Theory. Systems Engineering and Electronics, 23 (6), 40-43.

HUANG, J. J., Ong, C. S. & Tzeng, G. H. (2006). Optimal Fuzzy Multi-Criteria Expansion of Competence Sets Using Multi-Objectives Evolutionary Algorithms. Expert Systems with Applications, 30(4), 739-745.

YU, P. L., & CHEN, Y. C. (2010a). Blinds, Fuzziness and Habitual Domain Tools in Decision Making with Changeable Spaces. Human Systems Management, 29(4), 231-242.

LIN, C. M. (2006). Multiobjective Fuzzy Competence Set Expansion Problem by Multistate Decision-Based Hybrid Genetic Algorithms. Applied Mathematics and Computation, 181(10), 1402-1516.

LUO, B., & SHAO, P. J., etc. (2011). Customer Churn Research Based on Multiple Classifier Fusing Rough Sets-Neural Network-Artificial Bee Colony Algorithm. Chinese Journal of Management, (2), 265-272.

Shee Daniel Y. (2006). An Analytic Framework for Competence Set Expansion: Lessons Learned From an SME. Total Quality Management & Business Excellence, 17(8), 981-997.

WANG, H. T., FENG, J. W, & MIAO, C. L. (2008). The Research on Competence Set Expansion’S Management Decision Analysis Method. Engineering Sciences, 10(8), 51-55.

YU, P. L., & CHEN, Y. C. (2010). Dynamic Multiple Criteria Decision Making in Changeable Spaces: From Habitual Domains to Innovation Dynamics. Annals of Operations Research, 10(5), 1-20.

YU, P. L. (1991). Habitual Domains. Operations Research, 10(6), 869-876.

ZHOU, G. X., & WU, M. (2010). Fuzzy Neural Network Control Based on Improved Gray Prediction. Journal of System Simulation, 22(10), 2333-2336.




DOI: http://dx.doi.org/10.3968%2Fj.ibm.1923842820120502.1100

Refbacks

  • There are currently no refbacks.


Reminder

If you have already registered in Journal A and plan to submit article(s) to Journal B, please click the CATEGORIES, or JOURNALS A-Z on the right side of the "HOME".


We only use three mailboxes as follows to deal with issues about paper acceptance, payment and submission of electronic versions of our journals to databases: caooc@hotmail.com; ibm@cscanada.net; ibm@cscanada.org

Copyright © 2010 Canadian Research & Development Centre of Sciences and Cultures
Address: 730, 77e AV, Laval, Quebec, H7V 4A8, Canada

Telephone: 1-514-558 6138
Http://www.cscanada.net
Http://www.cscanada.org
E-mail:caooc@hotmail.com