Information Conservational YinYang Bipolar Quantum-Fuzzy Cognitive Maps-Mapping Business Data to Business Intelligence
Document Type
Contribution to Book
Publication Date
7-2016
Publication Title
Proceedings of 2016 IEEE International Conference on Fuzzy Systems (FUZZ-IEEE)
DOI
10.1109/FUZZ-IEEE.2016.7737977
ISBN
978-1-5090-0626-7
Abstract
Based on YinYang bipolar fuzzy sets and bipolar quantum linear algebra (BQLA), information conservational bi-polar quantum-fuzzy cognitive maps (BQFCMs) are proposed. It is shown that a bipolar relation can be normalized to a bipolar quantum-fuzzy logic gate (BQFLG) matrix – the equivalent of a BQFCM for equilibrium-based business intelligence. Computability and applicability of BQFCMs are illustrated with case studies in portfolio management, supply-production optimization and import-export rebalancing. This work is expected to add bipolar quantum computational intelligence (QCI) as an integrative dimension to computational intelligence. Its philosophical and mathematical uniqueness is discussed. An unsettled debate is outlined.
Recommended Citation
Zhang, Wen-Ran.
2016.
"Information Conservational YinYang Bipolar Quantum-Fuzzy Cognitive Maps-Mapping Business Data to Business Intelligence."
Proceedings of 2016 IEEE International Conference on Fuzzy Systems (FUZZ-IEEE): 2279-2286: IEEE.
doi: 10.1109/FUZZ-IEEE.2016.7737977 isbn: 978-1-5090-0626-7
https://digitalcommons.georgiasouthern.edu/compsci-facpubs/45
