From Equilibrium-Based Business Intelligence to Information Conservational Quantum-Fuzzy Cryptography—A Cellular Transformation of Bipolar Fuzzy Sets to Quantum Intelligence Machinery
Wen-Ran Zhang · IEEE Transactions on Fuzzy Systems · 2017
A cellular transformation of bipolar fuzzy sets to quantum intelligence (QI) machinery is presented based on an axiomatic formulation of equilibrium-based business intelligence (EBBI) and information conservational quantum-fuzzy cryptography (ICQFC). It is proven that any active bipolar cognitive map can be normalized to a bipolar quantum-fuzzy cognitive map-the logical equivalent of an information conservational bipolar quantum-fuzzy logic gate for equilibrium-based quantum cellular rebalancing. Such rebalancing leads to EBBI and ICQFC-an unexpected combination with unexpected synergy. Applicability of one EBBI algorithm and two ICQFC algorithms are illustrated. Information theoretic security and scalability of ICQFC are proved as a computational intelligence testbed for postquantum cryptography. It is argued that, while the illogical aspect of quantum mechanics prevents quantum computing from lending itself as an analytical paradigm, EBBI and ICQFC constitute a cellular transformation of bipolar fuzzy sets to high precision QI machinery-an equilibrium-based analytical paradigm for ubiquitous quantum modeling and quantum-digital compatible computing. A QI architecture is drafted. A QI transfer protocol is illustrated with ICQFC for EBBI. QI is, thus, distinguished by its ubiquitous, analytical, transferable, and quantum-digital compatible properties. It is asserted that QI as the most generic genre of intelligence underpins artificial and biological intelligence with mathematical, philosophical, and scientific distinctions. It is expected that through QI the research field of fuzzy sets and systems is destined to advance to the forefront of modern science including but not limited to brain science and quantum information science.