tailieunhanh - Summary of Computer doctoral thesis: Some extensions of the complex fuzzy inference system for decision support problem

Research objectives of the thesis: Research the theories of complex fuzzy sets, complex fuzzy logic and measures based on complex fuzzy sets; research and development of fuzzy inference system based on complex fuzzy sets; research applied techniques to reduce rules, optimize fuzzy rules in complex fuzzy inference system; research on how to represent rules based on fuzzy knowledge graphs to reduce inference computation time for the test set and deal with the cases where the new dataset is not present in the training data set. | MINISTRY OF EDUCATION VIETNAM ACADEMY AND TRAINING OF SCIENCE AND TECHNOLOGY GRADUATE UNIVERSITY OF SCIENCE AND TECHNOLOGY - LUONG THI HONG LAN SOME EXTENSIONS OF THE COMPLEX FUZZY INFERENCE SYSTEM FOR DECISION SUPPORT PROBLEM Major Computer science Code 9 48 01 01 SUMMARY OF COMPUTER DOCTORAL THESIS Ha Noi - 2021 The doctoral thesis was completed at Graduate University of Science and Technology Vietnam Academy of Science and Technology Supervisor 1 Assoc. Prof. Dr. Le Hoang Son Supervisor 2 Assoc. Prof. Dr. Nguyen Long Giang Reviewer 1 Reviewer 2 Reviewer 3 This doctoral thesis will be defended at the Board of Examiners of Graduate University of Science and Technology Vienam Academy of Science and Technology on hour . date . month . 2021 This doctoral thesis can be explored at - Library of the Graduate University of Science and Technology - National Library of Vietnam 1 PREFACE Fuzzy set FS 1 proposed by Zadeh in 1965 is considered as an effective tool to solve the problems with uncertain properties. Various extensions and operations of FS have been presented in recent years 2-6 . One of the most important techniques in FS is Fuzzy Inference System FIS which is widely applied in many decision-making and classification prediction problems such as green supplier selection personnel selection company strategy etc. In these applications FIS was used to generate a set of fuzzy rules to detect predict or classify objects such as lung cancer detection detection of diabetes mellitus heart disease prediction evaluation of green supply chain management performance penetration index estimation in rock mass 7-13 . An extended version of FIS embedded with neural network and gradient-based learning is the Adaptive Neuro Fuzzy Inference System ANFIS 14 which also demonstrated good performance in coronary artery disease prognosis estimating thermal conductivity enhancement of metal and metal oxide flood prediction etc. 15- 21 . Recently with the boost up of various .