Fuzzy neural logic network and its learning algorithms

• Main Authors: NAH, Fiona Fui-hoon, NAH Fiona
• Format: text
• Language: English
• Published: Institutional Knowledge at Singapore Management University 1991
• Subjects: Databases and Information Systems; OS and Networks
• Online Access: https://ink.library.smu.edu.sg/sis_research/10064; https://ink.library.smu.edu.sg/context/sis_research/article/11064/viewcontent/Fuzzy_neural_logic_network_and_its_learning_algorithms_pv.pdf
• Institution: Singapore Management University

The paper introduces the basic features of fuzzy neural logic network. Each fuzzy neural logic network model is trained from a set of knowledge in the form of examples using one of the three learning algorithms introduced. These three learning algorithms are the delta rule controlled learning algorithm and two mathematical construction algorithms, namely, the local learning method and the global learning method. Once the fuzzy neural logic network model is constructed, it is ready to accept any unknown input from the user. With a low percentage of mismatched features, output solution can be obtained.