Adaptive neuro-fuzzy inference system
Publish place: 1th conference on the opportunities and challenges of artificial intelligence and new technologies in industry and mining
Publish Year: 1403
نوع سند: مقاله کنفرانسی
زبان: English
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شناسه ملی سند علمی:
AITIM01_046
تاریخ نمایه سازی: 14 مرداد 1403
Abstract:
Modify network-based fuzzy inference (ANFIS) is a combination of two soft-computing methods of ANN and fuzzy logic (Jang ۱۹۹۳). Fuzzy logic has the ability to change the qualitative aspects of human knowledge and insights into the process of precise quantitative analysis. However, it does not have a defined method that can be used as a guide in the process of transformation and human thought into rule base fuzzy inference system (FIS), and it also takes quite a long time to adjust the membership functions (MFs) (Jang ۱۹۹۳). Unlike ANN, it has a higher capability in the learning process to adapt to its environment. Therefore, the ANN can be used to automatically adjust the MFs and reduce the rate of errors in the determination of rules in fuzzy logic. This section will describe in details of the architecture of ANFIS, FISs, and network flexibility, and hybrid learning algorithm.
Keywords:
Authors
Samaneh Soradi-Zeid
Faculty of Industry and Mining, University of Sistan and Baluchestan, Zahedan, Iran
Shahin Shahnavazi
Master of Software, University of Sistan and Baluchestan, Zahedan, Iran