Optimization of adaptive neuro–fuzzy inference system (ANFIS) parameters via Box-Behnken experimental design approach: The prediction of chromium adsorption-Reference-Cited by-同舟云学术

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Optimization of adaptive neuro–fuzzy inference system (ANFIS) parameters via Box-Behnken experimental design approach: The prediction of chromium adsorption

Published:2024-02 Issue:3 Volume:10 Page:e25813
ISSN:2405-8440
Container-title:Heliyon
language:en
Short-container-title:Heliyon

Author:

Duranoğlu Dilek^ORCID,Sinan Altın Esat^ORCID,Küçük İlknur^ORCID

Publisher

Elsevier BV

Reference20 articles.

1. An investigation of membership functions on performance of ANFIS for solving classification problems;Talpur;IOP Conf. Ser. Mater. Sci. Eng.,2017

2. ANFIS: adaptive-network-based fuzzy inference system;Jang;IEEE Transactions on Systems Man & Cybernetics,1993

3. Neural Network: A Comprehensive Foundation;Haykin,1994

4. Neuro-Fuzzy and Soft Computing;Jang,1997

5. Twelve considerations in choosing between Gaussian and trapezoidal membership functions in interval type-2 fuzzy logic controllers;Wu,2012

Cited by 3 articles. 订阅此论文施引文献订阅此论文施引文献，注册后可以免费订阅5篇论文的施引文献，订阅后可以查看论文全部施引文献

1. Agricultural low-cost waste adsorption of methylene blue and modelling linear isotherm method versus nonlinear prediction;Clean Technologies and Environmental Policy;2024-07-29

2. A Hybrid Intelligent Noise Pollution Prediction Model Based on ANFIS and Nature-Inspired Algorithms;American Journal of Mathematical and Computer Modelling;2024-05-17

3. Application of the Surface Regression Technique for Enhancing the Input Factors and Responses for Processing Coconut Oil under Vertical Compression;Foods;2024-04-30

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