Adaptive neuro-fuzzy approach to sodium chlorate cell modeling to predict cell pH for energy-efficient chlorate production

Author:

Sreekumar Sreepriya1,Kallingal Aparna1,Mundakkal Lakshmanan Vinila1

Affiliation:

1. Department of Chemical Engineering, National Institute of Technology, Calicut, India

Publisher

Informa UK Limited

Subject

General Chemical Engineering,General Chemistry

Reference49 articles.

1. The application of ANFIS prediction models for thermal error compensation on CNC machine tools

2. Hypochlorite Ion Decomposition:  Effects of Temperature, Ionic Strength, and Chloride Ion

3. Ajdari S. 2011. Modeling and simulation of a small scale chlorate electrolyzer. Master of Science Thesis in the Master Degree Program, Innovative and Sustainable Chemical engineering, Department of chemical and Biological Engineering, Division of chemical Reaction engineering, Chalmers University of Technology, Goteborg, Sweden.

4. Modeling and Simulation of an Adaptive Neuro-Fuzzy Inference System (ANFIS) for Mobile Learning

5. Buragohain M. 2008. Adaptive Network Based Fuzzy Inference System (ANFIS) as a tool for system identification with special emphasis on training data minimization. Doctoral Thesis Department of Electronics and Communication Engineering, Indian Institute of Technology Guwahati; p. 1–141.

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