Evaluation of the Ability of ANFIS and SVMR Models to Predict the Corrosion Inhibition of Cerium Conversion Coating

This work investigates the inhibition effect of cerium conversion coating on various aluminium alloys. Two different computational methods, ANFIS (adaptive-network-based fuzzy inference system) and SVMR (support vector machine regression) were developed to predict the inhibitory power of coated Al-a...

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Veröffentlicht in:	Protection of metals and physical chemistry of surfaces 2022-08, Vol.58 (4), p.872-882
Hauptverfasser:	Majdi, M. R., Ghobadi, M., Danaee, I., Zarezadeh, A., Saebnoori, E., Chocholatý, O., Bahrami Panah, N.
Format:	Artikel
Sprache:	eng
Schlagworte:	Alloying elements Aluminum base alloys Cerium oxides Characterization and Evaluation of Materials Chemistry and Materials Science Clustering Coating effects Computer networks Corrosion Corrosion and Coatings Corrosion effects Corrosion rate Industrial Chemistry/Chemical Engineering Inorganic Chemistry Investigation Methods for Physicochemical Systems Manganese Materials Science Mathematical models Metallic Materials Parameters Prediction models Protective coatings Root-mean-square errors Sensitivity analysis Statistical analysis Support vector machines Tribology
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