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Application of ANFIS Model for Thailand’s Electric Vehicle Consumption

Narongkorn Uthathip1,*, Pornrapeepat Bhasaputra1, Woraratana Pattaraprakorn2

1 Electrical and Computer Engineering, Thammasat University, Pathum Thani, Thailand
2 Chemical Engineering, Thammasat University, Pathum Thani, Thailand

* Corresponding Author: Narongkorn Uthathip. Email: email

(This article belongs to the Special Issue: Advances in Computational Intelligence and its Applications)

Computer Systems Science and Engineering 2022, 42(1), 69-86. https://doi.org/10.32604/csse.2022.020120

Abstract

Generally, road transport is a major energy-consuming sector. Fuel consumption of each vehicle is an important factor that affects the overall energy consumption, driving behavior and vehicle characteristic are the main factors affecting the change of vehicle fuel consumption. It is difficult to analyze the influence of fuel consumption with multiple and complex factors. The Adaptive Neuro-Fuzzy Inference System (ANFIS) approach was employed to develop a vehicle fuel consumption model based on multivariate input. The ANFIS network was constructed by various experiments based on the ANFIS Parameter setting. The performance of the ANFIS network was validated using Root Mean Square Error (RMSE) and Mean Average Error (MAE) which related to the setting of ANFIS parameters. The experimental results indicated that the training data sample, number, and type of membership functions are the most important factor affecting the performance of the ANFIS network. However, the number of epochs does not necessarily significantly improve the system performance, too many the number of epochs setting may not provide the best results and lead to excessive responding time. The results also demonstrate that three factors, consisted of the engine size, driving speed, and the number of passengers, are important factors that influence the change of vehicle fuel consumption. The selected ANFIS models with minimum error can be properly and efficiently used to predict vehicle fuel consumption for Thailand’s road transport sector.

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APA Style
Uthathip, N., Bhasaputra, P., Pattaraprakorn, W. (2022). Application of ANFIS model for thailand’s electric vehicle consumption. Computer Systems Science and Engineering, 42(1), 69-86. https://doi.org/10.32604/csse.2022.020120
Vancouver Style
Uthathip N, Bhasaputra P, Pattaraprakorn W. Application of ANFIS model for thailand’s electric vehicle consumption. Comput Syst Sci Eng. 2022;42(1):69-86 https://doi.org/10.32604/csse.2022.020120
IEEE Style
N. Uthathip, P. Bhasaputra, and W. Pattaraprakorn "Application of ANFIS Model for Thailand’s Electric Vehicle Consumption," Comput. Syst. Sci. Eng., vol. 42, no. 1, pp. 69-86. 2022. https://doi.org/10.32604/csse.2022.020120

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cc This work is licensed under a Creative Commons Attribution 4.0 International License , which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
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