Journal of Engineering and Applied Sciences

Year: 2018
Volume: 13
Issue: 6 SI
Page No. 5196 - 5202

Estimation of Carbon Dioxide Emission Using Adaptive Neuro-Fuzzy Inference System

Authors : Nur Rachman Dzakiyullah, Chairul Saleh, Fadmi Rina and Abdul Rahman Fitra

Abstract: Effect of CO2 emission was highly risked toward the climate change which arising from a natural process and human activities. This study presents a model of Adaptive Neuro-Fuzzy Inference System (ANFIS) for estimating the CO2 emission. This model is built based on input variables from the using of energy in producing the rubbing alcohol company which includes electrical energy and coal. The training of ANFIS analyzed by using hybrid LSE recursive then the performance of ANFIS analyzed by using RMSE. The experiment is performed by optimizing the parameter value of ANFIS. The proposed models are examined using a real word data as a dataset that was collected from rubbing alcohol company in Indonesia. The data was divided into 60% training data and 40% testing data. The experimental result shows that ANFIS provides small RMSE 0.0000259. It indicates that the ANFIS Model as a promising tool to ease company in estimating CO2 emission and even can contribute to practice as a tool for decision making to control CO2 emission.

How to cite this article:

Nur Rachman Dzakiyullah, Chairul Saleh, Fadmi Rina and Abdul Rahman Fitra, 2018. Estimation of Carbon Dioxide Emission Using Adaptive Neuro-Fuzzy Inference System. Journal of Engineering and Applied Sciences, 13: 5196-5202.

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