The Estimation of the Relationships between Water-Natural Gas Usage and Discharge-Emission Permission by Using Binary Logistic Model for the Industrial Establishments

This study presents a hybrid meta-modeling algorithm for optimum carbon dioxide (CO2) emission estimation. It is composed of artificial neural network (ANN), fuzzy linear regression (FLR), and conventional regression (CR). Different FLR models are considered to cover the latest algorithms and viewpoints. ANN with different training algorithms and transfer functions is also applied to data sets. The proposed hybrid algorithms uses analysis of variance (ANOVA), and mean absolute percentage error (MAPE) to select between ANN, FLR or conventional regression for future CO2 emission estimation. The intelligent algorithm of this study is then applied to estimate CO2 emission in seven countries including India, Canada, Brazil, France, Japan, United Kingdom and United States. Different models are selected as preferred model for annual CO2 emission estimation in these countries. The preferred model for India, Brazil, United Kingdom and United States is selected as FLR whereas the preferred model for CO2 emission estimation in Japan, Canada and France is ANN. This shows how adopting the proposed hybrid algorithm could help in selecting the preferred model between FLR, ANN and CR in order to cover possible noise, complexity and ambiguity. This is the first study that utilizes a hybrid algorithm based on ANN, FLR and CR for accurate and optimum long term CO2 emission estimation.

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The Estimation of the Relationships between Water-Natural Gas Usage and Discharge-Emission Permission by Using Binary Logistic Model for the Industrial Establishments

Abstract: binary logistic model, discharge, emission, industrial establishments, sustainable development,

Cited by 4 publications

References 6 publications

Does environmental performance affect financial performance? Evidence from Chinese listed companies in heavily polluting industries

Does environmental performance affect financial performance? Evidence from Chinese listed companies in heavily polluting industries

The effect of expected financial performance on corporate environmental responsibility disclosure: evidence from China

A hybrid intelligent algorithm for optimum forecasting of CO₂ emission in complex environments: the cases of Brazil, Canada, France, Japan, India, UK and US

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The Estimation of the Relationships between Water-Natural Gas Usage and Discharge-Emission Permission by Using Binary Logistic Model for the Industrial Establishments

Abstract: binary logistic model, discharge, emission, industrial establishments, sustainable development,

Cited by 4 publications

References 6 publications

Does environmental performance affect financial performance? Evidence from Chinese listed companies in heavily polluting industries

Does environmental performance affect financial performance? Evidence from Chinese listed companies in heavily polluting industries

The effect of expected financial performance on corporate environmental responsibility disclosure: evidence from China

A hybrid intelligent algorithm for optimum forecasting of CO2 emission in complex environments: the cases of Brazil, Canada, France, Japan, India, UK and US

Contact Info

Product

Resources

About

A hybrid intelligent algorithm for optimum forecasting of CO₂ emission in complex environments: the cases of Brazil, Canada, France, Japan, India, UK and US