Shahsavar, Mohammad M., Akrami, Mehran, Gheibi, Mohammad, Kavianpour, Babak, Fathollahi-Fard, Amir M. and Behzadian, Kourosh ORCID: https://orcid.org/0000-0002-1459-8408 (2021) Constructing a smart framework for supplying the biogas energy in green buildings using an integration of response surface methodology, artificial intelligence and petri net modelling. Energy Conversion and Management, 248. p. 114794. ISSN 0196-8904

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Abstract

Nowadays, energy crisis is considered an essential active issue for future urbanization in megacities. While the
rate of population growth increases, the volume of municipal solid waste production increases significantly. This
highlights the need of Sustainable Development Goals (SDGs) for both developed and developing countries. This
paper constructs a novel smart framework for supplying biogas energy. Our study is applicable for fields of waste
management and energy supply in green buildings. The proposed framework integrates the Response Surface
Methodology (RSM), Artificial Intelligence (AI), and Petri net modeling. In this regard, the AI techniques
including the Random Tree (RT), Random Forest (RF), Artificial Neural Network (ANN) and, Adaptive-Networkbased
Fuzzy Inference System (ANFIS) are employed. In addition, for creating the optimum condition, a dynamic
control system using the Petri Net modeling is applied. Among all machine learning methods, ANFIS with 0.99
correlation coefficient had the best accuracy for Accumulated Biogas Production (ABP) based on effective factors.
Finally, the main findings of this paper are to introduce a novel framework for addressing different scientific
issues such as supplying the clean energy in green buildings, the development of a smart and sustainable biogas
production control system, integration of solid waste management with the SDGs in green buildings.

Item Type:	Article
Identifier:	10.1016/j.enconman.2021.114794
Keywords:	Biogas, Solid waste management, Response surface methodology, Artificial intelligence, Petri net modelling
Subjects:	Construction and engineering > Civil and environmental engineering
Related URLs:	Publisher
Depositing User:	Kourosh Behzadian
Date Deposited:	05 Oct 2021 21:54
Last Modified:	04 Nov 2024 11:18
URI:	https://repository.uwl.ac.uk/id/eprint/8304

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