A Neural Network Model for Decision-Making with Application in Sewage Sludge Management

Wastewater treatment (WWT) is a foremost challenge for maintaining the health of ecosystems and human beings; the waste products of the water-treatment process can be a problem or an opportunity. The sewage sludge (SS) produced during sewage treatment can be considered a waste to be disposed of in a...

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Main Authors: Francesco Facchini, Luigi Ranieri, Micaela Vitti
Format: Article
Language:English
Published: MDPI AG 2021-06-01
Series:Applied Sciences
Subjects:
Online Access:https://www.mdpi.com/2076-3417/11/12/5434
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spelling doaj-ac33fafc48ac442d9f4263caa8d8a37c2021-06-30T23:57:05ZengMDPI AGApplied Sciences2076-34172021-06-01115434543410.3390/app11125434A Neural Network Model for Decision-Making with Application in Sewage Sludge ManagementFrancesco Facchini0Luigi Ranieri1Micaela Vitti2Department of Mechanics, Mathematics, and Management, Polytechnic University of Bari, 70126 Bari, ItalyDepartment of Innovation Engineering, University of Salento, 73047 Lecce, ItalyDepartment of Mechanics, Mathematics, and Management, Polytechnic University of Bari, 70126 Bari, ItalyWastewater treatment (WWT) is a foremost challenge for maintaining the health of ecosystems and human beings; the waste products of the water-treatment process can be a problem or an opportunity. The sewage sludge (SS) produced during sewage treatment can be considered a waste to be disposed of in a landfill or as a source for obtaining raw material to be used as a fertilizer, building material, or alternative fuel source suitable for co-incineration in a high-temperature furnace. To this concern, this study’s purpose consisted of developing a decision model, supported by an Artificial Neural Network (ANN model), allowing us to identify the most effective sludge management strategy in economic terms. Consistent with the aim of the work, the suitable SS treatment was identified, selecting for each phase of the SS treatment, an alternative available on the market ensuring energy and/or matter recovery, in line with the circular water value chain. Results show that the ANN model identifies the suitable SS treatments on multiple factors, thus supporting the decision-making and identifying the solution as per user requirements.https://www.mdpi.com/2076-3417/11/12/5434waste-treatment processsewage-sludge managementcircular economydecision support systemdecision problemartificial neural network
collection DOAJ
language English
format Article
sources DOAJ
author Francesco Facchini
Luigi Ranieri
Micaela Vitti
spellingShingle Francesco Facchini
Luigi Ranieri
Micaela Vitti
A Neural Network Model for Decision-Making with Application in Sewage Sludge Management
Applied Sciences
waste-treatment process
sewage-sludge management
circular economy
decision support system
decision problem
artificial neural network
author_facet Francesco Facchini
Luigi Ranieri
Micaela Vitti
author_sort Francesco Facchini
title A Neural Network Model for Decision-Making with Application in Sewage Sludge Management
title_short A Neural Network Model for Decision-Making with Application in Sewage Sludge Management
title_full A Neural Network Model for Decision-Making with Application in Sewage Sludge Management
title_fullStr A Neural Network Model for Decision-Making with Application in Sewage Sludge Management
title_full_unstemmed A Neural Network Model for Decision-Making with Application in Sewage Sludge Management
title_sort neural network model for decision-making with application in sewage sludge management
publisher MDPI AG
series Applied Sciences
issn 2076-3417
publishDate 2021-06-01
description Wastewater treatment (WWT) is a foremost challenge for maintaining the health of ecosystems and human beings; the waste products of the water-treatment process can be a problem or an opportunity. The sewage sludge (SS) produced during sewage treatment can be considered a waste to be disposed of in a landfill or as a source for obtaining raw material to be used as a fertilizer, building material, or alternative fuel source suitable for co-incineration in a high-temperature furnace. To this concern, this study’s purpose consisted of developing a decision model, supported by an Artificial Neural Network (ANN model), allowing us to identify the most effective sludge management strategy in economic terms. Consistent with the aim of the work, the suitable SS treatment was identified, selecting for each phase of the SS treatment, an alternative available on the market ensuring energy and/or matter recovery, in line with the circular water value chain. Results show that the ANN model identifies the suitable SS treatments on multiple factors, thus supporting the decision-making and identifying the solution as per user requirements.
topic waste-treatment process
sewage-sludge management
circular economy
decision support system
decision problem
artificial neural network
url https://www.mdpi.com/2076-3417/11/12/5434
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