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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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 |
work_keys_str_mv |
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1721350003316752384 |