Indicators and a Neuro-Fuzzy Based Model for the Evaluation of Water Supply Sustainability

Abstract In the field of water management, the evaluation of sustainability has no universal methodological approach nor any consensus regarding the definitions of sustainability or sustainable development. There is an essential need therefore for a precise definition of sustainability in different...
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Autor*in:	Halkijevic, Ivan [verfasserIn] Vukovic, Zivko [verfasserIn] Vouk, Drazen [verfasserIn]

Format:	E-Artikel
Sprache:	Englisch

Erschienen:	2017

Schlagwörter:	Water supply system sustainability Sustainability quantification Sustainability indicators Neuro-fuzzy evaluation of sustainability

Übergeordnetes Werk:	Enthalten in: Water resources management - Dordrecht [u.a.] : Springer Science + Business Media B.V, 1987, 31(2017), 12 vom: 11. Mai, Seite 3683-3698
Übergeordnetes Werk:	volume:31 ; year:2017 ; number:12 ; day:11 ; month:05 ; pages:3683-3698

Links:	Volltext

DOI / URN:	10.1007/s11269-017-1695-5

Katalog-ID:	SPR018393063

Internformat


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520			\|a Abstract In the field of water management, the evaluation of sustainability has no universal methodological approach nor any consensus regarding the definitions of sustainability or sustainable development. There is an essential need therefore for a precise definition of sustainability in different water management fields. This paper deals with the sustainability of one part of urban water management, namely a water supply. A precise definition of a sustainable water supply system is given, together with a methodological framework that quantifies the degree of water supply sustainability. The proposed framework relies on the proposed quasi-strong sustainability concept, its components (dimensions), their particular relationships and corresponding indicators representing individual processes in the water supply system and utility. The processing of indicators is performed through a joint fuzzy logic/neural network (ANFIS) model. In order to evaluate each sustainability component, separate ANFIS models were created whose results were aggregated into a single result (sustainability index). According to the presented framework, sustainability is evaluated for 17 public water supply systems/utilities in Croatia.
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allfields	10.1007/s11269-017-1695-5 doi (DE-627)SPR018393063 (SPR)s11269-017-1695-5-e DE-627 ger DE-627 rakwb eng 550 630 ASE 43.33 bkl Halkijevic, Ivan verfasserin aut Indicators and a Neuro-Fuzzy Based Model for the Evaluation of Water Supply Sustainability 2017 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier Abstract In the field of water management, the evaluation of sustainability has no universal methodological approach nor any consensus regarding the definitions of sustainability or sustainable development. There is an essential need therefore for a precise definition of sustainability in different water management fields. This paper deals with the sustainability of one part of urban water management, namely a water supply. A precise definition of a sustainable water supply system is given, together with a methodological framework that quantifies the degree of water supply sustainability. The proposed framework relies on the proposed quasi-strong sustainability concept, its components (dimensions), their particular relationships and corresponding indicators representing individual processes in the water supply system and utility. The processing of indicators is performed through a joint fuzzy logic/neural network (ANFIS) model. In order to evaluate each sustainability component, separate ANFIS models were created whose results were aggregated into a single result (sustainability index). According to the presented framework, sustainability is evaluated for 17 public water supply systems/utilities in Croatia. Water supply system sustainability (dpeaa)DE-He213 Sustainability quantification (dpeaa)DE-He213 Sustainability indicators (dpeaa)DE-He213 Neuro-fuzzy evaluation of sustainability (dpeaa)DE-He213 Vukovic, Zivko verfasserin aut Vouk, Drazen verfasserin aut Enthalten in Water resources management Dordrecht [u.a.] : Springer Science + Business Media B.V, 1987 31(2017), 12 vom: 11. Mai, Seite 3683-3698 (DE-627)315299924 (DE-600)2016360-5 1573-1650 nnns volume:31 year:2017 number:12 day:11 month:05 pages:3683-3698 https://dx.doi.org/10.1007/s11269-017-1695-5 lizenzpflichtig Volltext GBV_USEFLAG_A SYSFLAG_A GBV_SPRINGER SSG-OPC-GGO SSG-OPC-ASE GBV_ILN_11 GBV_ILN_20 GBV_ILN_22 GBV_ILN_23 GBV_ILN_24 GBV_ILN_31 GBV_ILN_32 GBV_ILN_39 GBV_ILN_40 GBV_ILN_60 GBV_ILN_62 GBV_ILN_63 GBV_ILN_69 GBV_ILN_70 GBV_ILN_73 GBV_ILN_74 GBV_ILN_90 GBV_ILN_95 GBV_ILN_100 GBV_ILN_105 GBV_ILN_110 GBV_ILN_120 GBV_ILN_138 GBV_ILN_150 GBV_ILN_151 GBV_ILN_152 GBV_ILN_161 GBV_ILN_170 GBV_ILN_171 GBV_ILN_187 GBV_ILN_213 GBV_ILN_224 GBV_ILN_230 GBV_ILN_250 GBV_ILN_281 GBV_ILN_285 GBV_ILN_293 GBV_ILN_370 GBV_ILN_602 GBV_ILN_636 GBV_ILN_702 GBV_ILN_2001 GBV_ILN_2003 GBV_ILN_2004 GBV_ILN_2005 GBV_ILN_2006 GBV_ILN_2007 GBV_ILN_2009 GBV_ILN_2010 GBV_ILN_2011 GBV_ILN_2014 GBV_ILN_2015 GBV_ILN_2020 GBV_ILN_2021 GBV_ILN_2025 GBV_ILN_2026 GBV_ILN_2027 GBV_ILN_2031 GBV_ILN_2034 GBV_ILN_2037 GBV_ILN_2038 GBV_ILN_2039 GBV_ILN_2044 GBV_ILN_2048 GBV_ILN_2049 GBV_ILN_2050 GBV_ILN_2055 GBV_ILN_2057 GBV_ILN_2059 GBV_ILN_2061 GBV_ILN_2064 GBV_ILN_2065 GBV_ILN_2068 GBV_ILN_2070 GBV_ILN_2086 GBV_ILN_2088 GBV_ILN_2093 GBV_ILN_2106 GBV_ILN_2107 GBV_ILN_2108 GBV_ILN_2110 GBV_ILN_2111 GBV_ILN_2112 GBV_ILN_2113 GBV_ILN_2116 GBV_ILN_2118 GBV_ILN_2119 GBV_ILN_2122 GBV_ILN_2129 GBV_ILN_2143 GBV_ILN_2144 GBV_ILN_2147 GBV_ILN_2148 GBV_ILN_2152 GBV_ILN_2153 GBV_ILN_2188 GBV_ILN_2190 GBV_ILN_2232 GBV_ILN_2336 GBV_ILN_2446 GBV_ILN_2470 GBV_ILN_2472 GBV_ILN_2507 GBV_ILN_2522 GBV_ILN_2548 GBV_ILN_4035 GBV_ILN_4037 GBV_ILN_4046 GBV_ILN_4112 GBV_ILN_4125 GBV_ILN_4126 GBV_ILN_4242 GBV_ILN_4246 GBV_ILN_4249 GBV_ILN_4251 GBV_ILN_4305 GBV_ILN_4306 GBV_ILN_4307 GBV_ILN_4313 GBV_ILN_4322 GBV_ILN_4323 GBV_ILN_4324 GBV_ILN_4325 GBV_ILN_4326 GBV_ILN_4328 GBV_ILN_4333 GBV_ILN_4334 GBV_ILN_4335 GBV_ILN_4336 GBV_ILN_4338 GBV_ILN_4393 GBV_ILN_4700 43.33 ASE AR 31 2017 12 11 05 3683-3698
spelling	10.1007/s11269-017-1695-5 doi (DE-627)SPR018393063 (SPR)s11269-017-1695-5-e DE-627 ger DE-627 rakwb eng 550 630 ASE 43.33 bkl Halkijevic, Ivan verfasserin aut Indicators and a Neuro-Fuzzy Based Model for the Evaluation of Water Supply Sustainability 2017 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier Abstract In the field of water management, the evaluation of sustainability has no universal methodological approach nor any consensus regarding the definitions of sustainability or sustainable development. There is an essential need therefore for a precise definition of sustainability in different water management fields. This paper deals with the sustainability of one part of urban water management, namely a water supply. A precise definition of a sustainable water supply system is given, together with a methodological framework that quantifies the degree of water supply sustainability. The proposed framework relies on the proposed quasi-strong sustainability concept, its components (dimensions), their particular relationships and corresponding indicators representing individual processes in the water supply system and utility. The processing of indicators is performed through a joint fuzzy logic/neural network (ANFIS) model. In order to evaluate each sustainability component, separate ANFIS models were created whose results were aggregated into a single result (sustainability index). According to the presented framework, sustainability is evaluated for 17 public water supply systems/utilities in Croatia. Water supply system sustainability (dpeaa)DE-He213 Sustainability quantification (dpeaa)DE-He213 Sustainability indicators (dpeaa)DE-He213 Neuro-fuzzy evaluation of sustainability (dpeaa)DE-He213 Vukovic, Zivko verfasserin aut Vouk, Drazen verfasserin aut Enthalten in Water resources management Dordrecht [u.a.] : Springer Science + Business Media B.V, 1987 31(2017), 12 vom: 11. Mai, Seite 3683-3698 (DE-627)315299924 (DE-600)2016360-5 1573-1650 nnns volume:31 year:2017 number:12 day:11 month:05 pages:3683-3698 https://dx.doi.org/10.1007/s11269-017-1695-5 lizenzpflichtig Volltext GBV_USEFLAG_A SYSFLAG_A GBV_SPRINGER SSG-OPC-GGO SSG-OPC-ASE GBV_ILN_11 GBV_ILN_20 GBV_ILN_22 GBV_ILN_23 GBV_ILN_24 GBV_ILN_31 GBV_ILN_32 GBV_ILN_39 GBV_ILN_40 GBV_ILN_60 GBV_ILN_62 GBV_ILN_63 GBV_ILN_69 GBV_ILN_70 GBV_ILN_73 GBV_ILN_74 GBV_ILN_90 GBV_ILN_95 GBV_ILN_100 GBV_ILN_105 GBV_ILN_110 GBV_ILN_120 GBV_ILN_138 GBV_ILN_150 GBV_ILN_151 GBV_ILN_152 GBV_ILN_161 GBV_ILN_170 GBV_ILN_171 GBV_ILN_187 GBV_ILN_213 GBV_ILN_224 GBV_ILN_230 GBV_ILN_250 GBV_ILN_281 GBV_ILN_285 GBV_ILN_293 GBV_ILN_370 GBV_ILN_602 GBV_ILN_636 GBV_ILN_702 GBV_ILN_2001 GBV_ILN_2003 GBV_ILN_2004 GBV_ILN_2005 GBV_ILN_2006 GBV_ILN_2007 GBV_ILN_2009 GBV_ILN_2010 GBV_ILN_2011 GBV_ILN_2014 GBV_ILN_2015 GBV_ILN_2020 GBV_ILN_2021 GBV_ILN_2025 GBV_ILN_2026 GBV_ILN_2027 GBV_ILN_2031 GBV_ILN_2034 GBV_ILN_2037 GBV_ILN_2038 GBV_ILN_2039 GBV_ILN_2044 GBV_ILN_2048 GBV_ILN_2049 GBV_ILN_2050 GBV_ILN_2055 GBV_ILN_2057 GBV_ILN_2059 GBV_ILN_2061 GBV_ILN_2064 GBV_ILN_2065 GBV_ILN_2068 GBV_ILN_2070 GBV_ILN_2086 GBV_ILN_2088 GBV_ILN_2093 GBV_ILN_2106 GBV_ILN_2107 GBV_ILN_2108 GBV_ILN_2110 GBV_ILN_2111 GBV_ILN_2112 GBV_ILN_2113 GBV_ILN_2116 GBV_ILN_2118 GBV_ILN_2119 GBV_ILN_2122 GBV_ILN_2129 GBV_ILN_2143 GBV_ILN_2144 GBV_ILN_2147 GBV_ILN_2148 GBV_ILN_2152 GBV_ILN_2153 GBV_ILN_2188 GBV_ILN_2190 GBV_ILN_2232 GBV_ILN_2336 GBV_ILN_2446 GBV_ILN_2470 GBV_ILN_2472 GBV_ILN_2507 GBV_ILN_2522 GBV_ILN_2548 GBV_ILN_4035 GBV_ILN_4037 GBV_ILN_4046 GBV_ILN_4112 GBV_ILN_4125 GBV_ILN_4126 GBV_ILN_4242 GBV_ILN_4246 GBV_ILN_4249 GBV_ILN_4251 GBV_ILN_4305 GBV_ILN_4306 GBV_ILN_4307 GBV_ILN_4313 GBV_ILN_4322 GBV_ILN_4323 GBV_ILN_4324 GBV_ILN_4325 GBV_ILN_4326 GBV_ILN_4328 GBV_ILN_4333 GBV_ILN_4334 GBV_ILN_4335 GBV_ILN_4336 GBV_ILN_4338 GBV_ILN_4393 GBV_ILN_4700 43.33 ASE AR 31 2017 12 11 05 3683-3698
allfields_unstemmed	10.1007/s11269-017-1695-5 doi (DE-627)SPR018393063 (SPR)s11269-017-1695-5-e DE-627 ger DE-627 rakwb eng 550 630 ASE 43.33 bkl Halkijevic, Ivan verfasserin aut Indicators and a Neuro-Fuzzy Based Model for the Evaluation of Water Supply Sustainability 2017 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier Abstract In the field of water management, the evaluation of sustainability has no universal methodological approach nor any consensus regarding the definitions of sustainability or sustainable development. There is an essential need therefore for a precise definition of sustainability in different water management fields. This paper deals with the sustainability of one part of urban water management, namely a water supply. A precise definition of a sustainable water supply system is given, together with a methodological framework that quantifies the degree of water supply sustainability. The proposed framework relies on the proposed quasi-strong sustainability concept, its components (dimensions), their particular relationships and corresponding indicators representing individual processes in the water supply system and utility. The processing of indicators is performed through a joint fuzzy logic/neural network (ANFIS) model. In order to evaluate each sustainability component, separate ANFIS models were created whose results were aggregated into a single result (sustainability index). According to the presented framework, sustainability is evaluated for 17 public water supply systems/utilities in Croatia. Water supply system sustainability (dpeaa)DE-He213 Sustainability quantification (dpeaa)DE-He213 Sustainability indicators (dpeaa)DE-He213 Neuro-fuzzy evaluation of sustainability (dpeaa)DE-He213 Vukovic, Zivko verfasserin aut Vouk, Drazen verfasserin aut Enthalten in Water resources management Dordrecht [u.a.] : Springer Science + Business Media B.V, 1987 31(2017), 12 vom: 11. Mai, Seite 3683-3698 (DE-627)315299924 (DE-600)2016360-5 1573-1650 nnns volume:31 year:2017 number:12 day:11 month:05 pages:3683-3698 https://dx.doi.org/10.1007/s11269-017-1695-5 lizenzpflichtig Volltext GBV_USEFLAG_A SYSFLAG_A GBV_SPRINGER SSG-OPC-GGO SSG-OPC-ASE GBV_ILN_11 GBV_ILN_20 GBV_ILN_22 GBV_ILN_23 GBV_ILN_24 GBV_ILN_31 GBV_ILN_32 GBV_ILN_39 GBV_ILN_40 GBV_ILN_60 GBV_ILN_62 GBV_ILN_63 GBV_ILN_69 GBV_ILN_70 GBV_ILN_73 GBV_ILN_74 GBV_ILN_90 GBV_ILN_95 GBV_ILN_100 GBV_ILN_105 GBV_ILN_110 GBV_ILN_120 GBV_ILN_138 GBV_ILN_150 GBV_ILN_151 GBV_ILN_152 GBV_ILN_161 GBV_ILN_170 GBV_ILN_171 GBV_ILN_187 GBV_ILN_213 GBV_ILN_224 GBV_ILN_230 GBV_ILN_250 GBV_ILN_281 GBV_ILN_285 GBV_ILN_293 GBV_ILN_370 GBV_ILN_602 GBV_ILN_636 GBV_ILN_702 GBV_ILN_2001 GBV_ILN_2003 GBV_ILN_2004 GBV_ILN_2005 GBV_ILN_2006 GBV_ILN_2007 GBV_ILN_2009 GBV_ILN_2010 GBV_ILN_2011 GBV_ILN_2014 GBV_ILN_2015 GBV_ILN_2020 GBV_ILN_2021 GBV_ILN_2025 GBV_ILN_2026 GBV_ILN_2027 GBV_ILN_2031 GBV_ILN_2034 GBV_ILN_2037 GBV_ILN_2038 GBV_ILN_2039 GBV_ILN_2044 GBV_ILN_2048 GBV_ILN_2049 GBV_ILN_2050 GBV_ILN_2055 GBV_ILN_2057 GBV_ILN_2059 GBV_ILN_2061 GBV_ILN_2064 GBV_ILN_2065 GBV_ILN_2068 GBV_ILN_2070 GBV_ILN_2086 GBV_ILN_2088 GBV_ILN_2093 GBV_ILN_2106 GBV_ILN_2107 GBV_ILN_2108 GBV_ILN_2110 GBV_ILN_2111 GBV_ILN_2112 GBV_ILN_2113 GBV_ILN_2116 GBV_ILN_2118 GBV_ILN_2119 GBV_ILN_2122 GBV_ILN_2129 GBV_ILN_2143 GBV_ILN_2144 GBV_ILN_2147 GBV_ILN_2148 GBV_ILN_2152 GBV_ILN_2153 GBV_ILN_2188 GBV_ILN_2190 GBV_ILN_2232 GBV_ILN_2336 GBV_ILN_2446 GBV_ILN_2470 GBV_ILN_2472 GBV_ILN_2507 GBV_ILN_2522 GBV_ILN_2548 GBV_ILN_4035 GBV_ILN_4037 GBV_ILN_4046 GBV_ILN_4112 GBV_ILN_4125 GBV_ILN_4126 GBV_ILN_4242 GBV_ILN_4246 GBV_ILN_4249 GBV_ILN_4251 GBV_ILN_4305 GBV_ILN_4306 GBV_ILN_4307 GBV_ILN_4313 GBV_ILN_4322 GBV_ILN_4323 GBV_ILN_4324 GBV_ILN_4325 GBV_ILN_4326 GBV_ILN_4328 GBV_ILN_4333 GBV_ILN_4334 GBV_ILN_4335 GBV_ILN_4336 GBV_ILN_4338 GBV_ILN_4393 GBV_ILN_4700 43.33 ASE AR 31 2017 12 11 05 3683-3698
allfieldsGer	10.1007/s11269-017-1695-5 doi (DE-627)SPR018393063 (SPR)s11269-017-1695-5-e DE-627 ger DE-627 rakwb eng 550 630 ASE 43.33 bkl Halkijevic, Ivan verfasserin aut Indicators and a Neuro-Fuzzy Based Model for the Evaluation of Water Supply Sustainability 2017 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier Abstract In the field of water management, the evaluation of sustainability has no universal methodological approach nor any consensus regarding the definitions of sustainability or sustainable development. There is an essential need therefore for a precise definition of sustainability in different water management fields. This paper deals with the sustainability of one part of urban water management, namely a water supply. A precise definition of a sustainable water supply system is given, together with a methodological framework that quantifies the degree of water supply sustainability. The proposed framework relies on the proposed quasi-strong sustainability concept, its components (dimensions), their particular relationships and corresponding indicators representing individual processes in the water supply system and utility. The processing of indicators is performed through a joint fuzzy logic/neural network (ANFIS) model. In order to evaluate each sustainability component, separate ANFIS models were created whose results were aggregated into a single result (sustainability index). According to the presented framework, sustainability is evaluated for 17 public water supply systems/utilities in Croatia. Water supply system sustainability (dpeaa)DE-He213 Sustainability quantification (dpeaa)DE-He213 Sustainability indicators (dpeaa)DE-He213 Neuro-fuzzy evaluation of sustainability (dpeaa)DE-He213 Vukovic, Zivko verfasserin aut Vouk, Drazen verfasserin aut Enthalten in Water resources management Dordrecht [u.a.] : Springer Science + Business Media B.V, 1987 31(2017), 12 vom: 11. Mai, Seite 3683-3698 (DE-627)315299924 (DE-600)2016360-5 1573-1650 nnns volume:31 year:2017 number:12 day:11 month:05 pages:3683-3698 https://dx.doi.org/10.1007/s11269-017-1695-5 lizenzpflichtig Volltext GBV_USEFLAG_A SYSFLAG_A GBV_SPRINGER SSG-OPC-GGO SSG-OPC-ASE GBV_ILN_11 GBV_ILN_20 GBV_ILN_22 GBV_ILN_23 GBV_ILN_24 GBV_ILN_31 GBV_ILN_32 GBV_ILN_39 GBV_ILN_40 GBV_ILN_60 GBV_ILN_62 GBV_ILN_63 GBV_ILN_69 GBV_ILN_70 GBV_ILN_73 GBV_ILN_74 GBV_ILN_90 GBV_ILN_95 GBV_ILN_100 GBV_ILN_105 GBV_ILN_110 GBV_ILN_120 GBV_ILN_138 GBV_ILN_150 GBV_ILN_151 GBV_ILN_152 GBV_ILN_161 GBV_ILN_170 GBV_ILN_171 GBV_ILN_187 GBV_ILN_213 GBV_ILN_224 GBV_ILN_230 GBV_ILN_250 GBV_ILN_281 GBV_ILN_285 GBV_ILN_293 GBV_ILN_370 GBV_ILN_602 GBV_ILN_636 GBV_ILN_702 GBV_ILN_2001 GBV_ILN_2003 GBV_ILN_2004 GBV_ILN_2005 GBV_ILN_2006 GBV_ILN_2007 GBV_ILN_2009 GBV_ILN_2010 GBV_ILN_2011 GBV_ILN_2014 GBV_ILN_2015 GBV_ILN_2020 GBV_ILN_2021 GBV_ILN_2025 GBV_ILN_2026 GBV_ILN_2027 GBV_ILN_2031 GBV_ILN_2034 GBV_ILN_2037 GBV_ILN_2038 GBV_ILN_2039 GBV_ILN_2044 GBV_ILN_2048 GBV_ILN_2049 GBV_ILN_2050 GBV_ILN_2055 GBV_ILN_2057 GBV_ILN_2059 GBV_ILN_2061 GBV_ILN_2064 GBV_ILN_2065 GBV_ILN_2068 GBV_ILN_2070 GBV_ILN_2086 GBV_ILN_2088 GBV_ILN_2093 GBV_ILN_2106 GBV_ILN_2107 GBV_ILN_2108 GBV_ILN_2110 GBV_ILN_2111 GBV_ILN_2112 GBV_ILN_2113 GBV_ILN_2116 GBV_ILN_2118 GBV_ILN_2119 GBV_ILN_2122 GBV_ILN_2129 GBV_ILN_2143 GBV_ILN_2144 GBV_ILN_2147 GBV_ILN_2148 GBV_ILN_2152 GBV_ILN_2153 GBV_ILN_2188 GBV_ILN_2190 GBV_ILN_2232 GBV_ILN_2336 GBV_ILN_2446 GBV_ILN_2470 GBV_ILN_2472 GBV_ILN_2507 GBV_ILN_2522 GBV_ILN_2548 GBV_ILN_4035 GBV_ILN_4037 GBV_ILN_4046 GBV_ILN_4112 GBV_ILN_4125 GBV_ILN_4126 GBV_ILN_4242 GBV_ILN_4246 GBV_ILN_4249 GBV_ILN_4251 GBV_ILN_4305 GBV_ILN_4306 GBV_ILN_4307 GBV_ILN_4313 GBV_ILN_4322 GBV_ILN_4323 GBV_ILN_4324 GBV_ILN_4325 GBV_ILN_4326 GBV_ILN_4328 GBV_ILN_4333 GBV_ILN_4334 GBV_ILN_4335 GBV_ILN_4336 GBV_ILN_4338 GBV_ILN_4393 GBV_ILN_4700 43.33 ASE AR 31 2017 12 11 05 3683-3698
allfieldsSound	10.1007/s11269-017-1695-5 doi (DE-627)SPR018393063 (SPR)s11269-017-1695-5-e DE-627 ger DE-627 rakwb eng 550 630 ASE 43.33 bkl Halkijevic, Ivan verfasserin aut Indicators and a Neuro-Fuzzy Based Model for the Evaluation of Water Supply Sustainability 2017 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier Abstract In the field of water management, the evaluation of sustainability has no universal methodological approach nor any consensus regarding the definitions of sustainability or sustainable development. There is an essential need therefore for a precise definition of sustainability in different water management fields. This paper deals with the sustainability of one part of urban water management, namely a water supply. A precise definition of a sustainable water supply system is given, together with a methodological framework that quantifies the degree of water supply sustainability. The proposed framework relies on the proposed quasi-strong sustainability concept, its components (dimensions), their particular relationships and corresponding indicators representing individual processes in the water supply system and utility. The processing of indicators is performed through a joint fuzzy logic/neural network (ANFIS) model. In order to evaluate each sustainability component, separate ANFIS models were created whose results were aggregated into a single result (sustainability index). According to the presented framework, sustainability is evaluated for 17 public water supply systems/utilities in Croatia. Water supply system sustainability (dpeaa)DE-He213 Sustainability quantification (dpeaa)DE-He213 Sustainability indicators (dpeaa)DE-He213 Neuro-fuzzy evaluation of sustainability (dpeaa)DE-He213 Vukovic, Zivko verfasserin aut Vouk, Drazen verfasserin aut Enthalten in Water resources management Dordrecht [u.a.] : Springer Science + Business Media B.V, 1987 31(2017), 12 vom: 11. Mai, Seite 3683-3698 (DE-627)315299924 (DE-600)2016360-5 1573-1650 nnns volume:31 year:2017 number:12 day:11 month:05 pages:3683-3698 https://dx.doi.org/10.1007/s11269-017-1695-5 lizenzpflichtig Volltext GBV_USEFLAG_A SYSFLAG_A GBV_SPRINGER SSG-OPC-GGO SSG-OPC-ASE GBV_ILN_11 GBV_ILN_20 GBV_ILN_22 GBV_ILN_23 GBV_ILN_24 GBV_ILN_31 GBV_ILN_32 GBV_ILN_39 GBV_ILN_40 GBV_ILN_60 GBV_ILN_62 GBV_ILN_63 GBV_ILN_69 GBV_ILN_70 GBV_ILN_73 GBV_ILN_74 GBV_ILN_90 GBV_ILN_95 GBV_ILN_100 GBV_ILN_105 GBV_ILN_110 GBV_ILN_120 GBV_ILN_138 GBV_ILN_150 GBV_ILN_151 GBV_ILN_152 GBV_ILN_161 GBV_ILN_170 GBV_ILN_171 GBV_ILN_187 GBV_ILN_213 GBV_ILN_224 GBV_ILN_230 GBV_ILN_250 GBV_ILN_281 GBV_ILN_285 GBV_ILN_293 GBV_ILN_370 GBV_ILN_602 GBV_ILN_636 GBV_ILN_702 GBV_ILN_2001 GBV_ILN_2003 GBV_ILN_2004 GBV_ILN_2005 GBV_ILN_2006 GBV_ILN_2007 GBV_ILN_2009 GBV_ILN_2010 GBV_ILN_2011 GBV_ILN_2014 GBV_ILN_2015 GBV_ILN_2020 GBV_ILN_2021 GBV_ILN_2025 GBV_ILN_2026 GBV_ILN_2027 GBV_ILN_2031 GBV_ILN_2034 GBV_ILN_2037 GBV_ILN_2038 GBV_ILN_2039 GBV_ILN_2044 GBV_ILN_2048 GBV_ILN_2049 GBV_ILN_2050 GBV_ILN_2055 GBV_ILN_2057 GBV_ILN_2059 GBV_ILN_2061 GBV_ILN_2064 GBV_ILN_2065 GBV_ILN_2068 GBV_ILN_2070 GBV_ILN_2086 GBV_ILN_2088 GBV_ILN_2093 GBV_ILN_2106 GBV_ILN_2107 GBV_ILN_2108 GBV_ILN_2110 GBV_ILN_2111 GBV_ILN_2112 GBV_ILN_2113 GBV_ILN_2116 GBV_ILN_2118 GBV_ILN_2119 GBV_ILN_2122 GBV_ILN_2129 GBV_ILN_2143 GBV_ILN_2144 GBV_ILN_2147 GBV_ILN_2148 GBV_ILN_2152 GBV_ILN_2153 GBV_ILN_2188 GBV_ILN_2190 GBV_ILN_2232 GBV_ILN_2336 GBV_ILN_2446 GBV_ILN_2470 GBV_ILN_2472 GBV_ILN_2507 GBV_ILN_2522 GBV_ILN_2548 GBV_ILN_4035 GBV_ILN_4037 GBV_ILN_4046 GBV_ILN_4112 GBV_ILN_4125 GBV_ILN_4126 GBV_ILN_4242 GBV_ILN_4246 GBV_ILN_4249 GBV_ILN_4251 GBV_ILN_4305 GBV_ILN_4306 GBV_ILN_4307 GBV_ILN_4313 GBV_ILN_4322 GBV_ILN_4323 GBV_ILN_4324 GBV_ILN_4325 GBV_ILN_4326 GBV_ILN_4328 GBV_ILN_4333 GBV_ILN_4334 GBV_ILN_4335 GBV_ILN_4336 GBV_ILN_4338 GBV_ILN_4393 GBV_ILN_4700 43.33 ASE AR 31 2017 12 11 05 3683-3698
language	English
source	Enthalten in Water resources management 31(2017), 12 vom: 11. Mai, Seite 3683-3698 volume:31 year:2017 number:12 day:11 month:05 pages:3683-3698
sourceStr	Enthalten in Water resources management 31(2017), 12 vom: 11. Mai, Seite 3683-3698 volume:31 year:2017 number:12 day:11 month:05 pages:3683-3698
format_phy_str_mv	Article
institution	findex.gbv.de
topic_facet	Water supply system sustainability Sustainability quantification Sustainability indicators Neuro-fuzzy evaluation of sustainability
dewey-raw	550
isfreeaccess_bool	false
container_title	Water resources management
authorswithroles_txt_mv	Halkijevic, Ivan @@aut@@ Vukovic, Zivko @@aut@@ Vouk, Drazen @@aut@@
publishDateDaySort_date	2017-05-11T00:00:00Z
hierarchy_top_id	315299924
dewey-sort	3550
id	SPR018393063
language_de	englisch
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author	Halkijevic, Ivan
spellingShingle	Halkijevic, Ivan ddc 550 bkl 43.33 misc Water supply system sustainability misc Sustainability quantification misc Sustainability indicators misc Neuro-fuzzy evaluation of sustainability Indicators and a Neuro-Fuzzy Based Model for the Evaluation of Water Supply Sustainability
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title	Indicators and a Neuro-Fuzzy Based Model for the Evaluation of Water Supply Sustainability
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title_full	Indicators and a Neuro-Fuzzy Based Model for the Evaluation of Water Supply Sustainability
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title_sort	indicators and a neuro-fuzzy based model for the evaluation of water supply sustainability
title_auth	Indicators and a Neuro-Fuzzy Based Model for the Evaluation of Water Supply Sustainability
abstract	Abstract In the field of water management, the evaluation of sustainability has no universal methodological approach nor any consensus regarding the definitions of sustainability or sustainable development. There is an essential need therefore for a precise definition of sustainability in different water management fields. This paper deals with the sustainability of one part of urban water management, namely a water supply. A precise definition of a sustainable water supply system is given, together with a methodological framework that quantifies the degree of water supply sustainability. The proposed framework relies on the proposed quasi-strong sustainability concept, its components (dimensions), their particular relationships and corresponding indicators representing individual processes in the water supply system and utility. The processing of indicators is performed through a joint fuzzy logic/neural network (ANFIS) model. In order to evaluate each sustainability component, separate ANFIS models were created whose results were aggregated into a single result (sustainability index). According to the presented framework, sustainability is evaluated for 17 public water supply systems/utilities in Croatia.
abstractGer	Abstract In the field of water management, the evaluation of sustainability has no universal methodological approach nor any consensus regarding the definitions of sustainability or sustainable development. There is an essential need therefore for a precise definition of sustainability in different water management fields. This paper deals with the sustainability of one part of urban water management, namely a water supply. A precise definition of a sustainable water supply system is given, together with a methodological framework that quantifies the degree of water supply sustainability. The proposed framework relies on the proposed quasi-strong sustainability concept, its components (dimensions), their particular relationships and corresponding indicators representing individual processes in the water supply system and utility. The processing of indicators is performed through a joint fuzzy logic/neural network (ANFIS) model. In order to evaluate each sustainability component, separate ANFIS models were created whose results were aggregated into a single result (sustainability index). According to the presented framework, sustainability is evaluated for 17 public water supply systems/utilities in Croatia.
abstract_unstemmed	Abstract In the field of water management, the evaluation of sustainability has no universal methodological approach nor any consensus regarding the definitions of sustainability or sustainable development. There is an essential need therefore for a precise definition of sustainability in different water management fields. This paper deals with the sustainability of one part of urban water management, namely a water supply. A precise definition of a sustainable water supply system is given, together with a methodological framework that quantifies the degree of water supply sustainability. The proposed framework relies on the proposed quasi-strong sustainability concept, its components (dimensions), their particular relationships and corresponding indicators representing individual processes in the water supply system and utility. The processing of indicators is performed through a joint fuzzy logic/neural network (ANFIS) model. In order to evaluate each sustainability component, separate ANFIS models were created whose results were aggregated into a single result (sustainability index). According to the presented framework, sustainability is evaluated for 17 public water supply systems/utilities in Croatia.
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container_issue	12
title_short	Indicators and a Neuro-Fuzzy Based Model for the Evaluation of Water Supply Sustainability
url	https://dx.doi.org/10.1007/s11269-017-1695-5
remote_bool	true
author2	Vukovic, Zivko Vouk, Drazen
author2Str	Vukovic, Zivko Vouk, Drazen
ppnlink	315299924
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doi_str	10.1007/s11269-017-1695-5
up_date	2024-07-03T19:22:04.950Z
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Indicators and a Neuro-Fuzzy Based Model for the Evaluation of Water Supply Sustainability

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