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http://hdl.handle.net/1942/23264
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DC Field | Value | Language |
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dc.contributor.author | Kokkinos, Konstantinos | - |
dc.contributor.author | PAPAGEORGIOU, Elpiniki | - |
dc.contributor.author | Poczeta, Katarzyna | - |
dc.contributor.author | Papadopoulos, Lefteris | - |
dc.contributor.author | Laspidou, Chrysi | - |
dc.date.accessioned | 2017-02-28T12:41:01Z | - |
dc.date.available | 2017-02-28T12:41:01Z | - |
dc.date.issued | 2016 | - |
dc.identifier.citation | Czarnowski, I.; Caballero, A.M.; Howlett, R.J.; Jain, L.C. (Ed.). Intelligent Decision Technologies 2016: Proceedings of the 8th KES International Conference on Intelligent Decision Technologies (KES-IDT 2016) – Part II, Springer International Publishing,p. 357-367 | - |
dc.identifier.isbn | 9783319396262 | - |
dc.identifier.issn | 2190-3018 | - |
dc.identifier.uri | http://hdl.handle.net/1942/23264 | - |
dc.description.abstract | This paper presents an integrated framework for water resources management at urban level which consists of a Neuro-Fuzzy and Fuzzy Cognitive Map-based, (FCM) decision support system (DSS) based on multiple objectives and multiple disciplines for planning and forecasting. The proposed DSS has as primary goals to: (a) adaptively control the water pressure of the water distribution system by forecasting the water demand at the urban level and (b) to reduce leakage of the water network by controlling the water pressure. The system follows a model-driven architecture with the inclusion of the FCM-based models and a spatio-temporal model for arranging all data. The validation of the proposed learning algorithms is made for two case studies that comprise different water supply characteristics and correspond to different locations in Europe. | - |
dc.language.iso | en | - |
dc.publisher | Springer International Publishing | - |
dc.relation.ispartofseries | Smart Innovation Systems and Technologies | - |
dc.rights | © Springer International Publishing Switzerland 2016 | - |
dc.subject.other | fuzzy cognitive maps; neuro-fuzzy; water management; forecasting; prediction; decision support | - |
dc.subject.other | Fuzzy Cognitive Maps; Neuro-Fuzzy; Water management; Forecasting; Prediction; Decision support | - |
dc.title | Soft Computing Approaches for Urban Water Demand Forecasting | - |
dc.type | Proceedings Paper | - |
local.bibliographicCitation.authors | Czarnowski, I. | - |
local.bibliographicCitation.authors | Caballero, A.M. | - |
local.bibliographicCitation.authors | Howlett, R.J. | - |
local.bibliographicCitation.authors | Jain, L.C. | - |
local.bibliographicCitation.conferencedate | June 15-17, 2016 | - |
local.bibliographicCitation.conferencename | 8th KES International Conference on Intelligent Decision Technologies (KES-IDT) | - |
local.bibliographicCitation.conferenceplace | Puerto de la Cruz, Spain | - |
dc.identifier.epage | 367 | - |
dc.identifier.spage | 357 | - |
dc.identifier.volume | 57 | - |
local.format.pages | 11 | - |
local.bibliographicCitation.jcat | C1 | - |
dc.description.notes | [Kokkinos, Konstantinos; Papadopoulos, Lefteris] Inst Informat Technol, CERTH, 6th Km Charilaou Thermi Rd, Thermi 57001, Greece. [Papageorgiou, Elpiniki I.] Hasselt Univ, Fac Business Econ, Hasselt, Belgium. [Poczeta, Katarzyna] Kielce Univ Technol, Dept Informat Syst, Al Tysiaclecia Panstwa Polskiego 7, PL-25314 Kielce, Poland. [Laspidou, Chrysi] Univ Thessaly, Dept Civil Engn, Nea Ionia, Greece. | - |
local.type.refereed | Refereed | - |
local.type.specified | Proceedings Paper | - |
local.relation.ispartofseriesnr | 57 | - |
dc.identifier.doi | 10.1007/978-3-319-39627-9_31 | - |
dc.identifier.isi | 000389636900031 | - |
local.bibliographicCitation.btitle | Intelligent Decision Technologies 2016: Proceedings of the 8th KES International Conference on Intelligent Decision Technologies (KES-IDT 2016) – Part II | - |
item.contributor | Kokkinos, Konstantinos | - |
item.contributor | PAPAGEORGIOU, Elpiniki | - |
item.contributor | Poczeta, Katarzyna | - |
item.contributor | Papadopoulos, Lefteris | - |
item.contributor | Laspidou, Chrysi | - |
item.fulltext | With Fulltext | - |
item.accessRights | Restricted Access | - |
item.fullcitation | Kokkinos, Konstantinos; PAPAGEORGIOU, Elpiniki; Poczeta, Katarzyna; Papadopoulos, Lefteris & Laspidou, Chrysi (2016) Soft Computing Approaches for Urban Water Demand Forecasting. In: Czarnowski, I.; Caballero, A.M.; Howlett, R.J.; Jain, L.C. (Ed.). Intelligent Decision Technologies 2016: Proceedings of the 8th KES International Conference on Intelligent Decision Technologies (KES-IDT 2016) – Part II, Springer International Publishing,p. 357-367. | - |
item.validation | ecoom 2018 | - |
Appears in Collections: | Research publications |
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chp%3A10.1007%2F978-3-319-39627-9_31.pdf Restricted Access | Published version | 712.71 kB | Adobe PDF | View/Open Request a copy |
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