scholarly journals Intelligent Soft Computing Models in Water Demand Forecasting

10.5772/63675 ◽  
2016 ◽  
Author(s):  
Sina Shabani ◽  
Peyman Yousefi ◽  
Jan Adamowski ◽  
Gholamreza Naser
Keyword(s):  
Soft Computing ◽  
Water Demand ◽  
Demand Forecasting ◽  
Water Demand Forecasting ◽  
Computing Models

scholarly journals Urban Water Demand Forecasting: A Comparative Evaluation of Conventional and Soft Computing Techniques

Resources ◽  
2019 ◽  
Vol 8 (3) ◽  
pp. 156 ◽  
Author(s):  
Oluwaseun Oyebode ◽  
Desmond Eseoghene Ighravwe
Keyword(s):  
Soft Computing ◽  
Predictive Models ◽  
Water Demand ◽  
Demand Forecasting ◽  
Support Vector ◽  
Ann Model ◽  
Real World Data ◽  
Water Demand Forecasting ◽  
Soft Computing Techniques ◽  
Computing Models

Previous studies have shown that soft computing models are excellent predictive models for demand management problems. However, their applications in solving water demand forecasting problems have been scantily reported. In this study, feedforward artificial neural networks (ANNs) and a support vector machine (SVM) were used to forecast water consumption. Two ANN models were trained using different algorithms: differential evolution (DE) and conjugate gradient (CG). The performance of these soft computing models was investigated with real-world data sets from the City of Ekurhuleni, South Africa, and compared with conventionally used exponential smoothing (ES) and multiple linear regression (MLR). The results obtained showed that the ANN model that was trained with DE performed better than the CG-trained ANN and other predictive models (SVM, ES and MLR). This observation further demonstrates the robustness of evolutionary computation techniques amongst soft computing techniques.

scholarly journals Soft Computing Approaches for Urban Water Demand Forecasting

2016 ◽  
pp. 357-367 ◽  
Author(s):  
Konstantinos Kokkinos ◽  
Elpiniki I. Papageorgiou ◽  
Katarzyna Poczeta ◽  
Lefteris Papadopoulos ◽  
Chrysi Laspidou
Keyword(s):  
Soft Computing ◽  
Water Demand ◽  
Demand Forecasting ◽  
Urban Water ◽  
Water Demand Forecasting ◽  
Urban Water Demand

Water demand forecasting: review of soft computing methods

2017 ◽  
Vol 189 (7) ◽  
Author(s):  
Iman Ghalehkhondabi ◽  
Ehsan Ardjmand ◽  
William A. Young ◽  
Gary R. Weckman
Keyword(s):  
Soft Computing ◽  
Water Demand ◽  
Demand Forecasting ◽  
Computing Methods ◽  
Water Demand Forecasting ◽  
Soft Computing Methods

scholarly journals Variable selection methods for water demand forecasting in Ethiopia: Case study Gondar town

2018 ◽  
Vol 4 (1) ◽  
pp. 1537067 ◽  
Author(s):  
Mohammed Gedefaw ◽  
Wang Hao ◽  
Yan Denghua ◽  
Abel Girma ◽  
Mustafa Ibrahim Khamis
Keyword(s):  
Variable Selection ◽  
Water Demand ◽  
Demand Forecasting ◽  
Selection Methods ◽  
Water Demand Forecasting ◽  
Gondar Town
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