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2008

Water Demand Prediction using Artificial Neural Networks and Support Vector Regression

12 years 1 months ago
Water Demand Prediction using Artificial Neural Networks and Support Vector Regression
Computational Intelligence techniques have been proposed as an efficient tool for modeling and forecasting in recent years and in various applications. Water is a basic need and as a result, water supply entities have the responsibility to supply clean and safe water at the rate required by the consumer. It is therefore necessary to implement mechanisms and systems that can be employed to predict both short-term and long-term water demands. The increasingly growing field of computational intelligence techniques has been proposed as an efficient tool in the modeling of dynamic phenomena. The primary objective of this paper is to compare the efficiency of two computational intelligence techniques in water demand forecasting. The techniques under comparison are Artificial Neural Networks (ANNs) and Support Vector Machines (SVMs). In this study it was observed that ANNs perform significantly better than SVMs. This performance is measured against the generalization ability of the two techni...
Ishmael S. Msiza, Fulufhelo Vincent Nelwamondo, Ts
Added 13 Dec 2010
Updated 13 Dec 2010
Type Journal
Year 2008
Where JCP
Authors Ishmael S. Msiza, Fulufhelo Vincent Nelwamondo, Tshilidzi Marwala
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