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JCP
2008
166views more  JCP 2008»
13 years 8 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...
Ishmael S. Msiza, Fulufhelo Vincent Nelwamondo, Ts...
BMCBI
2006
169views more  BMCBI 2006»
13 years 8 months ago
Machine learning techniques in disease forecasting: a case study on rice blast prediction
Background: Diverse modeling approaches viz. neural networks and multiple regression have been followed to date for disease prediction in plant populations. However, due to their ...
Rakesh Kaundal, Amar S. Kapoor, Gajendra P. S. Rag...
IJCNN
2008
IEEE
14 years 3 months ago
Long-term prediction of time series using NNE-based projection and OP-ELM
Abstract— This paper proposes a combination of methodologies based on a recent development –called Extreme Learning Machine (ELM)– decreasing drastically the training time of...
Antti Sorjamaa, Yoan Miche, Robert Weiss, Amaury L...
IJCNN
2008
IEEE
14 years 3 months ago
Support vector machines and dynamic time warping for time series
— Effective use of support vector machines (SVMs) in classification necessitates the appropriate choice of a kernel. Designing problem specific kernels involves the definition...
Steinn Gudmundsson, Thomas Philip Runarsson, Sven ...
ISNN
2005
Springer
14 years 2 months ago
Support Vector Regression for Software Reliability Growth Modeling and Prediction
In this work, we propose to apply support vector regression (SVR) to build software reliability growth model (SRGM). SRGM is an important aspect in software reliability engineering...
Fei Xing, Ping Guo