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This paper focuses on traffic flow forecasting approach based on soft computing tools. The soft computing tools used is Particle Swarm Optimization (PSO) with Wavelet Network Model(WNM). The forecast of short-term traffic flow in timely and accurate is one of important contents of intelligent transportation system research. The modelling of traffic characteristics and the prediction of future traffic...
A predictive model of water-quality, which based on wavelet transform and support vector machine, is proposed. This model uses wavelet transform to get water time sequence variations in different scale, and optimizes three parameters of Regression Support Vector Machine with improved Particle Swarm Optimization algorithm, to improve the accuracy of prediction model. This model is used to take one-step...
This paper presents a generic and patient-specific classification system designed for robust and accurate detection of ECG heartbeat patterns. The proposed feature extraction process utilizes morphological wavelet transform features, which are projected onto a lower dimensional feature space using principal component analysis, and temporal features from the ECG data. For the pattern recognition unit,...
Deregulation has created a competitive market among power market participants, and the pricing system plays an important role. Locational marginal pricing (LMP) provides clear market signals that identify the locations where power market participants could make their decisions so as to maximize their profits. In this work, artificial neural networks (ANNs) models are used to predict hourly LMP. ANN...
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