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This study applies a novel neural network technique, support vector regression (SVR), to rainfall forecasting. To build an effective SVR model, SVR's parameters must be set carefully. This study proposes a novel approach, known as particle swarm optimization algorithm (SVR-PSO), which searches for SVR's optimal parameters, and then adopts the optimal parameters to construct the SVR models. The monthly...
Accurate grid resources prediction is crucial for a grid scheduler. In this study, support vector regression (SVR), which is an effective regression algorithm, is applied to grid resource prediction. In order to obtain better prediction performance, SVR's parameters must be selected carefully. Therefore, a particle swarm optimization-based SVR (PSO-SVR) model, in which PSO is used to determine free...
This paper presents a comparative study of two artificial intelligence based heterogeneous catalysis modeling strategies, namely ANN-CPSO and SVR-CPSO, for modeling dimethyl ether (DME) in direct synthesis from syngas process (called STD process), for reducing both high temporal costs and financial costs, and accelerating the process of industrialization synthesis of DME. In the two hybrid approaches,...
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