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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...
The fault diagnosis model with support vector regression (SVR) and particle swarm optimization algorithm (POSA) for is proposed. The novel structure model has higher accuracy and faster convergence speed. We construct the network structure, and give the algorithm flow. The impact factor of fault behaviors is discussed. With the ability of strong self-learning and faster convergence, this fault detection...
Precise forecasting for shareprice is very important to investment and financing. Support vector regression, called as SVR, is a novel learning algorithm based on statistical learning theory, which has greater generalization ability than traditional neural networks. In order to select the appropriate parameters of SVR, particle swarm optimization is introduced to choose the user-determined parameters...
Fault diagnosis of electronic circuit is important for safety of the device and relevant power system. In the study, support vector regression (SVR) classifiers combined with the particle swarm optimization algorithm (POSA) are applied to construct diagnostic model of electronic circuit, and the diagnostic system structure of electronic circuit is presented on the basis of the model. It is powerful...
Traffic accident forecasting is important for altering and planning of road. Recently time series analysis is an important direction in traffic accident forecasting. Support vector regression (SVR) a kind of SVM used in regression and has better nonlinear forecasting performance than BP neural network. In the paper, the combination method based on particle swarm optimization and support vector regression...
In the predicting financial distress, we know that irrelevant or correlated features in the samples could spoil the performance of the SVR classifier, leading to decrease of prediction accuracy. In order to solve the problems mentioned above, this paper use rough sets as a preprocessor of SVR to select a subset of input variables and employ the particle swarm optimization algorithm (PSOA) to optimize...
Because the network intrusion behaviors are characterized with uncertainty, complexity and diversity, a new method based on support vector regression (SVR) and particle swarm optimization algorithm (PSOA) is presented and used for pattern analysis of intrusion detection in this paper. The novel structure model has higher accuracy and faster convergence speed. We construct the network structure, and...
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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