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This paper presents a dynamic mutation particle swarm optimization (DMPSO). The particle swarm optimization (PSO) is a popular swarm algorithm, which has exhibited good performance on many optimization problems. However, similar to other swarm intelligence algorithms, PSO also suffers from premature convergence. Sub swarm and mutation are widely used strategies in the PSO algorithm to overcome the...
This paper presents results of an approach to optimize architecture and weights of MLP Neural Networks, which is based on particle swarm optimization with time-varying parameters and early stopping criteria. This approach was shown to achieve a good generalization control, as well as similar or better results than other techniques, but with a lower computational cost, with the ability to generate...
A hybrid artificial neural network model combining particle swarm optimization (PSO) and back propagation (BP) was used for ice breakup date forecast in the top reach of the Yellow River, China. A comparison of PSO-BP model to other statistical models was also conducted to evaluate the performance of the PSO-BP model. The forecast results indicate a satisfactory performance in the ice breakup date...
The Chinese word segmentation based on the improved particle swarm optimization (PSO) neural networks is discussed in this paper. Firstly, a solution is obtained by searching globally using FPSO (fuzzy cluster particle swarm optimization) algorithm, which has strong parallel searching ability, encoding real number, and optimizing the training weights, thresholds, and structure of neural networks....
The particle swarm optimization was applied in BP neural network training. It reasonably confirms threshold and connection weight of neural network, and improves capability of solving problems in realities. Meanwhile, PSO-BP neural network is applied into classification of fabric defect. The method of orthogonal wavelet transform was used to decompose monolayer from fabric image. And the sub-images...
Classification of EEG mental task signals is a technique in the design of Brain machine interface [BMI]. A BMI can provide a digital channel for communication in the absence of the biological channels and are used to rehabilitate patients with neurodegenerative diseases, a condition in which all motor movements are impaired including speech leaving the patients totally locked-in. BMI are designed...
In this paper a network intrusion detection system using evolutionary neural networks (ENN's) is proposed. The analysis engine of the IDS is modeled by the ENN and its ability to predict attacks in a network environment is evaluated. The ENN is trained by a particle swarm optimization (PSO) algorithm using labeled data from the KDD cup '99 competition.The results from the experiments are compared...
Short term load forecasting is very essential to the operation of electricity companies. It enhances the energy-efficient and reliable operation of power system. Artificial neural networks have long been proven as a very accurate non-linear mapper. ANN based STLF models generally use back propagation algorithm which does not converge optimally & requires much longer time for training, which makes...
Under the application background of network security evaluation research, this paper proposes a method of situation prediction based on particle swarm optimization (PSO) for optimizing BP neural network (BPNN). It uses PSO to reach global optimization of BP network's weight value and threshold value, and then by means of the optimized BP network builds a prediction model to predict the future network...
An hybrid particle swarm optimization PSO-based wavelet neural network for modelling the development of fluid dispensing for electronic packaging is presented in this paper. In modelling the fluid dispensing process, it is important to understand the process behaviour as well as determine optimum operating conditions of the process for a high-yield, low cost and robust operation. Modelling the fluid...
The IT projects risk assessment is a focus problem of the practice and theories research of IT project management. In this paper, a set of index system of IT project risk assessment is established. Based on the index system, an integration classifier with GCPSO-based artificial neural network is established to assess IT projects risk in project management. At last, an experiment is given and BP neural...
In recent years, back-propagation (BP) neural network has been widely applied to the remote sensing image classification. However, the BP method based on the gradient descent principle suffers from the problem of getting stuck at local minimum. In addition, only using spectral information for multispectral remote sensing image classification could not get the ideal result. In this paper, a new method...
As an organic whole, there are unknown nonlinear relationships existing in the different parameters of wood. This paper is aimed to solve the complex nonlinear relationship of wood parameters. Maoershan larch is selected for the test material. A neural network model is adopted with the density of wood ring and moisture content as the model inputs, wood vertical elastic modulus as the output. Particle...
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...
Recently quite much attention was given to the investigation of Particle Swarm Optimization algorithm (PSO). It was proved that PSO algorithm has exhibited good performance across wide range application problems. This paper proposes the use of PSO algorithm for decision making model updating. The decision making model is used to generate one-step forward investment decisions for stock markets. The...
Prorsad neural network trained with particle swarm optimization (PSO) algorithm was studied, and the new method was suggested. Compared with BP algorithm , this new method shows high effectivity.
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