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The following topics are dealt with: genetic algorithm; evolutionary programming; neural network; information security; intelligence control algorithm; data mining; e-learning and quantum computing.
Classification is an important problem in data mining. This paper focuses on a method of optimizing classifiers of neural network by Genetic Algorithm based on principle of gene reconfiguration, and implement classification by training the weight. The paper uses shift reverse logic crossover operation and the improved genetic algorithm The article using the typical method for optimizing BP neural...
Although the decision support systems (DSS) theory and application has already taken significant progress, the development of DSS is strongly challenged for the bottleneck of existing serial characters store and process mechanism. The neural network is an ultra large-scale, time dynamic system with highly nonlinear. Its most important features are paralleled distributive treatment with large scale,...
By integrating the global searching advantage of Genetic Algorithm (GA) and the local searching ability of BP Artificial Neural Network (BP ANN), this paper proposes a new model of BP ANN based on GA (called GA-BP ANN). Firstly, it applies GA to optimize the initial interconnecting weights and thresholds of BP ANN. Then, it utilizes the BP algorithm to train the neural network more accurately. This...
A prediction model of compression ratio for extruded oilseeds was developed based on improved BP neural networks. As an applied example, the predicted curves were successfully used to predict critical pressing pressures. Results indicated that the predicted values of compression ratios conformed to the measured values well for extruded cottonseed and castor been. There was a limiting compression for...
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...
The pollution of Qinhuangdao Port is the bottleneck of economic development, so how to correct the environmental assessment of the work environment has important significance. The main pollutants in Qinhuangdao port is coal dust pollution, through various observation points on the measurement indicators of pollutants by EPA experts scoring can get a group of data, and then through various BP neural...
This paper improved and optimized the topology structure of the system cloud grey neural network model (SCGNNM (1,1)) and presented a novel SCGNNM (1,1) based on time response model. Because the dispersed data of time response model can be regarded as the data abstracted from the continued function, the model's precision can be improved greatly. Meantime, the learning algorithm is given. Finally,...
The paper proposes the new model of the genetic algorithm and BP neural networks to predict the blood concentration of Cyclosporine. The BP model was optimized by genetic algorithm to overcome the slower convergence speed, and the best result was found in the particular condition with the strong search function of genetic algorithm. The prediction precision of average blood concentration of Cyclosporine...
The paper proposes the use of the complex-valued neural network to detect spam. The main contributions of this work are two-fold. First, we present a new model based on the CVNN for classifying personal E-mails. We changed the input of the email into 2-dimensional vector. The complex-valued neural network is superior for handling 2-dimensional vector data stream, because the input of the complex-valued...
At present, the multivariate linear regression analysis was adopted in the biological toxicity forecast through establishment equation of the QSAR mostly, but the error forecasted was big in many situations because of the complexity and nonlinearity of structure-activity relationship, and it has a high request to the sample selection. In this paper forecast model of the nitrobenzene compound biological...
Research on stock company comprehensive assessment has always been an important focus for economists and computer experts. In this paper, the financial indexes reflecting the comprehensive capability of stock companies as main research objects including income per thigh, clean asset per thigh, profit rate of clean asset, Kohonen network with the advantage of clustering is applied to assess for stock...
3D data registration and classifier are two important components in face recognition system. Aiming at the handicaps in current methods such as slow convergence or easiness of getting into local optimization, this paper works out a novel face recognition method combining filled function method, which can find a lower local minimizer by leaving the local minimizer previously found. By repeating these...
Sunspot number time series, as a multivariable, strong coupling and nonlinear time series, has encountered troubles to describe its changes rules with modeling method owing to great complexity of sunspot number change. The main aim of this study is to develop a novel prediction method, based on the Quantum Neural Networks, which is composed of some quantum neurons and traditional neurons based on...
The implications of stable epistemologies have been far-reaching and pervasive. The synthesis of red-black trees has been validated in the paper. An atomic tool for investigating Smalltalk (Titi) was described, disconfirming that sensor networks can be made peer-to-peer, stable, and adaptive. Firstly, motivated the need for neural networks, validated the emulation of symmetric encryption. Furthermore,...
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