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Evaluating road safety is essential in identifying the potential road safety hazard which could result in casualties and property losses. in this paper, a BP neural network was built by using neural network toolkit in "Matlab", Two similar roadways are used in calibrating and validating the network. The high level of predictability provided that the application of BP neural network model...
With the e-commerce market competition becoming more and more furious, it has become one of the focuses of companies that how to avoid customer churn and carry out customer retention. This paper applies many techniques of data mining to the research of customer churn, such as clustering analysis, decision tree, neural network, etc, establishes an e-commerce customer churn model and analyzes the factors...
Objective: An intrusion detection system was constructed on the basis of the characteristics of BP neural network model. Methods: According to the capture engine of the text, all network data stream flowed through the systematic monitoring network segment will be captured, feature extraction module analyze and process the captured network data flow, you can extract complete and accurate eigenvector...
The discrimination and supervision of insider trading and market manipulation is very hard because of the cover-up used and the large trading data. So this paper firstly analyses the impact of insider trading and market manipulation on the security market. Based on it, we set up the discrimination model with probabilistic neural network, and use it to discriminate the insider trading and market manipulation...
In stamping process, springback is always determined by process parameters, such as blank-holder force, mould parameters, material parameters, and so on. Prediction of springback and parameters is a multi-objective optimization problem. Firstly, based on the same quantity of orthogonal experimental samples, prediction accuracy and efficiency of back propagation neural network (BPNN) prediction model...
In order to arrange the generators between hydrogenerators and themeturbine, the water data need to be sent to dispatch staffs timely. The daily submitted water data are intensive. And the dispatch staffs are pressured. Because the above objective conditions might lead to human error problems during the water submit processing, an artificial intelligence method of hydrological data validation and...
The robust adaptive decoupling control method is proposed to the helicopter rotor concordant load system. The controller realized the asymptotic tracking of the desired output trajectory, which used the PID controller as closed-loop controller and used the CMAC neural network to approximate the nonlinear and uncertainties. The stability analyses show that the control method has stability. The main...
Eddy current testing (ECT) is becoming a widely used inspection technique, particularly in the aircraft, power and nuclear industries. Many factors may affect the eddy current response. Inverse problems to determine the thickness from ECT signals of multilayer conductors have been a challenge for a certain degree. The objectives of this study are to introduce a method based on improved back propagation...
The methodology of developing fuzzy cognitive map (FCM) still exhibited weaknesses. This paper investigated a hybrid framework for learning FCM, which was combined of the real-coded genetic (RCGA) algorithm and nonlinear Hebbian learning (NHL) algorithm. This approach combined the synergistic theories of neural networks and fuzzy logic. The hybrid algorithm is introduced, presented and applied successfully...
The problem of stochastic robust stability of a class of stochastic neural networks with time-varying delays and parameter uncertainties is investigated in this paper. The parameter uncertainties are time-varying and norm-bounded. The time-delay factors are unknown and time-varying with known bounds. Based on Lyapunov-Krasovskii functional and stochastic analysis approaches, some new stability criteria...
In the fault diagnosis of the plane steering surface, exact fault prediction is very important for the security of the aircraft. According to design requirement of the plane steering surface fault prediction system, the application of neural network technique is plane fault prediction is presented, and the algorithm based on the neural network model in the prediction system is given. Considering the...
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