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The power factor and unbalanced three-phase power are important factors affecting the power quality in the three-phase power supply system. The smart algorithm strategy used as control strategy has the high practical value in terms of implementation of integrated compensation (including the power factor correcting and the three-phase unbalance reduction). Based on the research of the basic principles...
It is known that a direct application of artificial neural network (ANN) for modeling high power, nonlinear, and impact load may lead to inaccuracies. This paper proposes an approach that the characteristic of the high power, nonlinear and time varying load is modeled by advanced ANN, which is implemented by using back propagation network (BPN) and dynamic time warping (DTW) algorithms. The model...
As concerning the problems of intelligent construction existed in the decision support system (DSS) model, one construction plan and one system structure of intelligent construction of DSS model based on integration of neural network (NN) and expert system (ES) are presented. On the basis of separating the literal description and the data description, ES was applied to select the model type. On the...
An extended method for obtaining crypto-graphically strong substitution boxes (S-boxes) based on discretized chaotic map system (DCMS) is presented in this paper. The S-boxes' design criteria such as bijection, nonlinearity, strict avalanche, output bits independence and equiprobable input/output XOR distribution of these S-boxes are analyzed in detail. The results of numerical analysis show that...
This paper presents a method for obtaining dynamically cryptographically strong substitution boxes (S-boxes) based on discrete chaos map system (DCMS). The cryptographical properties such as bijection, nonlinearity, strict avalanche, output bits independence and equiprobable input/output XOR distribution of these S-boxes are analyzed in detail. The results of numerical analysis show that all the criteria...
This paper investigates the use of a support vector machine (SVM) to predict the state of charge (SOC) of a large-scale Ni-MH battery pack in hybrid electric vehicles (HEV). Estimate the state of charge (SOC) is very essential for HEVspsila energy monitoring and management systems. The nonlinear SOC dynamics is represented by a nonlinear autoregressive moving average with exogenous variables (NARMAX)...
The m-Sequences have been widely used in many areas such as telecommunication, cryptology, navigation and radar. Due to the difficulties of constructing the feedback functions of M-sequences, a new method of constructing one class M-sequence and its feedback function were presented. A sub-function Y was formed by remodeling the M root-sequence states diagram. To affix sub-function y to the feedback...
According to the complexity of the traffic historical data and the randomness of a lot of uncertain factors influence, a hybrid predicting model that combines both autoregressive integrated moving average (ARIMA) and multilayer artificial neural network (MLANN) is proposed in this paper. ARIMA is suitable for linear prediction and MLFNN is suitable for nonlinear prediction. This paper also investigates...
A number of different forecasting methods have been proposed for traffic flow forecasting including historic method, real-time method, time series analysis, and artificial neural networks (ANN), but accuracy and time efficiency in prediction are a couple of contradictions to be hard to resolve for real-time traffic information prediction. In order to improve time efficiency of prediction, a new short-term...
In this paper, the theory of sparse decomposition is introduced to weak signal detection, and the improved matching pursuit (MP) algorithm is studied to accomplish anti-interference process of some typical signals, such as a weak sine wave signal submerged in strong noises. The improved matching pursuit algorithm uses dual-parameter Gabor dictionary, and the iterative times can be modified in accordance...
Traditional recognition methods which mainly match object images with their skeleton couldnpsilat resolve well complex objectspsila recognition problems. So in the paper, with an introduction and improvement of moment invariants, a new image recognition method is proposed with the combination of skeleton and moment invariants. Firstly, the paper analyses the thoughts of method. Then, the concept of...
The detection of objects, the key technology in the field of image recognition, is the base of accuracy improvement of image recognition process. In this paper, a model is provided for detection and recognition of a objectpsilas internal structure. This model, which is based on Moment and Hough, combines geometric features as its parameter identification, and its evaluation criteria is matching percent...
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