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Congestion Control is concerned with allocating the network resources such that the network can operate at an optimum performance level when the demand exceeds or it is near the capacity of the network resources. This paper presents a novel scheme of adaptive Neuro-Fuzzy Inference Controller (ANFIS). The advantages of both Fuzzy Logic and Neural Networks are combined together to design the ANFIS....
Using Delphi method to determine the indicators and their weights of performance evaluation of enterprise's marketing team members, this paper proposes a performance evaluation model of enterprise's marketing team members based on BP neural network. Then, it operates the empirical analysis in an enterprise. The empirical results show that the model is an effective evaluation method because its output...
In this paper, the advanced fuzzy neural network is brought into the expressway ramp control by integrating the technology of fuzzy system and neutral network, which simplifies the control process and could make it a real-time control accurately. This approach considers both the traffic density and the entrance queue length together and aims at controlling both of them simultaneously. The study shows...
For the variable speed operation of large scale wind turbine, the vibrations become key problem that can not be ignored. In this paper, the active vibration control based on neural network PID control strategy was researched. Firstly, PID control algorithm was analyzed. Then, the PID control based on neural network was described especially BP network and its algorithm. In the end, this control method...
Effective fault detection and diagnosis (FDD) is especially important for some special applications, such as Navy ships operating in hostile environments. So far, FDD for nonlinear systems has not been fully explored. This paper makes an effort to fill the gap by extending an existing monitor architecture and a series of algorithms for FDD of permanent magnet synchronous motors (PMSM). A fault model...
At present, classic methods are often used to predict groundwater level, but the result is not ideal. Though GM(1,1) and neural network are applied in this field, some limits have been existed. In view of the difficulty to predict groundwater level, in this paper, a grey system-neural network united model is developed based on the grey theory and neural network method. It predicts various tendency...
In view of the defect that the grey method can only predict the tendency approximately and artificial neural network can not predict the future tendency really, a new combined grey neural network model was proposed. This paper mainly analyses the groundwater quality and establishes their mathematical model based on the groundwater monitoring data of one area by combined grey neural network method...
A method based on BP neural network was put forward to estimate the probability which a graduate is employed. The paper first introduced the principle of BP neural network. For the analysis of the employment problem of graduates, we adopt the multi-factor fuzzy comprehensive evaluation method of the fuzzy mathematics, which quantified the various data of the student information, and then set up a...
The evaluation of information system is a complex system. Domestic and foreign scholars generally agreed that the evaluation of information system is a difficult task. In this paper, we combined the principal component analysis (PCA) and neural network (NN) in order to evaluate the information system. Using principal component analysis to extract availability information and to solve a principal component,...
A fault diagnosis method based on immune neural network is proposed in this paper. In this method the weights of neural network is encoded as the antibody, and the network error is considered as the antigen. Firstly the weights of the network are searched globally using immune algorithm, then searched locally using BP algorithm. The simulation is done through the experiment of the pump-jack, and the...
A banknote orientation recognition method is introduced in the paper. In order to avoid dealing with large numbers of image pixels and reduce calculation, the banknote image is divided into several blocks. And then, neural network is applied to establish a universal recognition method. Different banknote can get corresponding model through BP network that is introduced in detail in the paper.
This paper dealt with the parameters detection of weak signal, which based on chaos and neural network. According to the characteristics of chaotic time series, chosen Elman network as neural network, constructed the network detection model though solving the correlation dimension of chaotic time series to determine input and output dimensions of the network, adopted single-step prediction method...
The urban road tunnel longitudinal ventilation is a complex non-linear process with the feature of strong time-varying, always affected by a good many uncertain factors, it is difficult to establish a precise mathematical model by using the traditional linear control theory. The paper describes an intelligent model consists of two levels of neural network, the first level is a traffic flow neural...
According to the demand of energy saving and energy conservation, unit process energy consumption of automobile enterprise is researched in this paper. Firstly the principal component analysis is utilized to choose main factor from many factors. Secondly, RBF neural network is utilized to set up unit process energy consumption model. The error of unit process energy consumption model is plusmn2%.The...
In order to improve the accuracy of prediction of gas emission, a novel nonlinear combined prediction method using support vector machines(SVM) was introduced. SVM, which was based on the rule of structural error minimization, was adopted to build a multi-input and single-output nonlinear prediction model. The model parameters were tuned by training samples sets and evaluated by the principle of the...
This paper presents a BP neural network-based model of enterprise learning capacity evaluation methods. Design a learning capacity enterprises evaluation index system through the point of learning process of enterprises. And build a model of enterprises learning capacity neural network. Experimental result shows that a BP neural network method is feasible and effective for enterprise learning capacity...
Patterns could be discovered from historical data and can be used to recommend decisions suitable for a typical situation in the past. In this study, the sliding window technique was used to discover flood patterns that relate hydrological data consisting of river water levels and rainfall measurements. Unique flood occurrence patterns were obtained at each location. Based on the discovered flood...
In order to counterbalance the unfairness to rare class on using Support Vector Machine to credit assess for imbalanced dataset from commercial banks, an adjustment Method of the separating hyperplane is proposed in the paper. Based on Fisher discrimination, the projected class mean and variance are got by projecting two classes samples onto the normal vector of the separating hyperplane, then adjust...
This paper presents a simulated annealing based rule extraction algorithm (SAREA) for credit scoring problems. In previous studies, several classification algorithms like statistical models, mathematical programming, and artificial intelligence techniques have been used. This paper aims to illustrate the ability of SA to develop accurate classifiers for credit scoring problems. The use of SA is a...
A model of the relationship between the structure of alcohols and their chromatographic retention index has been set by Randic branch index, 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. A model based on radial basis function (RBF) neural network for determining the...
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