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In the actual production process, the prediction of compressive strength of concrete 28d is of great significance. Prediction of compressive strength of concrete is a typical multi input single output nonlinear systems, which is very close to the BP neural network model. In this paper, the BP neural network is applied to the prediction of the compressive strength of concrete, but the training effect...
In this paper, we construct the financial risk early warning model based on BP neural network, make an empirical analysis of the data between January 2004 and October 2015, proves the reliability of the model prediction results through the training and test of the financial risk early warning model and finally put forward the following suggestions for preventing China's financial risks under the new...
Finger vein identification, as an important part in biological feature identification, has been widely used in various fields. The finger vein image shows the vein structure captured under infrared ray. This paper firstly ado pts the principal component analysis (PCA) to extract low-dimension features of vein images; and then constructs a multi-layer neural network classifier based on BP Neural Network,...
Corneal diseases are increasing year by year in the world, because of the lack of cornea donation. Thus the management of artificial corneal transplantation becomes much more necessary. As an important stage of medical device research projects, the animal experiments of artificial cornea should be completed before the clinical trials. In this paper, the corneas is prepared from pig eyes. Firstly,...
Tax audit has vital influence on improving professional quality of tax team, impartial law enforcement and construction of a clean government. View of the complexity of performance evaluation of tax audit, this paper established the performance evaluation model of tax audit to select the various influential factors via gray-relation analysis. Based on artificial neural network, it built the performance...
BP neural network is an important and efficient method in machine learning. But there are some drawbacks lying in its local minimum and slow convergence speed. To solve these problems and enhance the performance of BP network, an optimized BP neural network by genetic algorithm is proposed in this paper. Firstly, we design a fitness function based on genetic algorithm for the view of obtaining the...
This paper adopts a novel methodology to predict China's grain production. Using a grey model to capture the main trend, this paper establishes a modified model of BP neural networks and then analyzes the irregular events and its influencing direction and degree with Delphi methods. By testing the validity of the final model, the result shows an encouraging conclusion that the model is effective and...
This paper briefly discusses the basic principle of artificial neural network. BP network model based on time series has been established through an instance. Training and testing have been done for the network using existing observation data. Compared with the measured value through regression analysis, the effectiveness and accuracy of the network have been proved. It can be a prediction method...
The dynamic spectrum access method based on human ear perception can keep the quality of analog signal in HD Radio (Hybrid Digital Radio) stable, but it takes too much time to meet the real-time requirement of Radio. This paper proposes a dynamic spectrum access method in HD Radio based on BP NN (Back Propagation Neural Network). In the method, the data of dynamic spectrum access method based on human...
The accurate power output forecasting is advantageous to improving the reliability of power system. This paper presents a new power forecasting model based on grey neural network and Markov chain. In grey neural network, it gains the power at the corresponding time as the forecasting result. As getting the relative prediction residual errors of the forecasting sample data with grey neural network,...
For the disadvantages of BP neural network(NN), which easily traps into a local optimum and is sensitive to the initial parameters of the network, an algorithm for the optimization of the architecture, the weights and the thresholds of neural networks using an improved gene expression programming(IGEP) was presented. First, the basic principles of BP neural network (BP-NN) and GEP was introduced and...
In order to provide a scientific basis for the resource allocation in the stage of checked baggage, improve the service efficiency of airport passenger terminal. According to the flight data of an international airport passenger terminal in 2012 May, this paper establish the BP artificial neural network and multiple regression prediction models respectively, in which the influencing factors are decided...
PMSM servo systems require a high dynamic on speed control. In this paper, a modified model predictive direct speed control based on neural network is proposed, which not only overcomes limitations of cascaded linear controller, but also improves the poor adaptability of model predictive direct speed control(MP-DSC) based on mathematic model. BP neural network (NN) approaches the dynamics of PMSM,...
Artificial neural network (ANN) has been successfully applied into the engineering quality evaluation. With high robustness and fault-tolerant ability, this method works much better than multiple discriminant analysis (MDA) and logistic regression. In order to settle the traditional BP neural network's problem of slow convergence speed and running into the local least value easily while estimating...
Ship motion prediction plays a prominent role in the whole ship motion process. This paper presents a new approach for ship motion prediction. In order to obtain more effective prediction result, the paper studied the BP neural network and Volterra series model, and the chaos characteristics of ship motion time series. A novel method of single-output three-layer BP neural network to identify Volterra...
As a new technology of renewable energy, ground-coupled heat pump system has been rising in our country in recently years. However because of the nonlinear and high degree of coupling, it is not clear to find out the relationship between control variables and total energy consumption of the system. This paper proposes a modeling way for ground-coupled heat pump system that uses artificial neural network,...
The simple PID controller can't get the satisfied degree, especially for the time-varying objects and non-linear systems, the traditional PID controllers can do nothing for them. to non-linear systems, the NN PID controller has a good controller effect in the non-line premature turning and optimizing. The NN PID controller can make both neural network and PID control into an organic whole, which has...
Automatic target recognition (ATR) is an important issue in the military field, the topic of the ATR system is the pattern recognition and classification. In the paper, we present an approach for building an ATR system with improved artificial neural network to recognize and classify the typical targets in the army field. The invariant features of Hu invariant moments and roundness were selected to...
The BP Neural Network's application in financial pre-warning is studied in this paper. Use the dynamic cluster method to classify enterprise's standardized data and get enterprise's pre-warning model through training the BP neural network using classified data. Discuss its implementation on computer in J2EE platform. Through taking test on the panel data, this method can provide accurate forecast...
This paper introduced a new way which utilizes genetic algorithm to optimize neural network weights. And we have worked out the algorithm on ARCGIS and MATLAB platform. Meanwhile, a comprehensive evaluation of environment carrying capacity on Jiulong county has been carried out. The findings and results show that this method can provide a new way to evaluate geological environment, because it can...
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