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Guard against financial risks, reduce bad loans, increase the ability to identity risk of commercial banks, the key is risk warning. In view of the increasing proportion of personal loans in banking business, it is particularly important to warning personal loans default risk. Commercial bank lending itself is a complex nonlinear system, using general linear theory is difficult to objectively reflect...
Established the computational model about the safe distance of vehicles. In order to simulate the dynamic model of rear-end, based on VB software to build a freeway rear-end simulation system. Simulation system provides an important means for in-depth study on rear-end probability. To investigate the non-linear relationship of probability and impact factors of rear-end, established probability of...
Established the computational model about the safe distance of vehicles. In order to simulate the dynamic model of rear-end, based on VB software to build a freeway rear-end simulation system. Simulation system provides an important means for in-depth study on rear-end probability. To investigate the non-linear relationship of probability and impact factors of rear-end, established probability of...
Nowadays as low carbon economy is greatly advocated worldwide, the electricity consumption caused by a huge number of embedded computer systems is gaining more and more attention. Different instruction set, software algorithm and high-level software architecture can significantly affect the system energy consumption. In this paper, we first analyze the relations between software power consumption...
A method for prediction discrete data is presented in this article. In order to forecast the discrete data, the experiment that use the GM (1,1) and BP networks to predict discrete data are respectively executed, we found that AGO operation in the GM method can effectively reduce randomness of the discrete data, so AGO operation is applied into the BP network method. According to the result of the...
The problem of power battery state of charge estimation for hybrid vehicle directly affects the vehicle performance and driving distance. Considering there exists nonlinear relationship between the battery state of charge and the observable external characteristics, this paper presents a kind of algorithm which is based on the combination of genetic algorithm and back-propagation neural network namely...
Groundwater table often shows complex nonlinear characteristic. Back Propagation (BP) neural network is increasingly used to predict groundwater table. But man-made selecting the structure of BP neural network has blindness and expends much time. In order to overcome shortcomings of traditional BP neural network, Particle Swarm Optimization (PSO) algorithm was adopted to automatically search BP neural...
Aims at the complex and dynamic nature of traffic flow in mountain expressway tunnel, through the analysis of change characteristics of traffic flow, based on BP network improve the existing expressway traffic flow model, this thesis puts forward the Elman dynamic neural network model of traffic flow predicting in mountain expressway tunnel. In practice, this model has the strong operational, we adopt...
The thesis introduces grey system model and BP neural network. Through making full use of the merits of GM(1.1) and neural network model and overcoming their drawbacks, we construct the grey residue amending combined and prediction model based on BP Neural network, and such combined model as "combined prediction model= tendency prediction model/GM(1.1)+neural network model", and makes a...
This paper provides a method of discriminate analysis based on artificial neural network (ANN). 2-Class and multi-class discriminant analysis are separately discuss using Back Propagation network. The results of our study indicate that discriminate analysis based on ANN could classify the observation more accurately than the traditional methods.
Flood disaster management is an important part of flood risk assessment. A regional flood disaster risk assessment index system is established in this paper. Then principal component analysis (PCA) method and BP neural network are combined, and a regional flood disaster risk assessment of PCA-BP neural network model is established. PCA-BP neural network model analyze the loss of flood disaster about...
The paper combines theory with practice and applies neural network technology to establish a credit risk assessment model based on BP neural network technology. The assessment model, to some extent, improves the traditional credit risk analytical approaches in our country, overcoming the defects that subjectivity exists in credit risk measurement, expanding developing route for credit risk measurement...
To overcome the shortcomings of traditional software reliability models and adapt to the current software and its development process characterized by increasing complexity, this paper proposes a hybrid model with BP neural network model serving as a nonlinear hybrid system of several traditional models, to improve the prediction accuracy. Because of its input diversity, the model can be used universally...
The thesis introduces grey system model and BP neural network. Through making full use of the merits of GM(1.1) and neural network model and overcoming their drawbacks, we construct the grey residue amending combined and prediction model based on BP Neural network, and such combined model as “combined prediction model= tendency prediction model/GM(1.1)+neural network model”, and makes a contrast between...
Firstly, an air passenger capacity investigation at the capital international airport is made, and a composite forecasting model based on total air passenger capacity is established, in which multiple regression and ARIMA model are parallel connection and their forecast results are series connection with BP neural network. Secondly, according to the average growth rate of air passenger capacity, all...
Introduced the method of artificial neural networks, established a three-tier management of forest resources feed-forward back-propagation neural network model. Simulation results show that artificial neural network model can be applied to dynamic simulation of forest resources. And high precision, linear regression equation is a strong correlation. The results clearly demonstrate the superiority...
We present a model using back-forward feed propagation method for tree diameter distribution in stand based on artificial neural network with three-tier management. This model is able to describe dynamics of diameter distribution in stands with high precision and good correlation. We also demonstrate that an ANN model from it has superiority in regression due to its ability to overcome some difficulties...
Irradiation has been used for food preservation in many areas, however the high dose of irradiation is able to influence the safety of food. Rice flour is a staple food hackneyed in our lives and a part of them are processed by irradiation. Here we offer a new method for fast discriminating the rice flour with different doses of irradiation based on visible-near infrared spectroscopy. We dealt with...
For the method of neural network can modify and better the forecasting effects of grey prediction model, a combined NN-GM (1,1) forecasting model is proposed. After the time sequence of the network traffic was analyzed, the equidistant metabolic GM (1,1) forecasting model was constructed, and the residual error of the model was corrected by neural network based on Error Back Propagation (BP) algorithm...
Based on granularity distribution of soil having fractal character, the fractal dimension of soil is studied by theory analysis and calculation. The structure character of soil is quantized by using fractal dimension, which build up a foundation for neural network considering soil structure in the process of prediction of frost heave. Topology structure of BP neural network is built, and L-M arithmetic...
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