The Infona portal uses cookies, i.e. strings of text saved by a browser on the user's device. The portal can access those files and use them to remember the user's data, such as their chosen settings (screen view, interface language, etc.), or their login data. By using the Infona portal the user accepts automatic saving and using this information for portal operation purposes. More information on the subject can be found in the Privacy Policy and Terms of Service. By closing this window the user confirms that they have read the information on cookie usage, and they accept the privacy policy and the way cookies are used by the portal. You can change the cookie settings in your browser.
In order to testify the inner power of enterprise development, BP network Model is adopted and relevant data is selected (including input and output data) as experiment samples. After inputting sample data, the system studies the data automatically. When the error is reduced to the required extent, the system stops studying. The BP neural network study calculation is processed by Matlab software in...
The issue of the modeling for the distribution management based on demand forecasting. ANN model is applied to the field of demand forecasting. The modeling of market demand forecasting is built using BP algorithm. The model of forecasting is established by Simulation model of MATLAB. Based on them, a simple numerical example is given to test and forecast with three-layer BP network model.
In order to reflect the quality of construction projects, this paper constructed the evaluation index system of construction quality and designed BP network model based on neural network theory. Then in the MATLAB environment, an instance of the model was simulated, the results are consistent with the results of expert evaluation, and show that the method can make the quality evaluation of construction...
In order to predict the influence of earthquake on building and buried pipeline, predictive model is constructed on the basis of artificial neural network (ANN). According to double parallel feed-forward neutral network model, which is a basic model of Back Propagation (BP) network, predictive model and calculating method are analyzed. The model is applied to the calculation of earthquake affecting...
Urban building energy consumption is one important part of the total social energy consumption. How to predict building energy consumption of urban development trends and master the changes of urban building energy consumption are important link of building energy-saving. In order to forecast urban building energy consumption from both the macro and micro aspects, multi-layer feed forward artificial...
This paper discusses risk assessment of supply chain based on BP neural network. The risk assessment procedure is discussed and after the risk factors of supply chain identification and analysis, the risk assessment model is built with BP neural network. Through training of the model using MATLAB neural network toolbox and testing the model shows the preciseness and comprehensive practicability.
The application of back propagation(BP) neural networks in the Naval Minesweeping Effectiveness Estimating (NMEE) was investigated by introducing the theory of BP artificial neural network (BPANN) and establishing a learning algorithm of forecasting for minesweeping effectiveness under a certain battle-field situation. A three-layer BP network was designed and a computer program was written based...
Scope: Commercial banks, as the key of the nation's economy and the center of financial credit, play a multiple irreplaceable role in the financial system. Credit risks threaten the economic system as a whole. Therefore, predicting bank financial credit risks is crucial to prevent and lessen the incoming negative effects on the economic system. Objective: This study aims to apply a credit risk assessment...
Investment risks assessment of high-tech projects is a more complex process, involving various factors and it is not entirely the linear relationship between influencing factors and measurement results. Artificial neural network (ANN) has a strong nonlinear mapping ability, with strong learning ability and high classification and prediction accuracy. The paper applied ANN to establish a new risk assessment...
This paper presents applications of A.I. in turbine engines fault diagnosis and health management. Self-organizing map and back-propagation neural networks supported with fuzzy-logic decision-making tool were developed and integrated together as diagnostics software for turbine engines. Two different neural network architectures were trained and used. An unsupervised network (SOM) was used to cluster...
In this paper, the authors established an evaluation model of university teaching quality based on back-propagation neural networks. Quantified indices of teaching quality were inputs of the model, while teaching effect was output. The empirical research by MATLAB showed that this evaluation approach was suitable for the university teaching quality assessment tasks, which not only overcomes subjective...
Coal is a key of basic energy in China, and it supports the rapid development of the national economy. In the coming period, coal will also play the very important role in base energy. Therefore, the prediction of coal demand is particularly important in future. In this paper, the double hidden layers BP neural network is established and simulated based on Matlab technology. After testing actual data,...
This paper presents a method to discriminate the temporary faults from the permanent ones in an extra high voltage (EHV) transmission line so that improper reclosing of the line onto a fault is avoided. The fault identification prior to reclosing is based on optimized artificial neural network associated with standard error back-propagation, Levenberg Marquardt algorithm and resilient back-propagation...
Set the date range to filter the displayed results. You can set a starting date, ending date or both. You can enter the dates manually or choose them from the calendar.