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.
There are some important factors that have an impact on the measurement accuracy of the temperature measurement in multi-spectral radiation, including surface emissivity of measured target, variability emissivity models and effects of high temperature thermal radiation. In this paper, these factors were analyzed. And the BP neural network improved model is applied to multi-spectral temperature measurement...
With the rapid growth of the number of private cars and the development of the second-hand car market, second-hand cars have become the main choice when people buy cars. The online second-hand car platform provides both buyers and sellers the chance of online P2P trade. In such systems, the accuracy of second-hand car price evaluation largely determines whether the seller and the buyer can get more...
The IPTV video evaluation model based on big data is a beneficial basis for IPTV video evaluation. With the new media, social network, Internet of things and cloud computing continuing to evolve, the video-related big data arises at the historic moment. IPTV has also become the choice of more and more users. And IPTV editors are troubled by how to choose the best video for IPTV users. In this paper,...
With the help of MapReduce powerful parallel computing ability and good extensibility, we try to solve the bottleneck problem of traditional BP neural network in dealing with the big data for the training sets in this paper. Through the experimental data for the farmland fertilizer effect, we propose that fertilizer rate is taken as input for the neural network, and ultimately yield is taken as the...
Productivity reserve of emergency material is an effective measure to improve the efficiency of distribution and reduce the cost of physical reserve. We reserve raw materials, advanced technology and production line normally. When the material is needed, the production enterprise shall, according to the agreement, transfer the productivity capacity rapidly to the material. Therefore, it is essential...
Nowadays, the backwardness of the power automation management in our country causes the loss of a lot of energy. In order to improve the situation, an anti-stealing mathematical model is introduced in this paper. Firstly, ten factors are selected to build the indictor evaluation system, data mining is used to process lots of the electricity data. Then, a mathematical model based on BP neural network...
With the development of Internet based services, the requirement of keeping keep their vitality and the user viscosity has become an important challenge. Better understanding of users behaviour is an effective way to improve the services lifecycle management. As such analysis of users experience from web log, questionnaire and some other ways have been attached much importance. From previous studies...
A strong classifier model oriented to the financial risk warning of listed company has played an important role in the risk analysis of enterprise finance. Based on the BP_Adaboost composed of BP neural network and Adaboost algorithm, a strong classifier model of enterprise finance is designed and established, and is verified with the actual data. In the first, the evaluation index has the largest...
In recent years, BP neural network has been widely used in various fields, such as language comprehension, recognition and automatic control, etc. It has the advantages of approximating any nonlinear mapping relationship, better generalization ability, better fault tolerance, simple and easy to be implemented. This paper firstly introduces the basic principles of BP neural network from the two main...
Basing on statistic data of general aviation flying hours of the year 1990–2009, using BP neural network to forecast general aviation flying hours. Analysis BP neural network's principle and normalize the data, establish neural network forecast model of general aviation flying hours time-series data, design the network parameters, and learn an train the history data of the year 1990–2007, test data...
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...
Spares have many kinds and complex specifications, its prediction is difficult, for the problem, the paper proposes the use of nonlinear characteristics of BP neural networks and self-learning ability, based on historical data of spares consumption trains the network of all spares to determine its network model, and used for the future consumption forecast for next year. Through the predictive value...
In order to improve the accuracy of traffic forecasts, it's important to apply the supporting vector regression in prediction of network traffic. This paper introduced key factors in supporting vector-machine regression modeling, and this model is applied to calculate the actual network traffic prediction, which compared with the BP neural network model. The results showed that supporting vector-machine...
The article starts from factors of people, vehicles, road and environment to traffic accidents, builds the three-layer BP neural network model based on the influence factors of traffic accidents, and trains and predicts the traffic accidents of 1998–2009 years in china. The results show that the BP neural networks model used to predict the traffic accidents is precise and feasible.
Combining the intelligent algorithm such as BP neural network and support vector maching (SVM) with traditional chemical method, this paper models the relationship between plant surface color and its pigment. Using the neural network model constructed above, people can figure out the content of plant pigments by getting the corresponding plant surface color information. Compared with the traditional...
The back-propagation algorithm has been used widely as a learning algorithm in a feed-forward multilayer neural network. In this study, fault detection was carried out using the information of the arc current. After collecting the actual data, wavelet transformation were adopted in order to obtain the sideband or detail value characteristics under healthy and various faulty operating conditions. The...
As the critical demand of market for greater product, how to ensure the minimum inventory of customers in the supply chain and to make a reasonable prediction on the customer needs are particularly essential. The neural network technology will be introduced to VMI customer demand prediction, by means of professional visualization software development, supply chain efficiency improvement and budget...
In order to overcome the disadvantages such as low calculation precision and convergence rate of traditional BP neural network algorithm, a kind of nonlinear optimization method-BFGS method for unconstrained extreme problem is introduced into BP neural network algorithm, and a BFGS-BP neural network model is developed, which is applied well in structure deformation monitoring data processing and forecasting...
Determining of the torpedo's service year reasonably, it is an effective way to reduce the military expenses expenditure, and forecast the torpedo economic life. We can forecast the data of exponential use maintenance cost by using the grey metabolism GM(1,1) model. In order to improve the prediction precision, the data was divided into several groups, and prediction residual was modified by using...
Wind farm modeling is an important research topic, but the traditional mechanism modeling method is difficult to get accurate models. However, performance of the neural network model is superior for identification and approximation of complex nonlinear systems. Especially, the BP network has been widely and successfully used in the engineering field. This paper gives a brief introduction to the BP...
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.