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Based on the method of Skeletonization, the concept of influence factor is introduced in this paper. A method for trimming the fat from a Back Propagation (BP) neural network is proposed by modifying weight and influence factor alternately, and node with the least influence factor was deleted. This method is applied to modeling superheated steam temperature system of plant station. Simulation results...
To overcome the unsatisfying trend prediction results of network public opinion in the present research, this paper put forward a method of Levenberg-Marquardt-based Back-Propagation (LM-BP) neural network algorithm to predict the network public opinion trend. Taking the microblog as the research object, the effectiveness and reliability of the method are proved with some real data in this article...
In the submarine oil pipeline inspection, the magnetic flux leakage data may exist some abnormal values. In order to obtain the true value, the magnetic flux leakage data should be preprocessed. One of the important parts of data preprocessing is to discriminate the abnormal values, and predict and compensate its true value reasonably and effectively. In this paper, it combines threshold segmentation...
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...
In order to select the better wine grape varieties, and improve wine quality evaluation standards, the paper made a cluster analysis of wine grape samples based on the selected 57 physicochemical indexes. It's also classified different categories of wine grape after comparing the results of the wine quality evaluation. SPSS for canonical correlation analysis was used to find typical indicators, which...
Carrier landing is the accident prone phase during carrier-based aircraft task. The prediction of carrier landing position is able to provide pilots with decision basis while various guidance modes represented by automatic carrier landing system (ACLS) are available. Air wake and deck heaving motion are both crucial factors leading to carrier landing error. Hence, taking F-18/A with ACLS as the research...
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...
Study on the prediction of stock price has great theoretical significance and application value. Traditional stock forecasting methods cannot fit and analysis highly nonlinear, multi-factors of stock market well, there are problems such as the prediction accuracy is not high, the slow training speed etc. In order to improve the accuracy of stock price forecasting, this paper proposes a prediction...
Most of the traditional indoor location algorithms based on the distance loss model always filter the received signal strength, and then we can use the distance loss model to infer the distance between the nodes and achieve location eventually. The accuracy of the traditional indoor location algorithm is very unstable due to multipath propagation effects and complex signal attenuation law in the indoor...
Predictive analytics of the traffic flow is paid more attention by the traffic engineering experts and relevant departments. However, how to forecast traffic volume still is an important problem affecting the traffic theoretical and practical analysis. Firstly, this paper set up a three layers BP neural network basing on the actual situation to introduce the modeling process of the neural network...
In order to solve the problems existing in the fault diagnosis of tank fire control system, such as bigger subjectivity and less accuracy, a fault diagnosis model based on BP (Back Propagation) is studied. The working conditions of tank fire control system are described with a group of state parameters. A fault diagnosis model is established and a self adaptive variable BP learning algorithm is designed...
Affected by microtopography and micro-meteorological phenomena condition, accidents such as lines trip out, electric arc burn, hardware fittings and insulator damage, broken wire stocks, break line and downed towers often happen on overhead transmission lines, which has seriously threatened the safety operation of the power system, and brought the huge losses to the national economy. Therefore, it...
According to the status quo of integrated support ability evaluation for meteorological equipment, index system of equipment integrated support ability evaluation for meteorological station is established. Using BP neural network method, equipment support ability evaluation model is established. Combined with concrete examples of meteorological station equipment support ability evaluation, a better...
Due to the following characteristics of offshore program, such as one-time large-scale investment, comprehensive high-risk, long payback period, high uncertainty, high regional and political, the investors has been paid more and more attentions to the risk of offshore program. Combined with the characteristics of offshore program risk management, and with the use of BP neural network theory, this...
A BP network model for transformer fault diagnosis is established based on the MATLAB environment in this paper. A large number of data samples are collected and tested, L_M algorithm is used for training samples and simulation in network model. The actual output is gained and made comparative study with the expected output. Finally, it confirms that this network model has a high accuracy and can...
After a full study on the factors that affect the selection of CEO, this article has built a scientific criterion to select CEO by using the BP neural networks. Based on BP neural network, The CEO selection mechanism has solved the contradictory problems between the assumption and realities of logistic econometric model. It not only improves the quality of simulation results, but also helps companies...
Because of the developing environment, the occurring conditions and the randomness, uncertainty and fuzziness of mine water inrush, it is a very complex nonlinear system to determination of mine water inrush sources. Artificial neural network is of the stronger self-organization, self-adaptability and self-learning capability, which is specially suited to solve nonlinear problems. In the paper, we...
The operation principles of proton exchange membrane (PEM) fuel cell system relate to thermodynamics, electrochemistry, hydrodynamics, mass transfer theory, which form a complex nonlinear system, and it is different to establish its mathematical model. This paper utilizes the approach and self-study ability of artificial neural network to build a model of nonlinear system, and adapts the modified...
In order to study the impact of drivers' distance cognition difference on traffic safety in dynamic environment of daytime and night-time, a real road tests was carried out by asking 19 drivers randomly selected to percept the distances of obstacles with different distances and velocities on daytime and nighttime. The values of cognition are obtained by statistical methods. The distance cognition...
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