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In view of monitoring of water quality in Penaeus vannamei culture pond, this paper puts forward a method of two-level data fusion which is usually used to solve the problems of limited resources such as network energy, storage capacity and processing capacity of wireless sensor networks. The data transmitted from the sensor group distributed in the field can be processed and compressed to obtain...
In this paper, the neural network theory is used to establish the BP neural network prediction system for the occurrence of haze. The corresponding parameters are determined by MATLAB language, and the effect of the model is tested by the prediction of Shijiazhuang area. the result shows the feasibility of the predictive model. So it's valuable and has a bright future.
In this paper, rough set, genetic algorithm and BP neural network are combined together in pattern recognition. The neural network, rough set, and genetic algorithms are described in details. The wine dada in UCI database is considered and is dealt with by the above combination approach. The result shows that the accuracy of pattern recognition is improved and the cost of input is decreased. The proposed...
This paper studied the zero-sequence current of the distribution network with DGs. By comparison analysis, DGs do not affect the zero-sequence current measured at the initial points of each feeder. The transient component of zero-sequence current contains abundant fault information. The algorithm decomposed zero-sequence current on four scales with wavelet function db4. Fault characteristic components...
Although the basic method of cognitive reliability and error analysis method (CREAM) is widely used, there are still a lot of problems, for example, there is no consideration of the problems that CPC has different weights in different industrial environments and the process of determining control mode is not smooth. Therefore, the prediction of human error probability (HEP) in the basic method is...
There are always some errors based on nonlinear equation by choice different models in propagation loss prediction. A prediction method for propagation Loss in VHF based on BP neural network is proposed, and the model structure of BP network is designed. Then the propagation loss in VHF is predicted using the measured data of the different terrain. The results show that the prediction accuracy of...
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...
In order to resolve the comprehension difficulties of theory and implementation about multi-objective decision in "Decision Analysis and Decision Support" course for postgraduates, digit recognition experiment is introduced into teaching practice. PCA method is used in the process of digit recognition, which is one of multi-objective decision methods. The digital recognition principles are...
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...
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...
The optimization of the oxygen content in flue gas has a great impact on the safe and economic operation of boiler combustion system. With the model of BP neural network, the optimization of the oxygen content in flue gas is operated based on PSO, while the optimization settings are different under different load segments. The efficiency of the algorithm is proved by validation results of historical...
In order to be able to give an accurate assessment on supply-demand lever of Tanker transportation capacity and to reduce the risk of the corresponding market expansion, a model named PCA-BP Neural Network of capacity early warning on oil tanker. Capacity early warning indicators are built from the perspective of supply-demand level, and the model is applied to the simulation and comparative analysis...
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...
Because the quality of experience (QoE) of video is affected by the content type of the video, this paper firstly establishes a video content classification mechanism. Based on the content types and the objective parameters of bitstream layer and application layer, which have influences on video QoE, a multi-factor QoE evaluation method for H.264/AVC encoded video is proposed. The experimental study...
Based on BP artificial neural network, a method for the recognition of buckle which connect the airbag gas generator brackets and decorative cover is discussed in this paper. First, MATLAB is applied for image binarization and edge extraction. Then extract linear feature of the edge by using Hough transform. Finally, BP neural network is applied for image recognition and classification. It is demonstrated...
Main bearing that plays the role of supporting and making the cutter to rotate and tunnel is the core part of TBM. Because of the harsh working conditions and complex changeful construction, the axial and radial load and environmental factors such as temperature of TBM main bearing are changing to make the fault of main bearing presenting randomness, and then the not easy identified fault may be produced...
In this paper, it presented the method of network intrusion detection based on the neural network GCBP algorithm. By analyzing and comparing the BP algorithm with the GCBP algorithm, what learned is that the GCBP algorithm had overcome the weaknesses, which traditional BP algorithm has of slow convergent speed and easily getting into local minimum. Applicable effects of the method of the intrusion...
To counter the problem in quantitive identification of broken wire for steel rope, a BP neural network model was set up by using Matlab in the article. According to the simulative and real detection data, its features of reliability and usability were proved.
The coordination of control system and guidance system can solve currently urban congestion effectively, and traffic flow prediction is an important part for achieving this process. This paper establishes a short-term traffic flow predicting model of single intersection, then proves the feasibility of BP neural network being used in traffic flow prediction with several kinds of algorithms. Finally...
This article describes the application principle of BP Neural Network and introduces a kind of method that through calling the application program of MATLAB to realize BP Neural Network. By the method of the hybrid programming of MATLAB and Lab VIEW, we can play the advantages of both fully. It is possible that the complicated control arithmetic melts into virtual instrument to realize fault diagnosis.
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