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In different conditions such as light and complex backgrounds, we get some car images, the traditional methods are slow convergence speed and low accuracy. This paper presents a method which applies fuzzy theory to enhance several features of for target. To obtain the license information, we use an improved BP neural network algorithm, by through setting proper numbers of hidden layer of BP network,...
This paper proposes a composite method for short-term load forecasting, which is based on fuzzy clustering wavelet decomposition and BP neural network. Firstly, the similar-day's load is selected as the input load based on the fuzzy clustering method; secondly, the wavelet method is applied to decompose the similar-day load into the low frequency and high frequency components, from which the feature...
Fuzzy optimization neural networks combines neural networks model with fuzzy optimization model, its application must establishes fixed expression topology according to actual problem. Aiming at the experiments in which multiple stages, influence factors and treatment levels should be considered, a tower-topology is established to simulate relationships between factors and results in this paper. In...
Developed a novel model named dynamic neural network model for the risk evaluation of an investment project. The fundamental identification of weight was given based on Triangle Fuzzy Number and Analytical Hierarchy Process (TFN-AHP), through combining the weight with dynamic decision group, a formula of dynamic normalized weight vector was established by Clustering, and the final weight vector of...
Project selection is the key to organizational survival and development. Through surveys and interviews, the project evaluation index system is established from the fore aspects based on the Balanced Scorecard (BSC). Then the fuzzy multi-index evaluation method and the neural network theory are combined to create the BP neural network model of organizational project selection. Finally, the application...
Prediction of breakdown voltage of transformer oil facilitates the early fault diagnosis, prevention and treatment of transformer. In this article, a prediction method of breakdown voltage via multi-parameter correlation was proposed considering the lack of research in this field. Through examining the routine monitoring data of transformer oil by gray correlation analysis, some parameters which have...
In this paper, a method of complement of fuzzy rough set and BP neural network was proposed, and an early warning model of electronic information products on Technical Barriers to Trade (TBT) was given by the method. The attribute reduction for indicators of early warning based on fuzzy rough set can not only enhance the veracity of attribute reduction, but also improve the accuracy of the training...
With the conception of quantum mechanics, quantum neural network has a fuzzy character, and the fuzzy and uncertain datas can be distributed to different patterns, through which the uncertainty of pattern recognition is decreased. In this paper, the classified effect of quantum neural network has been used in the fault diagnosis of transformer. Firstly, the parameter space is mapped to the fault state...
Combines fuzzy logic inference system with Neural Network, a fault diagnosis method for diesel engine based on Adaptive Network-based Fuzzy Inference System (ANFIS) is studied. The theory and arithmetic and structure of this system are introduced, and a fault model for the fuel injection system of a diesel engine is built with the help of Matlab Fuzzy Toolbox. Simulation results demonstrate that the...
In this paper, 36 coats, which had different ease and made from different fabrics, were made and their profile appearance were evaluated by seven experts. These coats were scanned by using [TC]2 three dimensional body scanner and their three dimensional virtual pictures was shown according to the OpenGL software surface display theory. Key factors witch affected garments appearance ease most were...
Due to the fact that the detection of intrusion is inefficient and lacks intelligence in current intrusion detection system, this paper integrates BP neural network and support vector machine (SVM) based on the theory of neural network integration, applying fuzzy clustering technology to cluster data, choosing data from the cluster centre to train ensemble individuals, then selecting and integrating...
The classification and identification technology plays an important role in the research of brain-computer interface (BCI) systems. In this paper, we do fuzzy clustering disposal for the multi-channel electroencephalogram (EEG) during finger movement at first according to event-related desynchronization phenomena (ERD) in the event-related EEG. Then we classify signal-trial EEG with the feature extracted...
Aimed at minimizing the centre distance of reducer in lift mechanism and being satisfied with the conditions of load-bearing capacity and distribution of transmission ratio, the mathematical model in fuzzy design optimization was set up which was to considering the random character of the value of design parameters. Firstly, the number of teeth of the minor gear in the system, its normal module, and...
In the practice of risk evaluation on real estate, there are many events' degree of risk can not be accurately described, the application of fuzzy comprehensive evaluation method can reflect the risk degree of every element in detail. In addition, the combination use of BP neural network (ANN) and expert system (Es) method can determine impact extent of the risk factors on the real estate risk and...
A method based on BP neural network was put forward to estimate the probability which a graduate is employed. The paper first introduced the principle of BP neural network. For the analysis of the employment problem of graduates, we adopt the multi-factor fuzzy comprehensive evaluation method of the fuzzy mathematics, which quantified the various data of the student information, and then set up a...
The customer satisfaction degree represents enterprise value, also a fundamental of enterprise in their development. As a evaluation index which used to measure competition power and quality situation of the product, more and more enterprise pay great attention to the customer satisfaction degree. But the indexes of customer satisfaction is hard to be measured or defined by usual method. In this paper,...
The mergers and acquisitions (M&A) performance measurement is an important tool to test the M&A effects, evaluate the validity of M&A decision-making, and which is an important part in the M&A management. But how to measure the M&A performance is a major issue that troubled many enterprises. This paper overcomes the shortcoming of tradition linear M&A measuring methods, proposes...
Recent researches show that lung cancer owns actual dose-response relationship with calendar-year smoking environment exposure matrix and individual medical record. In this paper, two hybrid prediction models based on BP neural network, ES (exponential smoothing) and FCM (Fuzzy C-Means) clustering are proposed to predict the possible rate and ages of smokers suffering the lung cancer. The BP-ES (Exponential...
Red rot disease and ring spot disease are two common diseases at the seedling stage of sugarcane. According to the image characteristics of diseased spots, sugarcane diseased spots classification using BP neural network is proposed. Firstly, the feature parameter combination of mean value of color component Cr, mean value of color component V and roundness is selected as the feature parameters of...
Fuzzy neural network, which is based on fuzzy theory and BP neural network, plays an important role in practical. But the difficulty is how to construct its structure model. In this paper, according to the hypostasis of hidden layer, a fuzzy neural network model based on fuzzy clustering is brought forward, in which features of the samples are extracted and output information is synthetically considered...
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