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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...
In this paper, through combining information diffusion principle and BP neural network theory, a new prediction model of drought disaster assessment is established. First, the original data are fuzzily processed based on information diffusion method, then a new training sample is formed; second, the new sample is used to design and train BP neural network; finally, the trained fuzzy neural network...
The network course evaluation indicator system are established in the paper. The large number of representative uniformly distributed samples are designed for training the nearest neighbor- clustering RBF neural network (RBFNN) and solving the problem of RBFNN model's poor generalization ability. The experiments show the result of nearest neighbor- clustering RBFNN evaluation is very close to the...
As for more predicting errors of deposited metal impacting toughness of E4303 structural steel electrode with low alloy, related sample data are acquired by experiments. A nonlinear combination predicting neural network model for E4303 electrode mechanical properties is build based on predicting data acquired by BP, RBF and adaptive fuzzy neural network. To validate the validity of the model, experiment...
A new type of breakout prediction system based on multilevel neural network for continuous casting was proposed, which consists of a pattern recognition unit of single-thermocouple temperature pattern based on BP neural network, a logic judgment unit of multi-thermocouple temperature pattern and a decision making unit of fuzzy neural network based on T-S (Takagi-Sugeno) model. In the training of BP...
Risk assessment of information security is an important assessment method in the process of detecting potential threats and vulnerabilities. Select methods of risk assessment based on the requirements and the security level of organizational or enterprise information system. The general assessment methods simply calculate the risk value, In this paper, we propose a risk assessment model based on classified...
In the paper, the fuzzy neural network method is introduced into the field of enterprise performance evaluation in order to overcome the deficiencies of the traditional methods. We reference the state-owned capital performance evaluation index system, issued by The Ministry of Finance and other six ministries and commissions, to build evaluation index of this paper, propose and employ a hierarchical...
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...
As fresh farm produce occupies a pivotal position in the daily lives, the fresh farm produce logistics (FFPL) accompanied by it has become a rising industry in the logistics industry. Evaluating the performance of the fresh farm produce logistics and finding the existed problems can improve the fresh farm produce logistics management. To evaluate the FFPL performance, this paper overcomes the shortcoming...
The principle of attrition pattern recognition was discussed based on the research of the engine's characteristic of wear particle and fault mechanism, establish the relationship between the wear particle and attrition pattern, the paper give a new method which can be used for engine's fault diagnosis based on the ferrography technology, by using BP neural network established the fault diagnosis model,...
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...
This paper firstly elaborates the technological innovation and the characteristics of risks of Chinese small & medium-sized enterprises (SMEs) , then analyzes the risk factors of SMEs' technological innovation, on the basis of which the index system of risk evaluation is constructed. Then, incorporating the BP neural network, it proposes the risk evaluation model based on fuzzy neural network...
Using principal component analysis (PCA) and improved fuzzy neural network by PSO to evaluate the success degree in electric power engineering is this paper's innovative points. First we construct the algorithm model which based on PCA and BP neural network improved by PSO. Secondly using PCA to predigest the given index system and then using the relative membership degree processing the date, which...
According to the traffic flow features of urban intersections, a multi-phase adaptive control algorithm is given. The structure of network and program of realizing fuzzy control based on improved multi-layer BP neural networks are obtained. Results of simulation research show that with the abilities of learning and generation, the fuzzy neural controller can cope with the fast changing of arriving...
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