A mathematical model of engine throttle as the controlled object is established and then the neural network algorithms and MD control are combined. With the self -learning function of the neural network, self -tunings...
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ISBN:
(纸本)9783037855034
A mathematical model of engine throttle as the controlled object is established and then the neural network algorithms and MD control are combined. With the self -learning function of the neural network, self -tunings of PD parameters are realized. The method overcomes disadvantages of PD as parameters which are difficult to determine and embodies better intelligence and robustness of the neural network, the simulation is researched by Matlab and the results show that the PID neural network controller is more accurate and adaptive than conventional PID.
Speaker recognition is to recognize speaker's identity from its voice which contains physiological and behavioral characteristics unique to each individual. In this paper, the artificial neural network model, whic...
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ISBN:
(纸本)9780819491022
Speaker recognition is to recognize speaker's identity from its voice which contains physiological and behavioral characteristics unique to each individual. In this paper, the artificial neural network model, which has very good capacity of non-linear division in characteristic space, is used for pattern matching. The speaker's sample characteristic domain is built for his mixed voice characteristic signals based on Kmeanlbg algorithm. Then the dimension of the inputting eigenvector is reduced, and the redundant information is got rid of. On this basis, bp neural network is used to divide capacity area for characteristic space nonlinearly, and the bp neural network acts as a classifier for the speaker. Finally, a speaker recognition system based on the neural network is realized and the experiment results validate the recognition performance and robustness of the system.
He sensing of the weld pool and controlling of torch at the center of the groove are important problems in back welding of GMAW (Gas Metal Arc Welding) for pipeline, furthermore, the gap of the groove perhaps is varie...
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ISBN:
(纸本)9783037852866
He sensing of the weld pool and controlling of torch at the center of the groove are important problems in back welding of GMAW (Gas Metal Arc Welding) for pipeline, furthermore, the gap of the groove perhaps is varied, which needs an intelligent control strategy to obtain the high welding quality. Fuzzy neural network control method based on bp algorithm is proposed in this paper, from the module of image processing, the corresponding gap location and width can be obtained. Then determine corresponding swing width and speed when weld gap is varied by the network fuzzy inference and calculating Euclidean distance for GMAW variable gap backing welding process. Experiment results show that the designed control method can improve the welding quality compared with traditional fixed swing and the traditional auto swing.
The method using hierarchical clustering classify blouses and human somatatype into different categories. And then using bp algorithm of ANN to simulate the pattern master's experience and technique is proposed an...
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ISBN:
(纸本)9781467302395
The method using hierarchical clustering classify blouses and human somatatype into different categories. And then using bp algorithm of ANN to simulate the pattern master's experience and technique is proposed and used in the flat pattern design of *** method realizes intelligence formation of size for blouse based on effective anthropometric measurements. The Experimental results show that this method is feasible.
Based on the analysis of the back propagation (bp) algorithm, the application limitation of bp neural network mean square error (MSE) used in outlier removal is pointed out. An adaptive error performance function (AE)...
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ISBN:
(纸本)9783642319679
Based on the analysis of the back propagation (bp) algorithm, the application limitation of bp neural network mean square error (MSE) used in outlier removal is pointed out. An adaptive error performance function (AE) is proposed, and it is integrated into Levenberg-Marquardt algorithm (LM). Simulation results show that the three layer bp neural network model trained by the method have a certain ability of recognition for outlier with isolated type and spotted type, not knowing the theoretical true value.
With the fast development of mobile ad hoe networks (MANETs), fault diagnosis has become a critical need to guarantee robust service for various applications. Many techniques have been suggested to solve this problem,...
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ISBN:
(纸本)9781424421077
With the fast development of mobile ad hoe networks (MANETs), fault diagnosis has become a critical need to guarantee robust service for various applications. Many techniques have been suggested to solve this problem, but they still cannot satisfy the special need of MANETs. In this paper, we propose a new fault diagnosis system using hybrid GA-bp neural network. The results of simulation demonstrate that the performance of this system is excellent.
Intrusion detection plays an important part in network security today. bp algorithm which is an algorithm in artificial intelligences can also be used in IDS. This paper make use of improved bp algorithm compared to t...
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ISBN:
(纸本)9780769534947
Intrusion detection plays an important part in network security today. bp algorithm which is an algorithm in artificial intelligences can also be used in IDS. This paper make use of improved bp algorithm compared to the traditional one,the new algorithm brings us higher speed in constringency and more precise in detection. The new algorithm solves the difficulties of real-time system.
To the shortcoming of bp algorithm that solution is sensitive to initial value and easy to trap in local optima, this paper makes a research on Particle Swarm Optimization (PSO), Chaos Optimization algorithm (COA) and...
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ISBN:
(纸本)9789881563811
To the shortcoming of bp algorithm that solution is sensitive to initial value and easy to trap in local optima, this paper makes a research on Particle Swarm Optimization (PSO), Chaos Optimization algorithm (COA) and a modified Chaos Particle Swarm Optimization (CPSO) and applies them in neural networks learning problem. The mechanism of algorithms is explored in depth. A novel method of evaluating the degree of gathering for the swarm is proposed. The performance of algorithms is tested and analyzed by simulation and compared with bp algorithm. The results show that as novel neural networks learning algorithms, PSO and CPSO can overcome the defect of bp algorithm whose solution is sensitive to initial value and have the certain application value.
An adaptive genetic algorithm was proposed to optimization bound in order to speed up the convergence of Gaussian mean *** practical question,as it's difficult to give a critical value *** to the engine nonlinear ...
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ISBN:
(纸本)9783037855409
An adaptive genetic algorithm was proposed to optimization bound in order to speed up the convergence of Gaussian mean *** practical question,as it's difficult to give a critical value *** to the engine nonlinear of the corresponding oil and performance parameters,in gradient genetic algorithm,bp algorithm of local search is *** adaptive value of chromosomes group gets quickly improved with the search in one coding field getting avoided due to the utilization of knowledge of chromosomes in *** crossover and mutation operations are added so that chromosomes will not fall into the local minimum point in *** experimental results prove that the convergence speed of the proposed method is non-linear and the use of gradient genetic algorithm is a fast algorithm that can support the global optimization of chromosomes in a group of process of iteration.
Logistics supplier selection is a comprehensive appraisal influenced by many factors and the key is to choose a method of evaluation reasonably. In this paper, we use bp neural network, starting with the statistics of...
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ISBN:
(纸本)9780878492138
Logistics supplier selection is a comprehensive appraisal influenced by many factors and the key is to choose a method of evaluation reasonably. In this paper, we use bp neural network, starting with the statistics of listed logistics supplier, to train weights of appraisement indexes in self-organization. This method overcomes the impact of the results by subjective factors that exist in the AHP and fuzzy assessment, leads evaluation results to be a relative objectivity and provides a more effective method for the selection of listed logistics supplier.
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