We present a modeling method of the Nonlinear Dynamic System Nerve Network Based on tne unaouc time series in this paper and put forward a new *** last,A case study on modeling of the chaotic time series was performed.
We present a modeling method of the Nonlinear Dynamic System Nerve Network Based on tne unaouc time series in this paper and put forward a new *** last,A case study on modeling of the chaotic time series was performed.
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.
In this paper, we develop GA-bp algorithm by combining genetic algorithm (GA) with back propagation (bp) algorithm and establish genetic bp neural network. We also applied bp neural network based on bp algorithm and g...
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In this paper, we develop GA-bp algorithm by combining genetic algorithm (GA) with back propagation (bp) algorithm and establish genetic bp neural network. We also applied bp neural network based on bp algorithm and genetic bp neural network based on GA-bp algorithm to discriminate earthquakes and explosions. The obtained result shows that the discriminating performance of genetic bp network is slightly better than that of bp network.
Focused on various bp algorithms with variable learning rate based on network system error gradient, a modified learning strategy for training non-linear network models is developed with both the incremental and the d...
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Focused on various bp algorithms with variable learning rate based on network system error gradient, a modified learning strategy for training non-linear network models is developed with both the incremental and the decremental factors of network learning rate being adjusted adaptively and dynamically. The golden section law is put forward to build a relationship between the network training parameters, and a series of data from an existing model is used to train and test the network parameters. By means of the evaluation of network performance in respect to convergent speed and predicting precision, the effectiveness of the proposed learning strategy can be illustrated.
For the first time, artificial neural network (ANN) technique was used to investigate the properties of PZT based piezoelectric ceramic system in this article. Selecting several rare earth oxide dopants, the experimen...
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For the first time, artificial neural network (ANN) technique was used to investigate the properties of PZT based piezoelectric ceramic system in this article. Selecting several rare earth oxide dopants, the experimental results of 21 samples were analyzed by a three-layer bp network based on the homogenous experimental design. Through comparison it is found that the ANN model are much more accurate than conventional multiple nonlinear regression analysis (MNLR) model for the same set of data. The results of ANN model were also expressed and analyzed by intuitive graphics. The ANN prediction of the formulations not included in the train set also agree well with the testing values. It is indicated that the three-layer bp network based modeling is a very useful tool in dealing with problems with serious non-linearity encountered in the formulation design of piezoelectric ceramics.
Based on expatiated the basic structure model and some general improved algorithms of bp neural network, this paper brings forward a new self-organization learning algorithm. The algorithm can change network's lea...
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Based on expatiated the basic structure model and some general improved algorithms of bp neural network, this paper brings forward a new self-organization learning algorithm. The algorithm can change network's learning rate followed by network's convergence state, and can adjust network's structure based on the neurons' change and their relationship. Because of these improvements, the algorithm can keep consistency between the network's converging speed and the learning rate change, also it can ensure that the network's structure tends to validity progressively.
An artificial neural network (ANN) short term forecasting model of consumption per hour was built based on seasonality,trend and randomness of a city period of time water consumption *** hidden layer nodes,same inpu...
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An artificial neural network (ANN) short term forecasting model of consumption per hour was built based on seasonality,trend and randomness of a city period of time water consumption *** hidden layer nodes,same inputs and forecasting data were selected to train and forecast and then the relative errors were compared so as to confirm the NN structure.A model was set up and used to forecast concretely by *** is tested by examples and compared with the result of time series trigonometric function analytical *** result indicates that the prediction errors of NN are small and the velocity of forecasting is *** can completely meet the actual needs of the control and run of the water supply system.
This paper deals with the characteristics and design of visual quick nerval network. Numerous case studies are made on slopes to calculate the stability of slopes which have undergone potential arc failure and wedge f...
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This paper deals with the characteristics and design of visual quick nerval network. Numerous case studies are made on slopes to calculate the stability of slopes which have undergone potential arc failure and wedge failure. Calculation results indicate that reliable judge can be made with regard to the stability of slopes using nerval network.
pH regulation is a complicated and comprehensive technique in the crop fertigation system. In this paper, a method is put forward to improve the quality of pH regulation, using artificial neural network to map a nonli...
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pH regulation is a complicated and comprehensive technique in the crop fertigation system. In this paper, a method is put forward to improve the quality of pH regulation, using artificial neural network to map a nonlinear relationship between pH interfering factor and the switching frequency of pH control valve, which achieves the dynamic feedforward compensation to the main control system.
The creep rupture life of Ni-base superalloy was investigated by the bp algorithm based on ANN method. The model of relation among different temperatures, external stress and creep rupture life of the alloy with diffe...
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The creep rupture life of Ni-base superalloy was investigated by the bp algorithm based on ANN method. The model of relation among different temperatures, external stress and creep rupture life of the alloy with different compositions was developed. The simulation for creep rupture life of the alloy was conducted through net training. The simulated results was well in agreement with the measured ones. It shows that ANN method is an available and efficient way to predict the Ni-base superalloy's creep rupture life.
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