Power battery is the core equipment of electric *** role of power battery is to achieve power ***-time monitoring of battery voltage level is the key to ensure stable operation of the *** the power battery electricity...
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ISBN:
(数字)9789887581536
ISBN:
(纸本)9781665482561
Power battery is the core equipment of electric *** role of power battery is to achieve power ***-time monitoring of battery voltage level is the key to ensure stable operation of the *** the power battery electricity quantity during the power charge in advance can improve the operating efficiency of the *** paper establishes a power battery electricity quantity prediction method based on particle swarm optimization(PSO) bp algorithm,First,important parameter data are collected and the influence of the associated data is analyzed on the power battery electricity ***,the particle swarm optimization bp algorithm is proposed by using the training set data to predict and model the power battery electricity ***,the test set data is used to conduct a comprehensive simulation on the established power battery electricity quantity prediction *** results show that the model prediction data can fit well with the measured data,indicating the effectiveness of the power battery electricity quantity prediction model in this paper.
Traditional linear regression is the primary factor that affects measurement precision in measuring moisture content with microwave resonator. A regression is put forward based on an improved bp algorithm to modify th...
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ISBN:
(纸本)9781728181233
Traditional linear regression is the primary factor that affects measurement precision in measuring moisture content with microwave resonator. A regression is put forward based on an improved bp algorithm to modify the measurement result. First, the regression neural network is pre optimized by using the macro search ability, parallel operation and strong robustness of genetic algorithm. Then, integrating the gradient descent method of bp algorithm, the presented algorithm can effectively avoid the traditional bp algorithm of falling into local minimum, at the same time, high prediction accuracy and fast convergence speed are maintained. It has the characteristics of global superiority and accuracy for optimization, thus improving the measurement accuracy. The experimental results show that the mean square error between predicted moisture and actual moisture is 0.0109, the average absolute error is 0.0702, the average relative error is 0.1161, and the determination coefficient is 0.9989.
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.
In this paper, a dynamics model basing on the bp algorithm is proposed. The algorithm that can enhance the performance of the adaptability is the combination of torque control and a compensation structure using ANN. E...
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ISBN:
(纸本)9783037853191
In this paper, a dynamics model basing on the bp algorithm is proposed. The algorithm that can enhance the performance of the adaptability is the combination of torque control and a compensation structure using ANN. Errors are inevitable while the modeling for dynamics of robot manipulator. But they can be compensated by the compensation structure of ANN. The result of simulation shows that the controller can get the performance of trajectory well and the structure of controller is feasible.
The model of stock price forecast based on data mining of bp neural networks is put forward in this article. On the basis of an integrated data mining process of selection of data samples, data conversion, network mod...
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ISBN:
(纸本)9780769549231;9781467348935
The model of stock price forecast based on data mining of bp neural networks is put forward in this article. On the basis of an integrated data mining process of selection of data samples, data conversion, network modeling, network simulation, and evaluation of results, the prediction about the trend of SSE( Shanghai Stock Exchange) Composite Index provides a higher accuracy. It indicates that the use of data mining of bp neural network in the forecast of non-linear system has advantages, so will it provide a new idea for the forecast of non-linear system.
As to the mules-variable, close coupling, nonlinear and time-varying characteristics of the ball mill pulverizing system, the forward NN-PID controller based on chaos PSO-bp hybrid optimization algorithms for decoupli...
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ISBN:
(纸本)9780769538167
As to the mules-variable, close coupling, nonlinear and time-varying characteristics of the ball mill pulverizing system, the forward NN-PID controller based on chaos PSO-bp hybrid optimization algorithms for decoupling control system of ball mill was proposed. In this controller, the control parameters of PID controller are adaptively adjusted by forward NN, the weights of NN are optimized by the mixed learning methods integrating the offline PSO algorithm combined with chaos strategies of global searching ability, with the online bp algorithm of local searching ability. The results of simulation of Matlab/Simulink show that the hybrid optimization algorithms could solve some problems effectively,such as bp algorithm or PSO algorithm with slow convergence rate and falling to partial minimum easily, and the new control method has better quality than the traditional PID decoupling control method, it has fast tracking ability, strong robustness, good decoupling ability, and it can solve the time-varying problem and the coupling problem of ball mill effectively.
This paper introduces a method of constructing the control model of automatic windshield wiper based on bp neural network. A model of pattern recognition based on bp neural network is built and train it with specialis...
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ISBN:
(纸本)9783037853733
This paper introduces a method of constructing the control model of automatic windshield wiper based on bp neural network. A model of pattern recognition based on bp neural network is built and train it with specialists' experience data, and then tested it. The result indicates that this model based on bp neural network is effective to handle uncertainties and nonlinearities of the automatic windshield wiper system, without use of a sophisticated mathematical model.
This paper raises a kind of improved bp algorithm in order to compensate for some shortcomings which exist in traditional bp neural network. It has been applied to the recognition of character images. Computer simulat...
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ISBN:
(纸本)9783037851494
This paper raises a kind of improved bp algorithm in order to compensate for some shortcomings which exist in traditional bp neural network. It has been applied to the recognition of character images. Computer simulation results demonstrate that it does bring about an ideal result.
It is difficult to learn TSK fuzzy model because the problem is multi-constraint and multi-target optimization. GA-bp hybrid learning method for the model is proposed. Some problems related to a species coding means f...
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ISBN:
(纸本)9781424441983
It is difficult to learn TSK fuzzy model because the problem is multi-constraint and multi-target optimization. GA-bp hybrid learning method for the model is proposed. Some problems related to a species coding means for the model structure, evolution and fitness evaluation strategy are discussed. The error back propagation algorithm (bp) for training the antecedent and consequent parameters during the process of evolution is inferred. The characteristic Of the method requests a little of previous information about objects, and avoids slow convergence, and has better adaptive capability, and is able to obtain compact and accurate fuzzy model from samples, the validity of the method has been demonstrated by an example of function approximation.
Big data has emerged as an important area of study for both practitioners and researchers, reflecting the magnitude and impact of innovation in strategy and model in contemporary business organizations. In the paper, ...
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ISBN:
(纸本)9781509029273
Big data has emerged as an important area of study for both practitioners and researchers, reflecting the magnitude and impact of innovation in strategy and model in contemporary business organizations. In the paper, data mining perspectives are pointed out about how business model innovation is driven by "key data" based on illustrations about big data. Nine basic factors can be represented as business model innovation. GA-bp model is constructed by the combination of genetic algorithm and bp algorithm to extract the knowledge from the data in data mining environment and to find associations, patterns by analyzing the big data sets. Finally, "key data" that affects the consequence significantly can be grabbed to explore entry points for business model innovation in the era of big data, and to offer enterprises and executives for business model innovation from a new version.
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