A new conversion method for fault tree (FT) to binary decision diagram (BDD) was introduced. Firstly, FT was reduced and the reduction rule was proposed, share-node conception was introduced on the basis of FT decompo...
详细信息
A new conversion method for fault tree (FT) to binary decision diagram (BDD) was introduced. Firstly, FT was reduced and the reduction rule was proposed, share-node conception was introduced on the basis of FT decomposition, then the rules of connection of component BDD was proposed. Furthermore the route-based BDD reduction rule was proved, with which reduction can be done at the same time with BDD composition, and the route sequence and cut sets can be obtained, while computation and storage is greatly reduced during the process. Finally, the procedure of the transformation is presented. The affectivity effectiveness and practicability is thereby proved.
A Backlash neural network model is proposed for the systems with hysteresis nonlinearity. In order to approximate the hysteresis nonlinearity, Backlash-type operators are used as one layer of the neural network. Then,...
详细信息
A Backlash neural network model is proposed for the systems with hysteresis nonlinearity. In order to approximate the hysteresis nonlinearity, Backlash-type operators are used as one layer of the neural network. Then, the number of Backlash operators and neurons of hidden layer are gotten through simulation. Compared with the normal BP network, the results show the improvement validity of the proposed Backlash neural network model for describing the hysteresis nonlinearity.
One problem of marriage in honey bees optimization (MBO) is that its complex computation process will limit its applications. The paper proposed an improved marriage honey bees optimization (IMBO). By randomly initial...
详细信息
One problem of marriage in honey bees optimization (MBO) is that its complex computation process will limit its applications. The paper proposed an improved marriage honey bees optimization (IMBO). By randomly initializing drones and restricting the condition of iteration, the calculation process becomes easier. The global convergence characteristic of IMBO is also proved based on the Markov chain theory. With different number of nodes, traveling salesman problem(TSP) is used to compare the IMBO with MBO and genetic algorithm(GA). Simulation results show that IMBO has better convergence performance.
A new method and apparatus is proposed to improve the precision and reduce the cost of photoelectric encoder measurements. The method is based on highest resolution measurement and completely statistical analysis. The...
详细信息
A new method and apparatus is proposed to improve the precision and reduce the cost of photoelectric encoder measurements. The method is based on highest resolution measurement and completely statistical analysis. The system includes a stepping motor, a high precision worm reduction gear, a high speed single chip microcomputer, a low cost incremental optical electric encoder and some multi interfaces of communication protocols. The single chip microcomputer as the lower system can test and collect the optical electric encoder. The PC computer as host-computer can deal with the test data. The precision of the system can reach 18 binary digits. Results of application in practice showed that the method and apparatus is efficient and effective, the cost of the apparatus is less than the some kind of system.
Focuses on a method of parameter identification from indirect data, generated by indirect model. The indirect data are preprocessed in order to approximate the direct data generated by original model. Parameters of th...
详细信息
Focuses on a method of parameter identification from indirect data, generated by indirect model. The indirect data are preprocessed in order to approximate the direct data generated by original model. Parameters of the original model are identified from the approximate direct data. This method is employed to establish ballistic mathematical model of projectile based on firing table data. A ballistic integrated coefficient is proposed and identified by parameter identification method in order to establish ballistic mathematical model. The data used in identification are approximated by firing table data. Computation showed that the method was more precise than the simple table lookup method. Moreover, the method is a low-cost way to identify parameters and establish ballistic models.
In the high speed range, vector control of rotor flux orientation of an induction machine implements good perfornance. However, the perfornance in low speed rang deteriorates because of the inaccurate estimation of ro...
详细信息
ISBN:
(纸本)9623675445
In the high speed range, vector control of rotor flux orientation of an induction machine implements good perfornance. However, the perfornance in low speed rang deteriorates because of the inaccurate estimation of rotor flux and speed. In this paper, modified voltage model for rotor flux estimation and neuron model-reference adaptive system (MARS) for speed estimation are used to improve the perfornance of speed sensorless vector control. To improve the accuracy of rotor flux estimation, the stator resistance is identified on-line. The experimental results show that the proposed scheme yields improved perfornance in low speed range.
To found the suitable models to describe the behavior of biochemistry systems, the dynamic Ε -SVM method was proposed on the basis of SVM. Each training sample uses different error. The existed methods for selecting ...
详细信息
In the trend prediction to the state development of the large-scale rotary sets, the most important problem is how to enhance the accuracy of prediction. The combined predicting model based on neural networks can real...
详细信息
ISBN:
(纸本)980656068X
In the trend prediction to the state development of the large-scale rotary sets, the most important problem is how to enhance the accuracy of prediction. The combined predicting model based on neural networks can realize a comprehensive utilization to the effective information offered by several prediction methods and receive an optimum prediction result. But in the traditional combined predicting model, the weight coefficients are calculated complicatedly. And the current combined predicting model based on neural networks lacks enough emphases to the advantages of different prediction methods. Therefore, a new combined predicting model based on variable-weight neural networks is presented in this paper. And the weight coefficients of all methods in the new combined predicting model are also determined. By using the new model, a satisfying predictive effect is received in the application of the large-scale rotary sets.
To found the suitable models to describe the behavior of biochemistry systems, the dynamic epsiv-SVM method was proposed on the basis of SVM. Each training sample uses different error. The existed methods for selectin...
详细信息
To found the suitable models to describe the behavior of biochemistry systems, the dynamic epsiv-SVM method was proposed on the basis of SVM. Each training sample uses different error. The existed methods for selecting the parameters of SVM not only consume time, but also are difficult to find the optimal parameters. The optimal parameters were automatically decided by using multi-object genetic algorithm (MOGA). A new modeling method that combined MOGA with the dynamic epsiv-SVM was presented. The model for penicillin titer pre-estimate was developed by it in Matlab 6.5 with data collected from real plant. The model possesses the strong capability of fitting and generalization. Experiments show that the dynamic epsiv-SVM is superior to the standard SVM modeling method. MOGA is very feasible and efficient too
On the basis of the standard SVM for regression, the dynamic Ε-SVM method was proposed to establish precise mathematical models to describe the behavior of biochemistry systems, namely each training sample used diffe...
详细信息
On the basis of the standard SVM for regression, the dynamic Ε-SVM method was proposed to establish precise mathematical models to describe the behavior of biochemistry systems, namely each training sample used different error. At the same time, an improved multi-objective Genetic Algorithm (MOGA) was used to automatically select the dynamic Ε-SVM parameters. A new modeling method that combined improved MOGA with dynamic Ε-SVM regression was presented. The model for titer pre-estimate was developed in Matlab6.5 with data collected from real plant. The model possessed the strong capability of fitting and generalization. It is shown that the method achieves significant improvement in the generalization performance in comparison with the modeling method based on MOGA and the standard SVM.
暂无评论