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.
In this paper, high-density polyethylene (HDPE) films were prepared by three kinds of annealing methods which were different in cooling speed. The crystallinity of those HDPE samples were measured and compared. A high...
详细信息
In this paper, high-density polyethylene (HDPE) films were prepared by three kinds of annealing methods which were different in cooling speed. The crystallinity of those HDPE samples were measured and compared. A high DC voltage was applied to the samples and the space charge formed was measured. Homo-charges were found in samples that were applied with a negative high voltage. The space charge properties were discussed, based on crystallinity. From these results, it is found that the space charge formed in samples cooled at high speed is more than that of the samples cooled at normal and low speed.
This paper mainly studies stability and optimal control for networked controlsystems with the real-time setup of time-driven sensor, event-driven controller and actuator, and with the assumption that network-induced ...
详细信息
ISBN:
(纸本)0780382730
This paper mainly studies stability and optimal control for networked controlsystems with the real-time setup of time-driven sensor, event-driven controller and actuator, and with the assumption that network-induced delay is no longer than certain known times of sampling period. The modeling of this class of networked controlsystems is given. Then, preliminary stochastic stability analysis of it is presented. Finally, based on stochastic optimal control theory an LQG control scheme is provided. Much work needs to be continued for future research.
This paper presents a new technique for software pipelining using the Petri nets. Our technique called the Petri Net Pacemaker (PNP) can create near optimal pipelines with less algorithmic effort than other techniques...
详细信息
ISBN:
(纸本)9780818652806
This paper presents a new technique for software pipelining using the Petri nets. Our technique called the Petri Net Pacemaker (PNP) can create near optimal pipelines with less algorithmic effort than other techniques. The pacemaker is a novel idea which exploits the behavior of Petri nets to model the problem of scheduling operations of a loop body for software pipelining.< >
暂无评论