A previous study conducted in Anhui Province by collecting data from 56 county-level governments in 2009 has shown that the factors of demographic, financial and geographical area have linear relationship with governm...
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In this paper, a novel second-order integral sliding mode control (SOSMC) algorithm is proposed to accomplish velocity control of the permanent-magnet synchronous motor (PMSM) so that the performance can be improved. ...
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Fuzzy c-means(FCM) algorithm is an important clustering method in pattern recognition, while the fuzziness parameter, m, in FCM algorithm is a key parameter that can significantly affect the result of clustering. Clus...
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Fuzzy c-means(FCM) algorithm is an important clustering method in pattern recognition, while the fuzziness parameter, m, in FCM algorithm is a key parameter that can significantly affect the result of clustering. Cluster validity index(CVI) is a kind of criterion function to validate the clustering results, thereby determining the optimal cluster number of a data set. From the perspective of cluster validation, we propose a novel method to select the optimal value of m in FCM, and four well-known CVIs, namely XB, VK, VT, and SC, for fuzzy clustering are used. In this method, the optimal value of m is determined when CVIs reach their minimum values. Experimental results on four synthetic data sets and four real data sets have demonstrated that the range of m is [2, 3.5] and the optimal interval is [2.5, 3].
This paper investigates the predictive control synthesis problem for constrained feedback control systems with both missing data and quantization. By introducing a missing data compensation strategy and an augmented M...
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Moving window local outlier probability(MWLo OP)is an outlier detecting method which was proposed for monitoring time-varying industrial processes;however,for the practical industrial processes,besides the time-varyin...
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Moving window local outlier probability(MWLo OP)is an outlier detecting method which was proposed for monitoring time-varying industrial processes;however,for the practical industrial processes,besides the time-varying characters caused by deactivation of catalyst,measuring instrument drifting and so on,the operation mode is often switched as the adjusting of the feedstock,changes in market demands and so *** the WMLo OP algorithm can deal with the time-varying process data,the multi-mode process data will lead to a mass of fault *** solve this problem,an external analysis moving window local outlier probability(EA-MWLo OP)algorithm is proposed in this *** external analysis is employed to eliminate the influence of operation mode change on the process data,then the MWLo OP method can deal with complex distribution time-varying data,and give an outlier ***,the corresponding statistic and control limit are constructed to detect the process *** addition,while the monitoring model updated,the control limit is not necessary to *** performance of this method is evaluated through a case study of a non-isothermal continuous stirred tank reactor(CSTR).
Inspired by the fact that in most existing swarm models of multi-agent systems the velocity of an agent can be infinite, which is not in accordance with the real applications, we propose a novel swarm model of multi-a...
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Inspired by the fact that in most existing swarm models of multi-agent systems the velocity of an agent can be infinite, which is not in accordance with the real applications, we propose a novel swarm model of multi-agent systems where the velocity of an agent is finite. The Lyapunov function method and LaSalle's invariance principle are employed to show that by using the proposed model all of the agents eventually enter into a bounded region around the swarm center and finally tend to a stationary state. Numerical simulations are provided to demonstrate the effectiveness of the theoretical results.
To implement self-adaptive control parameters, a hybrid differential evolution algorithm integrated with particle swarm optimization (PSODE) is proposed. In the PSODE, control parameters are encoded to be a symbioti...
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To implement self-adaptive control parameters, a hybrid differential evolution algorithm integrated with particle swarm optimization (PSODE) is proposed. In the PSODE, control parameters are encoded to be a symbiotic individual of original individual, and each original individual has its own symbiotic individual. Differential evolution ( DE) operators are used to evolve the original population. And, particle swarm optimization (PSO) is applied to co-evolving the symbiotic population. Thus, with the evolution of the original population in PSODE, the symbiotic population is dynamically and self-adaptively adjusted and the realtime optimum control parameters are obtained. The proposed algorithm is compared with some DE variants on nine functious. The results show that the average performance of PSODE is the best.
Near-infrared( NIR) spectroscopy has been widely employed as a process analytical tool( PAT) in various fields; the most important reason for the use of this method is its ability to record spectra in real time to cap...
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Near-infrared( NIR) spectroscopy has been widely employed as a process analytical tool( PAT) in various fields; the most important reason for the use of this method is its ability to record spectra in real time to capture process properties. In quantitative online applications,the robustness of the established NIR model is often deteriorated by process condition variations,nonlinear of the properties or the high-dimensional of the NIR data set. To cope with such situation,a novel method based on principal component analysis( PCA) and artificial neural network( ANN) is proposed and a new sample-selection method is mentioned. The advantage of the presented approach is that it can select proper calibration samples and establish robust model effectively. The performance of the method was tested on a spectroscopic data set from a refinery process. Compared with traditional partial leastsquares( PLS),principal component regression( PCR) and several other modeling methods, the proposed approach was found to achieve good accuracy in the prediction of gasoline properties. An application of the proposed method is also reported.
This paper investigates the formation problem of an array of large multi-agent systems. A new framework for the dynamic of mobile agents as a continuum is proposed and the communication topology of agents is a chain g...
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This paper investigates the formation problem of an array of large multi-agent systems. A new framework for the dynamic of mobile agents as a continuum is proposed and the communication topology of agents is a chain graph and fixed. Leader feedback laws which designed in a manner to the boundary control of distributed parameter multi-agent system allow the mobile agents stable achieve the formation. By referring to Lyapunov functional method and employing boundary control techniques, a new protocol is established to deal with formation problem for the distributed parameter multi-agent system. Finally, a numerical example is given to illustrate the usefulness of the results.
With the rapid development of computer technology,software engineering disciplines has developed rapidly not only in the aspect of theory,but is increasingly important in the practical application,and gradually formed...
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With the rapid development of computer technology,software engineering disciplines has developed rapidly not only in the aspect of theory,but is increasingly important in the practical application,and gradually formed methodologies,tools and management of three *** these three factors,the study of software project management is relatively backward,and even become a major obstacle in the development of software engineering ***,in view of software engineering discipline facing the problem,this paper proposed dynamic programming algorithm should be applied to software engineering management.
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