Turbine steam flow is an important parameter for analyzing turbine operating efficiency. In order to solve such problems as lack of detection information, poor reliability of traditional measurement method, high cost ...
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Automatic EEG spike detection provide valuable information for diagnosis of epilepsy. In the past 30 years, a number of algorithms were proposed. However, the basic idea of most algorithms is to identify spike activit...
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With the information technology applied widely to process industry, a large amount of historical data which could be used for obtaining the prior probabilities of gross error occurrence is stored in database. To use t...
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With the information technology applied widely to process industry, a large amount of historical data which could be used for obtaining the prior probabilities of gross error occurrence is stored in database. To use the historical data to enhance the efficiency of gross error detection and data reconciliation, a new strategy which includes two steps is proposed. The first step is that mixed integer program technique is incorporated to use the prior information to detect gross errors. The second step is to estimate all detected gross errors and adjust process data with material, energy, and other balance constrains. In this step an improved method is proposed to achieve the same effect with traditional method through adjusting the covariance matrix. Novel prior information criteria are described and performance of this new strategy is compared and discussed by applying the strategy for a challenging test problem.
An evolutionary algorithm based on the parallel evolution of multiple single objective populations and Pareto archive population is proposed, which is not only suitable for solving multi-objective optimization, but al...
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In ethylene plant, charge gas compressor is one of the most important units. The charge gas compressor usually is a centrifugal compressor. The information of centrifugal compressors’ performance is not applicable to...
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In ethylene plant, charge gas compressor is one of the most important units. The charge gas compressor usually is a centrifugal compressor. The information of centrifugal compressors’ performance is not applicable to all of the conditions, which restricts the operation optimization of the compressor. To solve this problem, a tri-layer BP neural network was introduced to model the performance of compressor by using the data provided by manufacturers. The input data of the model in other conditions should be corrected according to the similar theory. At last, the method was used to optimize the system of charge gas compressor by embedding compressor performance model into the ASPEN PLUS model of compressor. The result shows that it is an effective method to optimize the compressor system.
Color night vision can map natural colors to nighttime images of multiple bands (e.g., visible and long-wave infrared (LWIR)). These colors can assist the observers in better and faster understanding images, thus impr...
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In this paper,the synchronization of a nonlinear network with time-varying coupling delay is investigated via distributed impulsive *** objective is to design the distributed impulsive controller with minimum coupling...
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ISBN:
(纸本)9781479900305
In this paper,the synchronization of a nonlinear network with time-varying coupling delay is investigated via distributed impulsive *** objective is to design the distributed impulsive controller with minimum coupling strength such that the nonlinear network with coupling delay is globally exponentially *** sufficient conditions have been derived based on Lyapunov-Razumikhin method in terms of matrix *** example is presented to illustrate the effectiveness of the proposed control methods.
In this paper, an improved hybrid particle swarm optimization (IHPSO) method, which is able to handle the equality constraints efficiently, has been proposed to determine the optimal recipe offline for the gasoline bl...
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In this paper, an improved hybrid particle swarm optimization (IHPSO) method, which is able to handle the equality constraints efficiently, has been proposed to determine the optimal recipe offline for the gasoline blending process. In addition, the proposed method has been applied onsite in a gasoline production line in Nanjing, China. The results show that the optimized recipes are able to improve the first-time success rate for the blending process and decrease the quality giveaways and blending cost significantly.
This study addresses the stability and stabilization problems of discrete-time semi-Markov jump linear systems(S-MJLSs) with unavailable sojourn-time information. The sojourn-time probability mass functions(S-TPMFs) o...
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This study addresses the stability and stabilization problems of discrete-time semi-Markov jump linear systems(S-MJLSs) with unavailable sojourn-time information. The sojourn-time probability mass functions(S-TPMFs) of discrete-time semi-Markov chains are no longer confined to the geometric distribution, and it is difficult to obtain accurate and comprehensive information for S-TPMFs in practice. This is because S-TPMFs are usually deduced from the statistical characteristics according to the sampled-data, while adequate samples are often costly and time consuming. In this study, when the S-TPMFs for semi-Markov chains are assumed to be unavailable, the σ-error mean square stability is investigated for discrete-time S-MJLSs with some widely used assumptions; for semi-Markov chains, only the transition probability matrix of the embedded chain is used. In addition, the existence conditions of the effective controller are provided for closed-loop systems without using the information of S-TPMFs. Numerical examples are presented to illustrate the validity of the obtained theoretical results.
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