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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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 act...
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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 activities. We have developed an algorithm based on identify non-spike activities for off-line analysis. In this paper, we improved the algorithm for online application using real-time template. Template method is a typical spike detection method. It was not widely employed because of the difficulty of making template. Our results suggested that multichannel template is meaningful and effective for real-time detection. Spike activities can be detected with a delay of about 2 s. We also designed an simple user-friendly monitor interface for monitor and review spike events in real-time.
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.
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.
In order to overcome the drawbacks of fuzzy kernel clustering method (FKCM) give the clustering number in advance, sensitive to the initial cluster centers and easy to be trapped into local optimum, the adaptive algor...
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Gasoline blending is a critical process in petroleum refineries. Real-time optimization(RTO) techniques have been popular with the applications for the blending process for optimization purpose. However the dependency...
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Gasoline blending is a critical process in petroleum refineries. Real-time optimization(RTO) techniques have been popular with the applications for the blending process for optimization purpose. However the dependency of RTO on the measurement of the component impairs its applicability. Therefore how to utilize the blending model and the product measurement to free RTO from the component measurement is the major research topic in this paper. Unscented Kalman Filter, due to its ability to estimate the parameter for nonlinear model, is chosen to estimate component properties based on the product measurement. The RTO strategy is then proposed with the UKF method for the recipe calculation periodically. Furthermore, the proposed RTO is tested with the gasoline blending benchmark problem, while the results are compared with the ideal blending case. The accuracy of the component estimation and the efficiency of the RTO are verified with the results.
In this paper, the vigilance levels during day time short nap sleep were estimated on the basis of Markov Process Amplitude (MPA) EEG model. The ultimate purpose was to adopt the MPA model to discriminate three le...
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In this paper, the vigilance levels during day time short nap sleep were estimated on the basis of Markov Process Amplitude (MPA) EEG model. The ultimate purpose was to adopt the MPA model to discriminate three levels of vigilance through a simple neural network. A set of parameters were firstly calculated based on MPA EEG model. Secondly, correlation analysis was adopted to extract effective parameters to ensure a small amount of inputs of the artificial neural network. The outputs of artificial neural network were the classified three levels: wakeful, drowsy and sleep. The obtained estimation result showed that the accuracy of wakeful was about 90.0%, drowsy 80.0%, and sleep 93.3%.
Focusing on ethylene oxide (EO) hydration reactor industrial equipment, the reaction mechanism model is established. Based on the principle of material balance, energy balance and kinetics of the reactions of ethylene...
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Focusing on ethylene oxide (EO) hydration reactor industrial equipment, the reaction mechanism model is established. Based on the principle of material balance, energy balance and kinetics of the reactions of ethylene oxide with water, partial least squares regression (PLSR) was used in the model to establish a corresponding relationship between the reaction rate constant and the reaction temperature. With kinetic parameters correction by using field data, the results are more tallies with the actual operation. Influences of water/EO molar ratio and inlet temperature on product quality, outlet temperature and energy consumption are analyzed according to the established model. The results showed that the model can preferably reflect the performance of EO hydration reactor and have certain guidance functions to the further advancedcontrol strategies.
Independent component analysis (ICA) and fuzzy c-means (FCM) clustering were adopted for automatic ocular artifact suppression from operator's electroencephalogram. Firstly, ICA was applied to the 20s data contain...
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Independent component analysis (ICA) and fuzzy c-means (FCM) clustering were adopted for automatic ocular artifact suppression from operator's electroencephalogram. Firstly, ICA was applied to the 20s data containing nine channels of EEG data and one of electrooculagram (EOG) data. Secondly, each 20s independent component (IC) was partitioned into ten 2 s epochs. And five features of each epoch were calculated, which are wavelet entropy, power in the band between 0 and 5 Hz, kurtosis, mutual information and correlation. Thirdly, the epochs were classified as either EEG or ocular artifact based on the result of FCM clustering. And then components which were recognized as ocular artifact were rejected. Clean EEG was obtained. The result shows that the method based on ICA and FCM can be applied to online automatic ocular artifact suppression from EEG.
This paper investigates the problem of stabilizing predictive control for constrained systems with quantization and communication delays. Based on the quantization matrix, the input-saturated control systems with loga...
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