Optimizing operation parameters for Texaco coal-water slurry gasifier with the consideration of multiple objectives is a complicated nonlinear constrained problem concerning 3 BP neural networks. In this paper, multio...
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In recent years, smart manufactur-ing has been the focus of competitionand collaboration between countriesaround the world. The major developedand developing countries are speedingup their strategic planning and layou...
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In recent years, smart manufactur-ing has been the focus of competitionand collaboration between countriesaround the world. The major developedand developing countries are speedingup their strategic planning and layoutfor smart manufacturing. Germany, theUnited States, and China have releasedthe Industry 4.0, Smart Process Man-ufacturing, and Made in China 2025initiatives, respectively, which aim ata deep integration of information andcommunication technology and man-ufacturing technology, thus achieving seamless integration of prod-ucts, equipment, humans, and organizations.
Specific index-related process monitoring covers a wide range of requirements from industrial production. At present, it is still a challenge to divide into the specific index-related information and the specific inde...
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Specific index-related process monitoring covers a wide range of requirements from industrial production. At present, it is still a challenge to divide into the specific index-related information and the specific index-unrelated information more accurately. In this paper, a two-step information extraction method is presented to solve this problem. In the first step, the overall process variables are separated into a strongly related variable set and a weakly related variable set. In the second step, the two sets are further divided into a specific index-related subset and a specific index-unrelated subset, respectively. Two specific index-related subsets form a new subspace related to the specific index. Two specific index-unrelated subsets are combined into a specific index-unrelated subspace. Two 2 T statistics are built in the specific index-related subspace and the specific index-unrelated subspace, respectively. Finally, the proposed method is applied for Tennessee Eastman(TE). The results indicate the effectiveness of the proposed method.
Terephthalic acid is a raw material for polyester and textile industry. However, the by-product 4-Carboxybenzaldehyde in TA is harmful to the polymer process since it can lower the polymerization rate and the average ...
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Production scheduling is an important aspect of batch process operations to achieve high productivity and operability. In this paper, we considered a zero-wait multiproduct scheduling with due dates under uncertainty,...
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We present a universally applicable hybrid modeling method for nonlinear industrial processes that combine the a priori process knowledge with a data-driven *** method constructs a unified framework for the modeling p...
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We present a universally applicable hybrid modeling method for nonlinear industrial processes that combine the a priori process knowledge with a data-driven *** method constructs a unified framework for the modeling process by integrating a data-driven modeling technique,sampling detection technique,constraint optimization problem,and an evolutionary *** the modeling process,a swarm intelligence algorithm is used to optimize the model parameters under the circumstances of satisfying the constraints of a priori *** adding the constraints of process a priori knowledge,we can obtain more information about the actual process and avoid the over-fitting problem to some extent,especially when modeling a system with a small quantity of *** order to show the effectiveness of the method proposed in this paper,two general data-driven models,the polynomial regression model and radial basis function network model,are used as case ***,a function simulation experiment is designed to test effectiveness,and applied to estimate average particle size of ZrO2-TiO2 composite colloidal sols.
This paper studies semi-global containment control problem for a multi-agent system. Each follower agent in the system is described by a general linear system in the presence of both actuator position and rate saturat...
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This paper studies semi-global containment control problem for a multi-agent system. Each follower agent in the system is described by a general linear system in the presence of both actuator position and rate saturation. A linear state feedback containment control law is constructed for each follower agent by using low gain approach such that the states of all follower agents will converge to the convex hull formed by the leader agents asymptotically when the communication topology among follower agents is a connected undirect graph and each leader agent is a neighbor of at least one follower agent. Simulation results illustrate the theoretical results.
This paper studies semi-global output consensus problem for multi-agent systems. The dynamics of each follower agent is described by a linear system subject to both actuator saturation and external disturbances. The d...
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This paper studies semi-global output consensus problem for multi-agent systems. The dynamics of each follower agent is described by a linear system subject to both actuator saturation and external disturbances. The dynamics of leader agent is also described by a linear system which generate both the tracking signal and disturbance as the exosystem does in output regulation problem for individual system. Solvability conditions are established based on the agent dynamics and the communication topology. For the follower agents, low-and-high gain based linear state feedback control laws are constructed such that all the outputs of agents achieve output consensus when the communication topology among the follower agents is a connected undirected graph, and the leader is a neighbor of at least one follower. Simulation results are given to illustrate the theoretical results.
Sleep staging is an effective method for diagnosing sleep disorder and monitoring sleep quality. With the rapid development of machine learning technology, the automatic staging methods of sleep gradually replace the ...
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ISBN:
(数字)9781728180229
ISBN:
(纸本)9781728180236
Sleep staging is an effective method for diagnosing sleep disorder and monitoring sleep quality. With the rapid development of machine learning technology, the automatic staging methods of sleep gradually replace the traditional manual interpretation which can improve the efficiency on sleep staging for medical research. LSTM networks can save the historical information as a reference for the current moment, which is undoubtedly a good way to improve sleep staging performance. In this paper, a convolutional neural network (CNN) is constructed to extract the features from a single-channel EEG. The Uni-directional Long Short-Term Memory (Uni-LSTM) network and Bi-directional Long Short-Term Memory (Bi-LSTM) network are combined with CNN to realize automatic sleep staging. The obtained results showed that the two presented network frameworks are effective and feasible on sleep staging. The Bi-LSTM which has more enriched sequence information got better classification performance than the Uni-LSTM.
Intelligent procedure expert system was developed to select appropriate GTAW procedure in this ***,the function design and implementation methods of the welding procedure expert system were *** expert system can prese...
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Intelligent procedure expert system was developed to select appropriate GTAW procedure in this ***,the function design and implementation methods of the welding procedure expert system were *** expert system can present the welding procedure card,multimedia display of welding process,and output function to makes the data sharing more ***,the database design of the welding procedure expert system based on C/S mode was presented where the expert knowledge was *** last,the neural network model was established to realize procedure selection based on the neural network learning ability and the welding case from the *** the BPNN model,the welding parameters can be obtained based on the input welding conditions.
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