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IEEE International Symposium on Industrial Electronics (ISIE)

作者： Paulo Leitão Joel Alves J. Marco Mendes Armando W. Colombo Artificial Intelligence and Computer Science Laboratory Porto Portugal Polytechnic Institute of Bragança Braganca Portugal Faculty of Engineering University of Porta Porto Portugal Schneider Electric Automation GmbH Seligenstadt Germany

This paper introduces an approach to decision support systems in service-oriented automation control systems, which considers the knowledge extracted from the Petri nets models used to describe and execute the process behavior. Such solution optimizes the decision-making taking into account multi-criteria, namely productive parameters and also energy parameters. In fact, being manufacturing processes typically energy-intensive, this allows contributing for a clean and saving environment (i.e. a better and efficient use of energy). The preliminary experimental results, using a real laboratorial case study, demonstrate the applicability of the knowledge extracted from the Petri nets models to support real-time decision-making systems in service-oriented automation systems, considering some energy efficiency criteria.

关键词： Petri nets Workstations Energy consumption Decision making automation Decision support systems Monitoring

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Composition of Petri nets models in serviceoriented industrial automation

Composition of Petri nets models in serviceoriented industri...

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8th IEEE International Conference on Industrial Informatics, INDIN 2010

作者： Mendes, J. Marco Leitão, Paulo Restivo, Francisco Colombo, Armando W. Faculty of Engineering University of Porto Rua Dr. Roberto Frias 4200-465 Porto Portugal Polytechnic Institute of Bragança Quinta Sta Apolónia Apartado 134 5301-857 Bragança Portugal Schneider Electric Automation GmbH Steinheimer Str. 117 D-63500 Seligenstadt Germany LIACC - Artificial Intelligence and Computer Science Laboratory University of Porto Portugal

ISBN: (纸本)9781424473007

In service-oriented systems, composition of services is required to build new, distributed and more complex services, based on the logic behavior of individual ones. This paper discusses the formal composition of Petri nets models used for the process description and control in service-oriented automation systems. The proposed approach considers two forms for the composition of services, notably the offline composition, applied during the design phase, and the online composition, related to the synchronization of Petri nets models on the fly. An experimental case study is used to illustrate the proposed composition approach. © 2010 IEEE.

关键词： Petri nets

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Process optimization of service-oriented automation devices based on Petri nets

Process optimization of service-oriented automation devices ...

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8th IEEE International Conference on Industrial Informatics, INDIN 2010

作者： Mendes, J. Marco Leitão, Paulo Restivo, Francisco Colombo, Armando W. University of Porto Faculty of Engineering Rua Dr. Roberto Frias 4200-465 Porto Portugal Polytechnic Institute of Bragança Quinta Sta Apolónia Apartado 134 5301-857 Bragança Portugal Schneider Electric Automation GmbH Steinheimer Str. 117 D-63500 Seligenstadt Germany LIACC Artificial Intelligence and Computer Science Laboratory University of Porto Portugal

ISBN: (纸本)9781424473007

This paper introduces a novel method for the specification and selection of criteria-weighted operation modes for the orchestration of services in industrial automation using Petri nets. The objective is to provide to the internal decision support system of a service-oriented automation device or of another applicable computational system the capability to select the best path in a Petri net orchestration model considering different criteria to evaluate the quality of services, such as the time, energy efficiency and reliability. The transition-invariants obtained from the Petri net represent the set of possible modi operandi and these are then weighted with decision criteria. The result will be afterwards evaluated in order to select the optimal modus operandi to be executed by the device. Based on the experiments, this method permits the dynamic optimization of processes in real-time, considering available parameters from devices and other resources. © 2010 IEEE.

关键词： Petri nets

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Scheduling jobs and preventive maintenance on fuzzy job shop using genetic algorithm

Scheduling jobs and preventive maintenance on fuzzy job shop...

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International Conference on Machine Learning and Cybernetics (ICMLC)

作者： You-Lian Zheng Yuan-Xiang Li De-Ming Lei The State Key Laboratory of Software Engineering Wuhan University of China Wuhan China Faculty of Mathematics & Computer Science Hubei University Wuhan China School of Automation Wuhan University of Technology Wuhan China

Preventive maintenance (PM) has been considered on many scheduling problems, however, the problem of scheduling jobs and PM on fuzzy job shop are seldom investigated. This paper presents a random key genetic algorithm (RKGA) for the problem with resumable jobs and PM in the fixed time intervals. RKGA uses a novel random key representation, a new decoding strategy incorporating maintenance operation, and discrete crossover. RKGA is applied to some instances to minimize the maximum fuzzy completion time. Computational results show the optimization ability of RKGA on fuzzy scheduling with PM.

关键词： Maintenance engineering Job shop scheduling Decoding Biological cells Machine learning Processor scheduling Cybernetics

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Scheduling fuzzy job shop using random key genetic algorithm

Scheduling fuzzy job shop using random key genetic algorithm

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International Conference on Machine Learning and Cybernetics (ICMLC)

作者： You-Lian Zheng Yuan-Xiang Li De-Ming Lei Chuan-Xiang Ma The State Key Laboratory of Software Engineering Wuhan University of China Wuhan China Faculty of Mathematics & Computer Science Hubei University Wuhan China School of Automation Wuhan University of Technology Wuhan China

Genetic algorithm has been successfully applied to fuzzy job shop scheduling problem, however, the coding and decoding strategies of the problem aren't fully investigated. This paper presents an efficient random key genetic algorithm (RKGA) for the problem to minimize the maximum fuzzy completion time. RKGA uses a novel random key representation, a new decoding strategy and discrete crossover. RKGA is applied to some fuzzy scheduling instances and compared with a genetic algorithm and particle swarm optimization with genetic operators. Computational results demonstrate that RKGA has the promising advantage on fuzzy scheduling.

关键词： Job shop scheduling Schedules Biological cells Genetics Decoding Machine learning Cybernetics

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Calculation of unbalanced magnetic pull in a salient-pole synchronous generator

Calculation of unbalanced magnetic pull in a salient-pole sy...

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International (EPE-PEMC) Power Electronics and Motion Control Conference

作者： Damir Žarko Drago Ban Ivan Vazdar Vladimir Jarić Department of Electric Machines Drives and Automation Faculty of Electrical and Computer Engineering Zagreb Croatia KONČAR Generators and Motors Inc. Zagreb Croatia Marketing d.o.o Zagreb Croatia

The unbalanced magnetic forces which act upon the rotor of a salient-pole synchronous generator due to eccentric motion of the rotor shaft in the presence of magnetic field originating from the field current in no-load operation have been calculated using finite-element method. The displacement of the rotor has been modeled using the actual shaft orbit recorded on a 5 MVA salient-pole generator driven by a gas turbine in a cogeneration plant. The results indicate that a variation of unbalanced forces in no-load operation at rated voltage occurs at the precession frequency of 25 Hz with maximum force of 2.32 kN.

关键词： Shafts Orbits Rotors Vibrations Extraterrestrial measurements Stator windings

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Composition of Petri nets models in service-oriented industrial automation

Composition of Petri nets models in service-oriented industr...

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IEEE International Conference on Industrial Informatics (INDIN)

作者： J. Marco Mendes Paulo Leitão Francisco Restivo Armando W. Colombo Faculty of Engineering University of Porto Porto Portugal LIACC - Artificial Intelligence and Computer Science Laboratory University of Porto Portugal Polytechnic Institute of Bragança Bragança Portugal Schneider Electric Automation GmbH Seligenstadt Germany

关键词： Petri nets automation Service oriented architecture Automatic control Power system modeling Application software Logic devices computer industry Artificial intelligence computer science

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New smooth space G for image denoising

New smooth space G for image denoising

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Congress on Image and Signal Processing, CISP

作者： Qiao-nong Wen Sui-ren Wan Zeng-li Liu Shuang Xu Medical Electronics Laboratory South-East University Nanjing China Faculty of Information Engineering and Automation Kunming University of Science and Technology Kunming China School of Computer Science and Technology South-East University Nanjing China

The noise image is decomposed into the unknown true image u and the noise v by a new image de-noising method based on image decomposition. The common decomposition models are all dense and can only be transformed into high-order partial differential equations to solve, which are heavy computations. DT model and the Jiang model are sparse image decomposition models. A new image de-noising model based on the above two models is put forward in this paper. This new model is sparse which is defined in the new smooth space G β p, q (smooth Besov space embedding) variational functional. The variational functional can be solved by second-generation Curvelet contraction threshold. Experimental results show that de-noising effect is better of the proposed model than these common models.

关键词： Mathematical model Noise Transforms Computational modeling Noise reduction Image denoising Image decomposition

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Backtrack and Restart Genetic Algorithm to Optimize Delivery Schedule

Backtrack and Restart Genetic Algorithm to Optimize Delivery...

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International IEEE Conference on Signal-Image Technologies and Internet-Based System

作者： Yoshitaka Sakurai Kouhei Takada Natsuki Tsukamoto Takashi Onoyama Rainer Knauf Setsuo Tsuruta School of Information Environment Tokyo Denki University Chiba Japan Research & Development Department Hitachi Software Engineering Company Limited Tokyo Japan Faculty of Computer Science and Automation Ilmenau University of Technology Ilmenau Germany

A delivery route optimization system greatly improves the real time delivery efficiency. To realize such an optimization, its distribution network requires solving several tens to hundreds (max. 1500-2000) cities Traveling Salesman Problems (TSP) within interactive response time (around 3 seconds) with expert-level accuracy (below 3% level of error rate). To meet these requirements, a Backtrack and Restart Genetic Algorithm (Br-GA) is proposed and compared with conventional ones, especially such as an Inner Random Restart Genetic Algorithm (Irr-GA). This method combines Backtracking and GA having simple heuristics such as 2-opt and NI (Nearest Insertion) so that, in case of stagflation, GA can restarts with the state of populations going back to the state in the generation before stagflation. Including these heuristics, field experts and field engineers can easily understand the way and use it. Using the tool applying their method, they can easily create/modify the solutions or conditions interactively depending on their field needs. Experimental results proved that the method meets the above-mentioned delivery scheduling requirements more than other methods from the viewpoint of optimality as well as simplicity. Especially as to optimality, Br-GA is superior to even Irr-GA.

关键词： Nickel Gallium Optimization Pediatrics Humans Cities and towns Real time systems

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Multi-agent system for customer relationship management with SVMs tool

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International Journal of Intelligent Information and Database Systems 2010年第2期4卷 121-136页

作者： Xiao, Yanshan Liu, Bo Luo, Dan Cao, Longbing Deng, Feiqi Hao, Zhifeng Faculty of Information Technology University of Technology Sydney PO Box 123 Broadway NSW 2007 Australia College of Automation Science and Engineering South China University of Technology Guangzhou 510640 China College of Computer Science GuangDong University of Technology Guangzhou China

In this paper, we introduce multiple agents, knowledge discovery and data mining into customer relationship management (CRM) to set up the architecture of a multi-agent-based CRM system (MAB-CRM), and then use the SVMs-based approach to build up the decision support model which can classify the patterns obtained by the multiple agents into several decision levels, so that managers can pursue different decision-making activities according to the decision level of a pattern. Substantial experiments in the two-dimensional space show how the SVMs-based approach works. The practical problem from one Chinese company has been resolved by the SVMs-based approach. The results illustrate that this approach has an effective ability to learn the decision rules from the assessors' experience. Copyright © 2010 Inderscience Enterprises Ltd.

关键词： Support vector machines

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