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Discrete variable structure control based on optimization by cultural differential evolution approach

Discrete variable structure control based on optimization by...

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2006 ASME International mechanical engineering Congress and Exposition, IMECE2006

作者： Dos Santos Coelho, Leandro Mariani, Viviana Cocco Pontifical Catholic University of Parana Production and Systems Engineering Graduate Program PPGEPS / CCET/ PUCPR Imaculada Conceicao 1155 80215-901 Curitiba Parana Brazil Pontifical Catholic University of Parana Mechanical Engineering Graduate Program PPGEM / CCET/ PUCPR Imaculada Conceicao 1155 80215-901 Curitiba Parana Brazil

ISBN: (纸本)0791837904

Advanced conceptions to design industrial control systems are, in general, dependent of mathematical models of the controlled process. Also, the task of the controllers is to achieve an optimum performance when facing with various types of disturbances that are, sometimes, unknown in practical applications. An advanced methodology for control design is the variable structure control (VSC) with sliding mode. This paper considers the non-linear control of industrial processes based on self-tuning discrete VSC technique. A novel and systematic VSC design methodology is proposed, which integrates an estimator based on recursive least square algorithm, a discrete quasi-sliding surface and a optimization method. Contrary to the trial and error selection of the variable structure feedback gains reported in the literature, the selection in present work is done using differential evolution (DE) optimization, an evolutionary computation technique, with a new operator based on normative knowledge of cultural algorithms. The proposed design has been applied to a control valve described by a non-linear Wiener model. Numerical simulation results reveal that the new DE approach is applicable and promising for the VSC design. Copyright © 2006 by ASME.

关键词： Optimal control systems

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mechanical design using quantum-behaved particle swarm optimizer with exponential mutation operator

Mechanical design using quantum-behaved particle swarm optim...

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2006 ASME International mechanical engineering Congress and Exposition, IMECE2006

作者： Dos Santos Coelho, Leandro Marian, Viviana Cocco Production and Systems Engineering Graduate Program PPGEPS / CCET / PUCPR Pontifical Catholic University of Parana Imaculada Conceicao 1155 80215-901 Curitiba Parana Brazil Mechanical Engineering Graduate Program PPGEM / CCET/ PUCPR Pontifical Catholic University of Parana Imaculada Conceicao 1155 80215-901 Curitiba Parana Brazil

ISBN: (纸本)0791837904

Particle swarm optimization (PSO) is a population-based swarm intelligence algorithm that shares many similarities with evolutionary computation techniques. However, the PSO is driven by the simulation of a social psychological metaphor motivated by collective behaviours of bird and other social organisms instead of the survival of the fittest individual. Inspired by the classical PSO method and quantum mechanics theories, this work presents new Quantum-behaved PSO (QPSO) approaches using mutation operator with exponential probability distribution. The simulation results demonstrate good performance of the QPSO in solving a well-studied continuous optimization problem of mechanical engineering design. Copyright © 2006 by ASME.

关键词： Quantum theory

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Reduction in the environmental impacts caused by the alumina production procces through the use of neural networks 22

Reduction in the environmental impacts caused by the alumina...

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22nd International Conference on Production Research, ICPR 2013

作者： Da Silva, Ruy Gomes Steiner, Maria Teresinha Arns Pontifical Catholic University of Paraná Graduate Program in Industrial and Systems Engineering Rua Imaculada Conceição 1155 Prado Velho Curitiba ParanáCEP: 80.215-901 Brazil

This work's goal is to recognize variable patterns in a process that will serve as basis for the creation of a mathematic model capable of predicting the results for caustic contents in the reject from the alumina production process, denominated Red Mud, making it possible to simulate the best combination among entry variables. By that, the reuse of red mud in civil construction industry is intended, minimizing environmental impacts generated by the excess of red mud discarded in the environment by the mentioned process. This work will perform tests with a historical registers database of entry and exit variables for the process's stage that makes this washing. For the creation of the model, the data will be submitted to an Artificial Neural Network for the training of such patterns that should generate predictions with a low error percentage when compared to the simulated data obtained in laboratories.

关键词： Forecasting

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Power demand forecast using least-squares support vector machines

Power demand forecast using least-squares support vector mac...

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2009 15th International Conference on Intelligent System Applications to Power systems, ISAP '09

作者： Dos Santos Coelho, Leandro Klein, Carlos Eduardo PUC-PR Industrial and Systems Engineering Graduate Program Pontifical Catholic University of Paraná Imaculada Conceição 1155 Zip code 80215-901 Curitiba Paraná Brazil

ISBN: (纸本)9781424450985

This paper aims to share the results on forecasting power demand using least-squares support vector machines. The development is based on model estimation taking in consideration the past measurements for power demand and ambient temperature. All approximated models were evaluated using the multiple correlation coefficient (R2) or mean absolute percentage error (MAPE) and maximum error combined as quality parameters. © 2009 IEEE.

关键词： Support vector machines

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Swim velocity profile identification by using a modified differential evolution method associated with RBF Neural Network

Swim velocity profile identification by using a modified dif...

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2013 3rd International Conference on Innovative Computing Technology, INTECH 2013

作者： Santos Coelho, Leandro Dos Da Cruz, Luciano Ferreira Freire, Roberto Zanetti Pontifical Catholic University of Parana - PUCPR Industrial and Systems Engineering Graduate Program - PPGEPS Curitiba PR Brazil Federal University of Parana - UFPR Department of Electrical Engineering - DEE/PPGEE Curitiba PR Brazil

ISBN: (纸本)9781479900473

High level sports require a steady intensification of training in order to raise the athletes' performance. With the purpose of support swimmers and coaches new biomechanical analysis are been performed, becoming one of the most studied areas in swimming. By using technology resources, Esignificant results related to performance improvements are being achieved. Specific analysis of the movements, strength, velocity and projection allow identifying relevant points that directly impact athletes' results. In this context, this work uses a Radial Basis Function Neural Network (RBF-NN) with training combining the Gustafson-Kessel clustering method and the proposed Modified Differential Evolution (MDE) in order to perform the swimmer velocity profile identification. The main idea is to obtain the dynamic of the velocity profile and to use it to improve the athletes' swim style. Differential Evolution (DE) is an evolutionary algorithm that uses a rather greedy and less stochastic approach to solve problems when compared to other evolutionary methods [1]. However, to achieve good performance with DE, the tuning of control parameters is essential as its performance is sensitive to the choice of the mutation and crossover settings. On the other hand, the RBF-NN is a powerful approach for nonlinear identification. This paper combines the two strategies described above proposing a modified DE algorithm based on the association of a sinusoidal signal and chaotic sequences generated by logistic map for the mutation factor tuning. By using data collected from breaststroke and crawl swim style of an elite female swimmer, the validity and the accuracy of the RBF-NN model have been tested by simulations. Results reveal that it is feasible to establish a good model to represent data experimental related to swimming field. Identification results show that MDE outperforms both other tested classical DE approaches for training RBF-NNs in terms of solution quality. © 2013 IEEE.

关键词： Optimization

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Structural Analysis of Thumb Mechanism Exoskeleton Design for Post-Stroke Rehabilitation

Structural Analysis of Thumb Mechanism Exoskeleton Design fo...

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2023 International Conference on Advanced Mechatronics, Intelligent Manufacture and industrial Automation, ICAMIMIA 2023

作者： Qoryah, Rika Dwi Hidayatul Guntur, Harus Laksana Nurhadi, Hendro Prastyo, Handri Kristianta, Franciscus Xaverius Chandika, Shendy Institut Teknologi Sepuluh Nopember Graduate Program of Mechanical Engineering Department Surabaya Indonesia Institut Teknologi Sepuluh Nopember Mechanical Engineering Department Surabaya Indonesia Institut Teknologi Sepuluh Nopember Mechanical Engineering Department Surabaya Indonesia University of Jember Undergraduate Program Mechanical Engineering Department Jember Indonesia University of Jember Mechanical Engineering Department Jember Indonesia

ISBN: (纸本)9798350309225

Stroke is the second cause of death and the third cause of disability in the world. Stroke is a disease caused by a clot in the artery that supplies blood to the brain (ischemia). Rehabilitation is a solution to restore the function of parts of the body that have been disturbed by a stroke. Therefore, exoskeleton robots for stroke therapy are one solution to provide good rehabilitation. The exoskeleton robot supports healthy human hand movements and considers the safety and comfort factors during rehabilitation. The exoskeleton in this research uses a cable and sheath transmission mechanism with a locally situated motor as a design mechanism that guarantees safety and comfort. The design strength can be determined using ANSYS static structural assistance software so that the maximum stress in links 1, 2, and 3 is known within safe limits with anthropometric loading. Apart from that, the static structural simulation results show that link 1 can withstand a maximum load of 20 N or more in the X-axis loading, a load of 15 N in the Y-axis loading, and a load of 15 N in the Y-axis loading, and a load of 10 N in the Z-axis loading. Link 2 can withstand a maximum load of 10 N in the X-axis load and 20 N or more in the Y-axis load. Meanwhile, link 3 can withstand a maximum load of 20 N in the X-axis load and below 10 N in the Y-axis load. © 2023 IEEE.

关键词： Finite element method

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CLINICAL DETERIORATION PREDICTION IN BRAZILIAN HOSPITALS BASED ON ARTIFICIAL NEURAL NETWORKS AND TREE DECISION MODELS 15

CLINICAL DETERIORATION PREDICTION IN BRAZILIAN HOSPITALS BAS...

引用

15th International Conference on ICT, Society and Human Beings, ICT 2022, 19th International Conference on Web Based Communities and Social Media, WBC 2022 and 14th International Conference on e-Health, EH 2022 - Held at the 16th Multi Conference on Computer Science and Information systems, MCCSIS 2022

作者： Yazdanpanah, Hamed Silva, Augusto C.M. Guedes, Murilo Morales, Hugo M.P. dos Coelho, Leandro S. Moro, Fernando G. Department of Research Robô Laura PR Curitiba Brazil Department of Computer Science University of São Paulo SP São Paulo Brazil Industrial and Systems Engineering Graduate Program Pontifical Catholic University of Parana PR Curitiba Brazil Electrical Engineering Graduate Program Federal University of Parana PR Curitiba Brazil

ISBN: (纸本)9789898704405

Early recognition of clinical deterioration (CD) has vital importance in patients’ survival from exacerbation or death. Electronic health records (EHRs) data have been widely employed in Early Warning Scores (EWS) to measure CD risk in hospitalized patients. Recently, EHRs data have been utilized in Machine Learning (ML) models to predict mortality and CD. The ML models have shown superior performance in CD prediction compared to EWS. Since EHRs data are structured and tabular, conventional ML models are generally applied to them, and less effort is put into evaluating the artificial neural network’s performance on EHRs data. Thus, in this article, an extremely boosted neural network (XBNet) is used to predict CD, and its performance is compared to eXtreme Gradient Boosting (XGBoost) and random forest (RF) models. For this purpose, 103,105 samples from thirteen Brazilian hospitals are used to generate the models. Moreover, the principal component analysis (PCA) is employed to verify whether it can improve the adopted models’ performance. The performance of ML models and Modified Early Warning Score (MEWS), an EWS candidate, are evaluated in CD prediction regarding the accuracy, precision, recall, F1-score, and geometric mean (G-mean) metrics in a 10-fold cross-validation approach. According to the experiments, the XGBoost model obtained the best results in predicting CD among Brazilian hospitals’ data. © 2022 15th International Conference on ICT, Society and Human Beings, ICT 2022, 19th International Conference on Web Based Communities and Social Media, WBC 2022 and 14th International Conference on e-Health, EH 2022 - Held at the 16th Multi Conference on Computer Science and Information systems, MCCSIS 2022. All rights reserved.

关键词： Neural networks

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Weasel: A user guided enemy course of action generator

Weasel: A user guided enemy course of action generator

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7th International Conference on knowledge-Based Intelligent Information and engineering systems, KES 2003

作者： Hayes, Caroline C. Ravinder, Ujwala University of Minnesota Graduate Program in Industrial Engineering 111 Church Street S. E MinneapolisMN55101 United States

ISBN: (纸本)3540408045

A difficulty for military analysts to thoroughly consider possible plans which the enemy might follow under various assumptions [1]. However, it is critical to do so to avoid dangerous surprises. Weasel is a decision support system that assists intelligence analysts in developing alternative enemy courses of action (ECOAs) consistent with intelligence conclusions and specified assumptions. A design goal behind Weasel is to provide users with the convenience of automation while still providing them with flexibility and control over the results. Weasel allows users to perform "what if" analyses in which they can change assumptions about enemy resources, current position, and maneuver constraints. Weasel integrates two other decision support tools, CoRaven[2], which assists in analyzing intelligence data, and Fox [4], which assists in generating friendly courses of action (FCOAs). The combination of CoRaven,Weasel and Fox can provide powerful assistance in the military tactical decision making process. © Springer-Verlag Berlin Heidelberg 2003.

关键词： Decision support systems

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Addressing knowledge management transfer in project management at digital manufacturing

Addressing knowledge management transfer in project manageme...

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2018 Institute of industrial and systems Engineers Annual Conference and Expo, IISE 2018

作者： Muncinelli, Gianfranco De Lima, Edson Pinheiro Deschamps, Fernando Gouvea Da Costa, Sergio E. Beller, Cassiano S. Industrial and Systems Engineering Graduate Program Pontifical Catholic University of Parana Curitiba Brazil Federal University of Technology - Parana Curitiba Brazil Department of Mechanical Engineering Federal University of Parana Curitiba Brazil Superior Institute of Administration and Economy of Mercosul Curitiba Brazil

Manufacturing has been changing drastically the way it approaches facility design and implementation, that is, there is a growing adoption of digital techniques. This paper intends to determine the theoretical concepts and guidelines for assisting the study of alternatives for problem-solving in a specific case of an automaker digital manufacturing project. The main objective of the research is to determine the theoretical components that will assist in the forwarding of solutions to the problems observed in the current model of project management of digital manufacturing projects. The conceptual guidelines proposed based on systematic literature and guided the construction of research protocol that collects data from technical visits (semi-participative observation), technical documents and procedures, information systems log and archives, and semi-structured interviews. Data analysis use the mechanism of triangulation and workshops for producing a conceptual analysis about how each factor can assist in addressing the solving of the issues observed, building the theoretical constructs. The manufacturing engineering team could identify strengths and weakness on the ongoing practices and better plan improvements for reaching opportunities and mitigating threats/risks. The findings are classified in the following aspects: cultural, technology, knowledge content, organization, processes, and project management;and showed a complete analysis on how ready is the organization for developing digital manufacturing projects. © 2018 Institute of industrial Engineers (IIE). All rights reserved.

关键词： Knowledge management

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Proposal of a framework for a disaster management system

Proposal of a framework for a disaster management system

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2016 industrial and systems engineering Research Conference, ISERC 2016

作者： Foggiatto, Anderson Avanzi, Daniel de Freitas Rocha Loures, Eduardo Deschamps, Fernando Industrial and Systems Engineering Graduate Program Pontifical Catholic University of Parana Curitiba Brazil Instituto Curitiba de Informática Curitiba Brazil Federal University of Technology - Parana Curitiba Brazil Department of Mechanical Engineering Federal University of Parana Curitiba Brazil

During a disaster, the more coordinated the response, the lesser its impacts are. One of the factors that has a major influence in response coordination is the interoperability among involved actors - public and private entities that interact to exchange information through the communication of people and systems. This factor is critical because it allows an efficient and effective mobilization of available resources towards reducing the effects caused by an event. This work proposes a framework for the development of Disaster Management systems (DMS) that promote real time communication (information flow and process coordination) among different involved entities, primarily focusing on interoperability in its different levels. This framework is based both on a literature review of scientific works and a survey of worldwide initiatives related to improving disaster response. The main components of the related framework architecture are an SDK (software development kit), a common relational database, multiple communication platforms (e.g., a Web portal and a mobile app), and low-cost hardware to better collect and make needed information available quickly and accurately. © 2016 Proceedings of the 2016 industrial and systems engineering Research Conference, ISERC 2016. All rights reserved.

关键词： Interoperability

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