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检索条件"机构=Graduate Program in Systems Engineering"

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Multi-objective Support Vector Machines Ensemble Generation for Water Quality Monitoring

Multi-objective Support Vector Machines Ensemble Generation ...

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Congress on Evolutionary Computation

作者： Victor Henrique Alves Ribeiro Gilberto Reynoso-Meza Industrial and Systems Engineering Graduate Program Pontifical Catholic University of Parana (PUCPR) Curitiba Brazil

Real-world classification problems generally deal with imbalanced data, where one class represents the majority of the data set. The present work deals with event detection on a drinking-water quality time series, where the presence of a quality event is the minority class. In order to solve such problems, supervised learning algorithms are recommended. Researchers have also used multi-objective optimization (MOO) in order to generate diverse models to build ensembles of classifiers. Although MOO has been used for ensemble member generation, there is a lack on it's application for member selection, which is usually done by selecting a specific subset from the resulting models, or by using meta-algorithms, such as boosting. The proposed work comprises the application of MOO design in the whole process of ensemble generation. To do so, one multi-objective problem (MOP) is defined for the creation of a set of non-dominated solutions with Pareto-optimal support vector machines (SVM). After that, a second MOP is defined for the selection of such SVMs as members of an ensemble. Such methodology is compared to other member selection methods, such as: the single best classifier, an ensemble composed of the full set of non-dominated solutions, and the selection of a specific subset from the Pareto front. Results show that the proposed method is suitable for the creation of ensembles, achieving the highest classification scores.

关键词： Support vector machines Optimization Mood Training Event detection Kernel Supervised learning

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Integrating agents and soft computing in Intelligent Manufacturing System models

Integrating agents and soft computing in Intelligent Manufac...

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International Conference on Emerging Technologies and Factory Automation (ETFA)

作者： Luiz Marcio Spinosa Leandro dos Santos Coelho Industrial and Systems Engineering Graduate Program Pontifical Catholic University of Paraná Curitiba Parana Brazil

This paper introduces an approach to deal with IMS (Intelligent Manufacturing System) models, in order to help the development of Decision Support systems, Simulators and Performance Evaluators. The complexity of such systems is growing continuously requiring knowledge and information exchange between different manufacturing functions with more and more efficiency. This paper explores some potentialities of soft computing approaches and intelligent agent-oriented design including artificial neural networks, fuzzy systems, and evolutionary computation. The rationale is in order to support decision making processes performed by the autonomous and co-operative units of an IMS.

关键词： Computational modeling Manufacturing Object oriented modeling Artificial intelligence Artificial neural networks Evolutionary computation Fuzzy logic

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Multi-objective PID Controller Tuning for an Industrial Gasifier

Multi-objective PID Controller Tuning for an Industrial Gasi...

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Congress on Evolutionary Computation

作者： Victor Henrique Alves Ribeiro Gilberto Reynoso- Meza Industrial and Systems Engineering Graduate Program Pontifical Catholic University of Paraná (PUCPR) Curitiba Brazil

Control of industrial plants is an important engineering field of study, where the optimization of such processes can lead to better product quality and higher profit. The present work deals with the optimization of an industrial gasifier, proposed as a benchmark challenge by ALSTOM Power Technologies in 2002. Researchers from around the globe proposed different methods for optimizing such system, using linear and nonlinear system identification techniques, different controller schemes, such as proportional-integral-derivative and model predictive controllers, and search methods for controller tuning. The authors care for the study of a methodology that can generalize the controller optimization process of real industrial systems, where linear system identification can lead to simpler systems, which are used to design more robust controllers. The proposed work deals with linear system identification and multiobjective optimization for the gasifier's controller design. To do so, the authors divide the problem in two steps, the linear system identification, where step functions are fed to the gasifier in order to detect the output response of the system, and the design of a proportional-integral-derivative controller, where spherical pruned multi-objective differential evolution algorithm is used in order to optimize the controller gains. The proposed method, unfortunately, does not provide an optimal controller, which can be explained by the complexity of the benchmark system. With such results, the authors believe a better multi-objective problem definition is necessary. Also, it is concluded that such benchmark presents a real challenge for future controller design methndologies.

关键词： Optimization Process control Benchmark testing Tuning PD control Genetic algorithms

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A genetic algorithm based method to support the geometric prosthesis modelling in skull repairing

A genetic algorithm based method to support the geometric pr...

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2013 International Conference on Biomedical engineering and Environmental engineering (ICBEEE 2013)

作者： Marcelo Rudek Osiris Canciglieri Junior Thiago Greboge Anderson Luis Szejka Industrial and Systems Engineering Post-Graduate Program PPGEPSPontifical Catholic University of ParanaPUCPR

This paper addresses the problem of the geometric modeling of prosthesis to correct defects in skull bone by computational approach viewpoint. The missing area in a defective skull can be virtually filled by a criterion based on the curvature of the skull shape. The basic argument is that in a computed tomography, the 2D skull border in slice image is similar to a rounded form. This research is proposing a method to find adjusted ellipses on its curvature by Ellipse Adjustment Algorithm(EAA) technique. If the ellipse is correctly adjusted in each computed tomography slice, the resulting arcs that fill the missing area can be built in 3D in order to complete an unknown region in the bone. The problem is that there are many possible solutions and the selection of the best ellipse that fits the contour shape is performed by a Genetic Algorithm(GA). The piece of bone that was missed in skull can be built as a synthetic image to fill a hole at defect position in the skull. With the ellipse parameters it is possible to generate profiles with its set of points in order to build the 3D model using a CAD system. The case study shows the use of the method applied to non-symmetric defects and presents the obtained results.

关键词： Prosthesis modelling tomography images genetic algorithm

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Design of support vector machine by adaptive aggregation

Design of support vector machine by adaptive aggregation

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International Joint Conference on Neural Networks (IJCNN)

作者： O. Chacon I. Litvintchev A. Alvarez E. Vazquez Graduate Program of Systems Engineering Universidad Autonoma de Nuevo Leon Nuevo Leon Mexico

This article provides a new algorithm to solve the design of classification machine, for linearly separable sets, based in support vectors. For large scale binary classification, an adaptive aggregation (AAM) procedure is executed so that the size of possible support vectors decrease, in each iteration, until convergence to maximum separation margin is achieved.

关键词： Support vector machines Support vector machine classification systems engineering and theory Algorithm design and analysis Large-scale systems Active appearance model Convergence Pattern recognition Statistical learning Statistics

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Editorial

引用

Journal of Scheduling 2006年第3期9卷 199-201页

作者： Bard, Jonathan F. Barnhart, Cynthia Graduate Program in Operations Research The University of Texas Austin USA Civil & Environmental Engineering and Engineering Systems Massachusetts Institute of Technology Cambridge USA

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Potential Impact of Social Media to Support Government Services in Jakarta Smart City 3

Potential Impact of Social Media to Support Government Servi...

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3rd International Conference on Information Management and Technology, ICIMTech 2018

作者： Didik Madyatmadja, Evaristus Abdurachman, Edi Gaol, Ford Lumban Pudjianto, Bonifasius W. Hapsara, Manik Information Systems Department Computer Science Department BINUS Graduate Program-Doctor of Computer Science Jakarta11480 Indonesia Computer Science Department Bina Nusantara University BINUS Graduate Program-Doctor of Computer Science Jakarta11480 Indonesia Indonesian Creative Economy Agency Jakarta Indonesia University of New South Wales School of Engineering and Information Technology Australia

ISBN: (纸本)9781538658215

The purpose of this initiative is to ensure that citizens use social media to access information about the state of the city. Social media application offers benefits in the form of a channel of communication between the community and the government or the group that has public interest. Through this application, the public could channel complaints about public services. Perception becomes the important key for this condition because user action is determined by their perception toward the government e-services. The result of standard measurement for customer satisfaction on government organization is used to help find the weakness of the service and correct it. The interface is made to be more user-friendly to ensure the effective service. So, it is necessary to develop the system continuously. Perceived quality is one of the important determinants of the success of social media application, therefore needs identification of the user's perception and expectations and involving becomes the key to success besides the good quality that will increase the trust and satisfaction of users. Evaluation of social media applications is needed so that it can provide recommendations to the provincial government of DKI Jakarta related to what things can be done to improve community service. © 2018 IEEE.

关键词： Smart city

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Use of Cultural Particle Swarm Optimization for Loney's Solenoids Design

Use of Cultural Particle Swarm Optimization for Loney's Sole...

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IEEE Conference on Electromagnetic Field Computation

作者： L. dos Santos Coelho V. Cocco Mariani Production and Systems Engineering Graduate Program Automation and Systems Laboratory PUCPR/PPGEPS/LAS Pontifical Catholic University of Paraná Curitiba Brazil Mechanical Engineering Graduate Program PUCPR/PPGEM Pontifical Catholic University of Paraná Curitiba Brazil

This work presents the use of particle swarm optimization (PSO) techniques with the particles' population space based on normative knowledge of cultural algorithms (CA). In this work, the optimal shape design of L... 详细信息

关键词： Cultural differences Particle swarm optimization Solenoids Optimization methods Design optimization Algorithm design and analysis Gaussian distribution Probability distribution Random number generation Equations

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Applying the MVC EA-IRPM to reporting-guidelines in medicine: A strategy that is a web system 4

Applying the MVC EA-IRPM to reporting-guidelines in medicine...

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4th IEEE EMBS International Conference on Biomedical and Health Informatics, BHI 2017

作者： Letouze, Patrick De Souza, J.I.M. Silva, Valeria Martins Climaco, Glaubos Chagas, F.B. Ishihara, Joao Y. Graduate Program of Computational Modeling of Systems Universidade Federal Do Tocantins Quadra 109 Norte Avenida NS-15 Palmas77001-090 Brazil Graduate Program of Systems' Engineering and Computation - PESC Universidade Federal Do Rio de Janeiro Rio de Janeiro Brazil Department of Informatics at the Universidade Federal Do Maranh/ Ao - UFMA Brazil Faculty of Computer Science Faculdade Pitagoras Imperatriz Imperatriz Brazil Faculty of Electrical Engineering Universidade de Brasília Brasília Brazil

ISBN: (纸本)9781509041794

Reporting-Guidelines in Medicine play an important role in promoting the quality of reports in health-related research. For instance, a poorly reported research may induce misinterpretation and inappropriate clinical settings. Basically, three major issues regarding Reporting-Guidelines in Medicine has to be addressed: (1) the existence of lots of reporting guidelines covering a broad spectrum of medical research increases the difficulties when reporting a medical research because it may not be clear which guidelines are applicable, or if all related guidelines are considered;(2) most guideline developers have not described how their guidance was developed, consequently tracking guidelines and features for evaluation, or even for correcting, may be not possible;(3) few guideline developers have evaluated the effectiveness of their guidance, then the real value that the guideline brings to reporting the research is not assured. Hence, we propose a solution to these three issues based on the Model-View-Controller Evolutionary Acquisition Interdisciplinary Research Project Management (MVC EA-IRPM) that is simultaneously a strategy and a web system for the development and management of reporting guidelines. © 2017 IEEE.

关键词： Clinical research

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Cascaded free search differential evolution applied to nonlinear system identification based on correlation functions and neural networks

Cascaded free search differential evolution applied to nonli...

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IEEE Symposium on Computational Intelligence in Control and Automation, CICA

作者： Helon Vicente Hultmann Ayala Luciano F. da Cruz Roberto Z. Freire Leandro dos Santos Coelho Industrial and Systems Engineering Graduate Program Pontificia Universidade Catolica do Parana Curitiba PR BR Industrial and Systems Engineering Graduate Program Pontifical Catholic University of Parana Curitiba Brazil Federal University of Parana Curitiba Brazil

This paper presents a procedure for input selection and parameter estimation for system identification based on Radial Basis Functions Neural Networks (RBFNNs) models and Free Search Differential Evolution (FSDE). We adopt a cascaded evolutionary algorithm approach and problem decomposition to define the model orders and the related model parameters based on higher orders correlation functions. Thus, we adopt two distinct populations: the first to select the lags on the inputs and outputs of the system and the second to define the parameters for the RBFNN. We show the results when the proposed methodology is applied to model a coupled drives system with real acquired data. We use to this end the canonical binary genetic algorithm (selection of lags) and the recently proposed FSDE (definition of the model parameters), which is very convenient for the present problem for having few control parameters. The results show the validity of the approach when compared to a classical input selection algorithm.

关键词： Modeling Correlation Predictive models Sociology Evolutionary computation Algorithm design and analysis

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