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9th International Joint Conference on Computational Intelligence, IJCCI 2017

作者： Boaretto, Marco A. R. Busatto, Rafael Commim Dos S Coelho, Leandro Federal University of Parana Electrical Engineering Graduate Program Curitiba Brazil Pontifical Catholic University of Parana Industrial and Systems Eng. Grad. Program Curitiba Brazil

ISBN: (纸本)9789897582745

The problems related with urban fires brings destruction, casualties and economic issues to the country. On aiming to decrease the risk specially on populous areas, the development of classification and/or forecasting systems are needed to detect these events. This paper presents a new case of study related with fire incidents to create a predictor with a machine learning technique allied with an optimization technique. Differential evolution (DE) is a population-based stochastic search evolutionary algorithm applied to nonlinear, nondifferentiable, and continuous space functions. It has shown good performance on a wide range of benchmark problems as well as many real-world applications. Extreme Gradient boosting machine (XGBoost) is an efficient boosting technique that is getting a lot of attention because of its success on winning several of competitions hosted by the site Kaggle. However, XGBoost's hyper-parameters tuning process demands a high effort and computational time, hence the application of an optimization technique as DE. In this context, DE showed to be an efficient and robust optimization tool, presenting good and stable results on the adopted tests. Along with the XGBoost hyper-parameter tuning optimized approach, this paper presents a novel database from service times of real fire incidents of the years 2013 and 2014 that were gathered with the Fire department of the state of Paraná on the city of Curitiba in Brazil (FDPRC). The regression results could contribute with FDPRC, to speed up the location reckoning process of the fire incidents, improving the answering time of the calling. Copyright © 2017 by SCITEPRESS - Science and Technology Publications, Lda. All rights reserved.

关键词： Evolutionary algorithms

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Vibration-based classification of road damages: Gyroscope data and a simple neural network model 2

Vibration-based classification of road damages: Gyroscope da...

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2nd International Conference on Eco engineering Development 2018, ICEED 2018

作者： Gunawan, Fergyanto E. Herriyandi Soewito, Benfano Mauritsius, Tuga Surantha, Nico Industrial Engineering Department BINUS Graduate Program - Master of Industrial Engineering Bina Nusantara University Jakarta11480 Indonesia Computer Science Department BINUS Graduate Program - Master of Computer Science Bina Nusantara University Jakarta11480 Indonesia Information Systems Management Department BINUS Graduate Program - Master of Information Systems Management Bina Nusantara University Jakarta11480 Indonesia

A system for automatic detection of road damages is essential for logistics management. At the core of the system lies an algorithm for classification of damages. This work intends to establish such an algorithm. In the current proposal, the algorithm receives data of the probe vehicle rate of rotations, extracts statistics descriptive from the data to produce a feature vector, and finally, feeds the vector to a simple-three-layer neural network to classify the damages. The types of damages are limited to four cases: normal, pothole, speed bump, and expansion joint. For the development, a probe vehicle is used to produce 400 empirical data involving those four damage cases. By using Monte Carlo approach, the established neural network model is evaluated. The results show that the approach is able to classify the cases with 85% accuracy. The study also finds that the rates of pitch and roll to be the determining factors. © 2018 Institute of Physics Publishing. All rights reserved.

关键词： Neural network models

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On selecting the MIMO Generalized Orthonormal Basis Functions poles by using Particle Swarm Optimization

On selecting the MIMO Generalized Orthonormal Basis Function...

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European Control Conference (ECC)

作者： Bruno C. Reginato Gustavo H. C. Oliveira Industrial and Systems Engineering Graduate Program (PPGEPS) of the Pontifical Catholic University of Parana (PUCPR)

This paper deals with the problem of finding the pole(s) in Orthonormal Basis Functions (OBF) models. In fact, any stable system can be exactly represented by an infinite orthonormal functions series, assuming that the basis used in such representation is complete. However, in practice a truncated basis functions expansion is used. For certain basis choice and fixed number of functions, there is a pole or set of poles that minimizes the truncation error. The problem is then to find such set. Therefore, the present paper is focused on the problem of finding the basis functions poles when more than one dynamic is involved, for instance, in SISO Generalized Orthonormal Basis Functions (GOBF) models or MIMO Laguerre, Kautz and/or GOBF models. It is proposed and analyzed here the use of Particle Swarm Optimization (PSO) for such problem. Simulation results presented shows the validity of the proposed method.

关键词： Convergence Mathematical model Particle swarm optimization Approximation methods Optimization MIMO Equations

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Improved multiobjective particle swarm optimization for designing PID controllers applied to robotic manipulator

Improved multiobjective particle swarm optimization for desi...

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IEEE Symposium on Computational Intelligence in Control and Automation, CICA

作者： Juliano Pierezan Helon H. V. Ayala Luciano F. da Cruz Roberto Z. Freire Leandro dos S. Coelho Federal University of Parana— UFPR Electrical Engineering Graduate Program — PPGEE Curitiba Brazil Pontifical Catholic University of Parana — PUCPR Industrial and Systems Engineering Graduate Program — PPGEPS Curitiba Brazil Department of Electrical Engineering — DEE/PPGEE Industrial and Systems Engineering Graduate Program — PPGEPS and Federal University of Parana — UFPR Curitiba Brazil

In order to improve equipment efficiency in terms of performance, energy consumption and degradation for example, the industry has increased the use of control systems as the PID (proportional-integral-derivative) to a new baseline. This structure has few parameters to adjust and it is easy to implement practically. However, there are some requirements often included on multivariable systems that cannot be solved concurrently by classical methods. To solve this problem, the current paper approaches the application of Multiobjective Differential Evolution (MODE), Multiobjective Harmony Search (MOHS) and Multiobjective Particle Swarm Optimization (MOPSO) on multivariable PID controllers tuning. Moreover, an improved version of MOPSO (I-MOPSO) is proposed and its performance is compared with the other algorithms. In order to validate it under control systems, the optimization technique is applied on a two degree of freedom robotic manipulator. Finally, a detailed analysis is made on the I-MOPSO achievements.

关键词： Optimization Manipulator dynamics Mathematical model Particle swarm optimization Vectors

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Automated 3D bone modelling based on geometric features from images 24

Automated 3D bone modelling based on geometric features from...

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24th International Conference on Production Research, ICPR 2017

作者： Rudek, M. Gumiel, Y.B. Canciglieri, O. Carvalho, D.R. Trajanovic, M. Industrial and Systems Engineering Post-Graduate Program PUCPR Imaculada Conceicao Street 1155 zip code CuritibaParana80215-901 Brazil Graduate Program on Health Technology in Pontifical Catholic University of Parana PUCPR Imaculada Conceicao Street 1155 zip code CuritibaParana80215-901 Brazil Faculty of Mechanical Engineering University of Nis Aleksandra Medvedeva 14 Niš18000 Serbia

ISBN: (纸本)9781605955070

Currently the computational modelling tools, expert algorithms for image segmentation and three-dimensional printing devices have improved the process of manufacture of customized pieces in the context of automation of prosthesis modelling. Among several strategies to obtain the correct shape of a missing bone part, we explore a modelling method based on geometric features defined by Bezier cubic curves. The data is obtained from sets of slices of tomographic scans as a reference. From the images, we know about data from the edges in the image but we do not have any information about a missing area in a specific bone region. Thus, the objective is to search patterns for features whose values are known from similar tomographic image which matches to fill a hole in a bone. Due the free form of a bone there are a lot of parameters to be evaluated. Thus, a Data Mining approach is applied for classification and to discover the best features as shape descriptors. In this way, the prosthesis manufacture can be automated in all stages among image scanning and printing. © 2017 DEStech Publications. All rights reserved.

关键词： Image enhancement

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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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The performance measurement in nonprofit organizations - A case study 67

The performance measurement in nonprofit organizations - A c...

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67th Annual Conference and Expo of the Institute of industrial Engineers 2017

作者： Moura, Louisi Francis De Lima, Edson Pinheiro Van Aken, Eileen Deschamps, Fernando Treinta, Fernanda Tavares Da Costa, Sergio E. Gouvea 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 Grado Department of Industrial and Systems Engineering Virginia Tech Blacksburg United States

ISBN: (纸本)9780983762461

Nonprofit organizations have specific and complex characteristics that influence their performance measurement and differentiate it from others business models. So, it is important to know what are the factors, as motivations, barriers, and drivers, that influence the design of a performance measurement system to develop a complete system with all organizational issues, as social aspects, accountability, and legitimacy. A systematic literature review was previously performed and a set of factors that influence the design of performance measurement system for nonprofit organizations were identified. This paper presents a case study conducted in a Fire department in the United States with the purpose investigate the set of factors in the practice. The data were collected using four techniques: interviews, documents and archival records, and observation. The findings show that the influence of the factors can vary depending on the type of organization and the paper indicates some reasons for that. Therefore, understanding the organization and these factors is a challenge for the performance measurement area to provide tools and frameworks that contribute to the organizational management and research area advance.

关键词： Social aspects

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Factors for design of performance measurement systems for not-for-profit organizations

Factors for design of performance measurement systems for no...

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2016 industrial and systems engineering Research Conference, ISERC 2016

作者： Moura, Louisi Francis de Lima, Edson Pinheiro Deschamps, Fernando van Aken, Eileen Gouvea da Costa, Sergio E. 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 Grado Department of Industrial and Systems Engineering Virginia Tech Blacksburg United States

The scope of this research is delimited by the study of not-for-profit organizations performance through operations management lens. According to a systematic literature review, the performance measurement frameworks applied to not-for-profit organizations are adaptations of models developed for for-profit companies. However, the specific characteristics related to participatory governance, responsibility to declare their tangible and intangible results, and accountability of different revenue sources that combine donations, governmental aids, volunteering or public financing are usually not properly considered. In this context, this paper intends to identify factors that intervene in not-for-profit organizations' performance measurement systems, and to organize them in a conceptual framework that could assist not-for-profit organizations to better design their performance measurement systems. The paper also analyzes how enterprise engineering design principles can be applied in this context, relating the intervening factors to enterprise engineering guidelines. © 2016 Proceedings of the 2016 industrial and systems engineering Research Conference, ISERC 2016. All rights reserved.

关键词： industrial research

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Controller tuning with multi-objective optimization: benchmark definitions for SISO linear systems: A PI controller case ⁎

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IFAC-PapersOnLine 2024年第7期58卷 126-131页

作者： Gilberto Reynoso-Meza Ricardo Massao Kagami Industrial and Systems Engineering Graduate Program (PPGEPS) Pontifical Catholic University of Paraná (PUCPR) Control Systems Optimization Laboratory (LOSC) Pontifícia Universidade Católica do Paraná (PUCPR)

Multi-objective optimization techniques are practical techniques for controller tuning purposes. A wide variety of papers use such an approach or propose new algorithms to approximate the Pareto front. Nevertheless, despite the expressive volume of works dealing with it, there is no standard benchmark testbed that could be used as a baseline comparison among different techniques. This work addresses such a gap, with a first step proposing a linear-SISO testbed with guidelines and rules and providing a basic example for a PI controller. Such a benchmark is expected to promote further research on the topic.

关键词： Multi-objective optimization Parametric optimization Evolutionary 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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