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4th IEEE Symposium on Computational Intelligence in Control and Automation, CICA 2014

作者： Pierezan, Juliano Ayala, Helon H. V. Da Cruz, Luciano F. Freire, Roberto Z. Dos S. Coelho, Leandro 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 Federal University of Parana - UFPR Department of Electrical Engineering - DEE/PPGEE Curitiba Brazil

ISBN: (纸本)9781479945313

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. © 2014 IEEE.

关键词： Three term control systems

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Water management and conductivity studies in novel polymer zirconium-based membranes for PEM fuel cells

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Case Studies in Chemical and Environmental engineering 2025年 11.0卷

作者： Ahmed, Tallah Magdi Al Othman, Amani Shamayleh, Abdulrahim Tawalbeh, Muhammad Engineering Systems Management Graduate Program American University of Sharjah PO. Box 26666 Sharjah United Arab Emirates Department of Chemical and Biological Engineering American University of Sharjah PO. Box 26666 Sharjah United Arab Emirates Energy Water and Sustainable Environment Research Center American University of Sharjah PO. Box 26666 Sharjah United Arab Emirates Department of Industrial Engineering American University of Sharjah PO. Box 26666 Sharjah United Arab Emirates Sustainable and Renewable Energy Engineering Department University of Sharjah PO. Box 27272 Sharjah United Arab Emirates Sustainable Energy & Power Systems Research Centre RISE University of Sharjah P.O. Box 27272 Sharjah United Arab Emirates

Proton exchange membrane fuel cells (PEMFCs) are among the promising alternatives for clean energy generation, especially when hydrogen is the fuel used. Their operation is still faced with several challenges, and one of them is water accumulation in the cathode compartment. If PEMFCs are operated at temperatures above the boiling point of water, a significant obstacle would be eliminated due to the formation of water in the vapor phase. This prevents water from accumulating in the liquid phase which causes flooding. Therefore, this work aims to develop a novel composite membrane based on zirconium silicate (ZrSiO₄) and Polyvinylidene fluoride (PVDF) for such high-temperature operation. The composite membrane was synthesized using solution casting, and its structural and chemical properties were characterized using thermogravimetric analysis (TGA), Fourier-transform infrared spectroscopy (FTIR), X-ray diffraction (XRD), and scanning electron microscopy (SEM) techniques. The ZrSiO₄/PVDF membrane demonstrated a maximum proton conductivity of 2.14 × 10⁻³ S/cm at room temperature with 8 wt% ZrSiO₄, along with a water uptake value of 43.85 %. Consequently, when tested above the boiling point of water, the membrane exhibited a high conductivity of 2.13 × 10⁻³ S/cm at 105 °C. The results suggest the suitability of such zirconium silicate-based composite membranes for fuel cell applications operating above the boiling point of water. © 2024 The Author(s)

关键词： Composite membranes PEM fuel cells Proton conduction PVDF Water management Zirconium silicate

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Towards a Predictive Approach for Omni-channel Retailing Supply Chains

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IFAC-PapersOnLine 2019年第13期52卷 844-850页

作者： Pereira, Marina Meireles Frazzon, Enzo Morosini Graduate Program in Production Engineering Industrial and Systems Engineering Department Technology Center Federal University of Santa Catarina Florianópolis Santa Catarina Brazil

The adoption of omni-channel strategy has changed the relation between retailers and customers and brought more complexity to the retailing supply chains. To address the increasing complexity, it is necessary to adopt innovative approaches based on information technologies and intelligent decision methods. The challenges to retailers are improving the accuracy of offline and online channels demand forecasting, better managing offline and online customer's needs, thus reducing the uncertainties of the omni-channel retailing supply chain. In this context, this research paper aims to propose a predictive approach for omni-channel retailing supply chain combining clustering with artificial neural network to handle demand uncertainty. © 2019, IFAC (International Federation of Automatic Control) Hosting by Elsevier Ltd. All rights reserved.

关键词： Neural networks Complex networks Learning systems Sales Supply chain management Channel strategies Clustering Demand forecasting Demand uncertainty Innovative approaches Intelligent decisions Omni channel Retail supply chain

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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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RBF Neural Network combined with Self-Adaptive MODE and Genetic Algorithm to Identify Velocity Profile of Swimmers

RBF Neural Network combined with Self-Adaptive MODE and Gene...

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IEEE Symposium Series on Computational Intelligence

作者： Luciano F. da Cruz Roberto Z. Freire Gilberto Reynoso-Meza Flavia B. Pinto Leandro dos S. Coelho Industrial and Systems Engineering Graduate Program PUCPR Curitiba Brazil Industrial and Systems Engineering Graduate Program Department of Electrical Engineering PUCPR UFPR Curitiba Brazil

ISBN: (纸本)9781509042418

On the side of enhancing the execution of skills, specialists in sports are adopting analysis of kinematics to correct actions of an athlete. By means of technological resources used to measure physical variables and to supply relevant data to trainers, results related to improvements on athletes' performance are being achieved. In this context, this work uses the Radial Basis Function Neural Networks (RBF-NNs) combined in cascade with a Genetic Algorithm (GA) as a cross-correlation method, likewise Multiobjective Differential Evolution (MODE) and self-adaptive MODE (using JADE - Adaptive Differential Evolution with Optional External Archive - self-adaptation method) for optimization. The RBF-NNs have been applied to predict the swimmers velocity profile being multiple correlation coefficient (R~2) adopted to evaluate the optimization techniques during both estimation and validation stages. A data acquisition system was used to capture the para-swimming athletes' instantaneous velocity data, swimming 25 meters in crawl, breaststroke, backstroke, and butterfly strokes. Looking at the results achieved, self-adaptive MODE outperforms classical MODE in approach point of view considering all cases studied, finding the best RBF-NN framework to identify the profile of speed in swimming.

关键词： Multiobjective optimization RBF neural networks self-adaptive swim time series forecasting

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Multiobjective Cuckoo Search Applied to Radial Basis Function Neural Networks Training for System Identification

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IFAC Proceedings Volumes 2014年第3期47卷 2539-2544页

作者： Helon Vicente Hultmann Ayala Leandro dos Santos Coelho Industrial and Systems Engineering Graduate Program (PPGEPS) PUCPR Curitiba Brazil Electrical Engineering Graduate Program (PPGEE) UFPR Curitiba Brazil

In the present work we introduce a system identification framework where no a priori information on the system to be identified is available. Focusing in the specific case of radial basis functions neural networks models, we insert the choice of the model complexity and its inputs in the optimization procedure together with the model parameters, aiming at accuracy, model validity and regularization in a multiobjective approach. The multicriteria problem is solved by means of the multiobjective cuckoo search, which is based on an archiving technique and the crowding distance metric. Simulation results are promising when the methodology is applied to identify a robot arm given solely input and output data.

关键词： System Identification Multiobjective optimization Cuckoo Search Multiobjective Cuckoo Search Neural Networks Radial Basis Functions Robotics

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Multiband Patch Antenna Design Using Nature-Inspired Optimization Method

IEEE Open Journal of Antennas and Propagation

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IEEE Open Journal of Antennas and Propagation 2021年 2卷 151-162页

作者： Boursianis, Achilles D. Papadopoulou, Maria S. Pierezan, Juliano Mariani, Viviana C. Coelho, Leandro S. Sarigiannidis, Panagiotis Koulouridis, Stavros Goudos, Sotirios K. ELEDIA@AUTH Research Group School of Physics Aristotle University of Thessaloniki Thessaloniki54124 Greece Department of Electrical Engineering Federal University of Parana Curitiba80060-000 Brazil Industrial and Systems Engineering Graduate Program and Mechanical Engineering Graduate Program Pontifical Catholic University of Parana Curitiba80215-901 Brazil Department of Electrical and Computer Engineering University of Western Macedonia Kozani501 00 Greece Electrical and Computer Engineering Department University of Patras Patras26504 Greece

Radio frequency energy harvesting has attracted considerable interest as a technique of enabling self-powered wireless networks. This technique faces several challenges, such as the receiving and the rectifying modules of a rectenna system. Multiband antennas provide several comparative advantages against the goal of maximizing the amount of energy harvesting. In this work, we present a multiband microstrip patch antenna with three slits operating in the LoRaWAN (Long Range Wide Area Network) and the cellular (GSM-1800 and UMTS) communication frequency bands. A feasible solution of the antenna is obtained by the application of a recently introduced nature-inspired optimization technique, namely the Coyote Optimization Algorithm. The proposed antenna operates satisfactorily in the LoRaWAN (Long Range Wide Area Network) and the cellular (GSM-1800 and UMTS) communication frequency bands. Measured results of the proposed antenna exhibit an acceptable performance (multiband frequency operation, maximum gain of 3.94 dBi, broadside operation) and demonstrate features of operation, which make it a strong candidate for various RF energy harvesting applications. © 2020 IEEE.

关键词： Microstrip antennas

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A method for displacement measurement of femoral head and acetabulum based on tomography images

A method for displacement measurement of femoral head and ac...

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12th IASTED International Conference on Computer Graphics and Imaging, CGIM 2011

作者： Rudek, Marcelo Canciglieri Jr., Osiris Catani, Fábio Industrial and Systems Engineering Graduate Program - PPGEPS Pontifical Catholic University of Parana - PUCPR Imaculada Conceicao Street 1155 - Curitiba-Parana Brazil

ISBN: (纸本)9780889868656

This paper presents a method for visualization of displacement between the centre of the femoral head and acetabulum cavity centre. The measurement is performed in 3D tomography reconstructed images. The femoral head and acetabulum cavity can be represented by synthetic spheres and can be reconstructed based on the slice information of each bone of the joint. With the two spheres it is possible to measure the degree of the displacement between the centres. This representation gives support to the specialized doctors in their diagnostic of hip subluxation in children with cerebral paralysis, once that this problem causes pain because the acetabulum and femur disengagement. The proposal method is a compilation of some computational techniques of image handling such as bone segmentation using Hough Transform, chain code for reduction of the number of the points, Delaunay triangulation to perform a 3D reconstruction and OpenGL graphic library. A software prototype was constructed to validate the method proposed.

关键词： Tomography

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A weblab control experiment using the ball and beam system and multiobjective optimization 5

A weblab control experiment using the ball and beam system a...

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5th Experiment at International Conference, exp.at 2019

作者： Kagami, Ricardo Massao Kovalski Da Costa, Guinther Mendes, Luciano Antonio Freire, Roberto Zanetti Industrial and Systems Engineering Graduate Program-PPGEPS Pontifícia Universidade Católica Do Paraná-PUCPR Curitiba Brazil Department of Control and Automation Engineering Pontifícia Universidade Católica Do Paraná-PUCPR Curitiba Brazil

ISBN: (纸本)9781728136370

y associating active learning methodologies and digital media as a form to improve educational quality, the diversity of experimentations in engineering education has been motivating researches in many areas with possibilities of increasing both students' knowledge and skills. Control engineering is an area where educational laboratories are usually costly, thus the use of virtual laboratories for remote experimentation became an interesting approach. In this work, it is presented a remote experimentation procedure for the ball and beam system, which is a nonlinear and unstable open loop process. Considering the advanced control topic, multiobjective optimization was introduced in the experiment in order to tune Proportional-Integral-Derivative (PID) controllers. Through the description of the system model, the multiobjective optimization technique, and the experiment configuration, students can simulate and test their controllers remotely in a real plant. © 2019 IEEE.

关键词： Multiobjective optimization

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Cascaded evolutionary multiobjective identification based on correlation function statistical tests for improving velocity analyzes in swimming

Cascaded evolutionary multiobjective identification based on...

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IEEE Symposium on Computational Intelligence in Multi-Criteria Decision-Making, MCDM

作者： Helon Vicente Hultmann Ayala Luciano Ferreira da Cruz Roberto Zanetti Freire Leandro dos Santos Coelho Industrial and Systems Engineering Graduate Program PUCPR Curitiba Brazil Department of Electrical Engineering PUCPR UFPR Curitiba Brazil

By using biomechanical analyses applied to sports many researchers are providing important information to coaches and athletes in order to reach better performance in a shorter time. In swimming, these kinds of analyses are being used to evaluate, to detect and to improve the skills of high level athletes. Recently, evolutionary computing theories have been adopted to support swim velocity profile identification. Based on velocity profiles recognition, it is possible to identify distinct characteristics and classify swimmers according to their abilities. In this way, this work presents an application of Radial Basis Function Neural Network (RBF-NN) associated to a proposed cascaded evolutionary procedure composed by a genetic and Multiobjective Differential Evolution (MODE) algorithms as optimization method for searching the best fitness within a set of parameters to configure the RBF-NN. The main goal and novelty of the proposed approach is to enable, through the adoption of cascaded multiobjective optimization, the use of correlation based tests in order to select both the model lagged inputs and the associated parameters in a supervised fashion. Finally, the real data of a Brazilian elite female swimmer in crawl and breaststroke styles obtained into a 25 meters swimming pool have been identified by the proposed method. The soundness of the approach is illustrated with the adherence to the model validity tests and the values of the multiple correlation coefficients between 0.95 and 0.93 for two tests for both breaststroke and crawl strokes, respectively.

关键词： Sociology Correlation Optimization Genetic algorithms Time series analysis Training

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