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Nonlinear System Identification Based on B-Spline Neural Network and Modified Particle Swarm Optimization

Nonlinear System Identification Based on B-Spline Neural Net...

引用

International Joint Conference on Neural Networks (IJCNN)

作者： L. dos Santos Coelho R.A. Krohling Production and Systems Engineering Graduate Program Automation and Systems Laboratory PPGEPS/CCET/PUCPR Pontifical Catholic University of Paraná Parana Brazil Chair for Control Systems Engineering RST Faculty of Electrical Engineering and Information Technology University of Dortmund Dortmund Germany

Artificial neural networks, in particular, feedforward multilayer networks and basis function networks, have gradually established themselves as a usual tool in approximating complex nonlinear systems. B-spline networks, a type of basis function neural network, are normally trained by gradient-based methods, which may fall into local minima during the learning phase. In order to overcome the drawbacks encountered by conventional learning methods, particle swarm optimization - a swarm intelligence methodology - can provide a stochastic global search of B-spline networks for nonlinear system identification. In this paper, a modified particle swarm optimization algorithm using Gaussian and Cauchy probability distributions are applied to adjust the control points of B-spline neural networks. Simulation results for the identification of Rossler systems are provided and demonstrate the effectiveness and robustness of the proposed identification scheme.

关键词： Nonlinear systems Spline Neural networks Particle swarm optimization Artificial neural networks Multi-layer neural network Learning systems Stochastic systems Probability distribution Robustness

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Supply Chain Optimization Using Chaotic Differential Evolution Method

Supply Chain Optimization Using Chaotic Differential Evoluti...

引用

IEEE International Conference on systems, Man and Cybernetics

作者： Leandro dos Santos Coelho Heitor Silverio Lopes Production and Systems Engineering Graduate Program Automation and Systems Laboratory Pontifical Catholic University of Paraná Curitiba Parana Brazil UTFPR/CPGEI Federal Technological University of Parana Curitiba Parana Brazil

This paper describes the application of differential evolution approaches to the optimization of a supply chain. Although simplified, this supply chain included stocks, production, transportation and distribution, in an integrated production-inventory-distribution system. The supply chain problem model is presented as well as a short introduction to each evolutionary algorithm. Differential evolution (DE) is an emergent evolutionary algorithm that offers three major advantages: it finds the global minimum regardless of the initial parameter values, it involves fast convergence, and it uses few control parameters. Inspired by the chaos theory, this work presents a new global optimization algorithm based on different DE approaches combined with chaotic sequences (DEC), called chaotic differential evolution algorithm. The performance of three evolutionary algorithm approaches (genetic algorithm, DE and DEC) and branch and bound method were evaluated with numerical simulations. Results were also compared with other similar approach in the literature. DEC was the algorithm that led to better results, outperforming previously published solutions. The simplicity and robustness of evolutionary algorithms in general, and the efficiency of DEC, in particular, suggest their great utility for the supply chain optimization problem, as well as other logistics-related problems.

关键词： Supply chains Optimization methods Chaos Evolutionary computation Production systems Transportation Convergence Genetic algorithms Numerical simulation Robustness

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Chaotic Differential Evolution Applied to Electromagnetics Optimization

Chaotic Differential Evolution Applied to Electromagnetics O...

引用

IEEE Conference on Electromagnetic Field Computation

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

This work presents a new global optimization algorithm based on differential evolution (DE) method and DE combined with chaotic sequences (DEC) given by logistic map. In this paper, the optimal shape design of Loney's solenoids benchmark problem is carried out by DE and DEC algorithms. The results of DE and DEC approaches are also investigated and their performance compared with those reported in the literature

关键词： Chaos Solenoids Optimization methods Evolutionary computation Stochastic processes Genetic mutations Logistics Algorithm design and analysis Design optimization Electronic mail

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Enhancing IoT Intrusion Detection with Federated Learning-Based CNN-GRU and LSTM-GRU Ensembles

Enhancing IoT Intrusion Detection with Federated Learning-Ba...

引用

International Symposium on Wireless Communication systems (ISWCS)

作者： Ogobuchi Daniel Okey Demostenes Zegarra Rodriguez João Henrique Kleinschmidt Center for Engineering Modeling and Applied Social Sciences Federal University of ABC São Paulo Brazil Graduate Program in Systems and Automation Engineering Federal University of Lavras Minas Gerais Brazil

ISBN: (数字)9798350362510

ISBN: (纸本)9798350362527

The Internet of Things (IoT) devices have been identified to have low security measures by default, thus making them highly vulnerable to malicious attacks. Machine learning-based intrusion detection systems (IDS) are used to mitigate these attacks, however, there is a compromise in security and privacy of data ownership between IoT devices. This paper proposes a Federated Ensemble IDS (CNN-GRU and LSTM-GRU) for monitoring IoT network activities using Convolutional Neural Network (CNN), Gated Recurrent Unit (GRU) and Long-Short Term Memory (LSTM) networks that classifies the network as either normal or malicious. Two aggregation functions, including wFedAvg and wFedProx, are developed to create a global model from different clients’ contribution. We perform an evaluation of the proposed IDS on CICIoT2023 and FLNET2023 datasets. The results show that with wFedAvg, the CNN-GRU achieved an accuracy of 98.25% and 99.25% on the CICIoT2023 and FLNET2023 datasets respectively. Additionally, the LSTM-GRU model shows a detection accuracy of 93.36% and 95.66%, respectively on CICIoT2023 and FLNET2023 datasets. The performance shows that the proposed method is robust enough to enhancing the privacy of IoT devices.

关键词： Wireless communication Accuracy Intrusion detection Telecommunication traffic Robustness Internet of Things Convolutional neural networks

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The Creation and Application of a Simulator in Educational Robotics Classes

The Creation and Application of a Simulator in Educational R...

引用

IEEE Latin American Robotics Symposium, LARS

作者： Carla Fernandes Sarah Thomaz Renata Pitta Luiz Marcos Goncalves Post-Graduate Program in Electrical and Computer Engineering Federal University of Rio Grande do Norte Natal RN Brazil Department of Computer and Automation Engineering Federal University of Rio Grande do Norte Natal RN Brazil

ISBN: (纸本)9781479934775

Educational robotics classes consist of the use of robots in classes that involve interdisciplinary or social themes, creating innovative learning environments involving the use of such technology. In the usually known approach, educational robotics uses robotics kits. We developed a robotic simulator, called S-Educ, which can be used as an alternative or in association with robotics kits in classes involving the use of robotics. Simulators are not replacements of robotics kits, but an alternative for cases where the kits can not be used or they are not appropriate. Tests were carried out to analyze the use of the simulator, obtaining good results on the application of this simulator in educational robotics classes.

关键词： Robot sensing systems Virtual environments Mobile robots Actuators Wheels

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A stochastic method for characterization of soft magnetic material with a damped LC circuit

A stochastic method for characterization of soft magnetic ma...

引用

IEEE Conference on Electromagnetic Field Computation

作者： Paulo R. Eckert Luiz A. Righi Aly F. Flores Filho Joao M. Kanieski Post-Graduate Program in Electrical Engineering Federal University of Rio Grande do Sul RS Brazil Department of Electromechanical and Power Systems Federal University of Santa Maria RS Brazil

ISBN: (纸本)9781509010332

This paper presents a method to determine hysteresis parameters of an inductor's core with a closed magnetic circuit based on electric current and voltage curves of a damped LC circuit. The proposed procedure makes use of the concept of hysteresis modeling by separating the magnetic field into four components, which can be linearized in terms of its parameters. Thus, curves can be adjusted with a stochastic method in order to match experimental ones, allowing for determination of hysteresis parameters.

关键词： Magnetic hysteresis Integrated circuit modeling Stochastic processes Soft magnetic materials Magnetic fields Standards Data models

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Heuristic Methodology for Horizontal Multilayer Soil Stratification

Heuristic Methodology for Horizontal Multilayer Soil Stratif...

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IEEE International Conference on Environment and Electrical engineering

作者： Diogo N. Oliveira Carlos L.B. Silva Wesley P. Calixto Aylton J. Alves Viviane Gomes José Luís Domingos Graduate Program in Electronic and Automation Systems Engineering University of Brasilia Brasilia Brazil Experimental Technological Research and Study Group Federal Institute of Education Science and Technology Goiania Brazil

ISBN: (纸本)9781509023219

Soil Stratification methods are used to estimate soil geoelectrical parameters. Several stratification methods are available, but reducing the error estimation introduced by such methods still poses as a challenge. The purpose of this work is to present a heuristic algorithm applied to the optimization of geoelectrical prospection process. The goal is to estimate soil parameters, such as the amount of layers, thickness and resistivity of each layer in an optimal and automated manner. The algorithm consists of analyzing the sensitivity of sampling space parameters. The propose methodology shows error reduction above 75% between the experimental and theoretical curves of the analyzed soils. The results are presented and discussed.

关键词： Heuristic algorithm soil stratification parameter sensitivity

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Fuzzy-neuro predictive control, tuned by genetic algorithms, applied to a fermentation process

Fuzzy-neuro predictive control, tuned by genetic algorithms,...

引用

IEEE International Symposium on Intelligent Control (ISIC)

作者： J.A. Fabro L.V.R. Arruda Automation and Advanced Control Systems Labratory-LASCA Graduate Program on Electrical Engineering and Applied Computer Science-CPGEI Federal Centre of Technological Education of Paraná Curitiba Parana Brazil

This paper proposes the development of a fuzzy predictive control. Genetic algorithms (GA's) are used to automatically tune the controller. A recurrent neural network is used to identify the process, and then provides predictions about the process behavior, based on control actions applied to the system. These predictions are used by the fuzzy controller, in order to accomplish a better control of an alcoholic fermentation process from chemical industry. This problem has been chosen due to its non-linearity and large accommodation time, that make it hard to control by standard controllers. Comparison of performance is made with non-predictive approaches(PID and Fuzzy-PD), and also with another predictive approach, GPC(Generalized Predictive Control).

关键词： Predictive control Genetic algorithms Control systems Fuzzy control Alcoholism Recurrent neural networks Nonlinear control systems Artificial intelligence Biomass Control system synthesis

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PV Microgeneration Perspective in Brazil: Approaching Interconnection Procedures and Equipment Certification

PV Microgeneration Perspective in Brazil: Approaching Interc...

引用

IEEE Green Technologies Conference (IEEE-Green)

作者： A.M.S. Alonso F.P. Marafão F.A.S. Gonçalves H.K.M. Paredes A.C.G. Martins D.I. Brandao Group of Automation and Integrated Systems São Paulo State University (Unesp) Sorocaba Brazil Graduate Program in Electrical Engineering Federal University of Minas Gerais Belo Horizonte Brazil

Considering that distributed microgeneration systems are one of the most prominent trends in adding flexibility to the Brazilian energy matrix, regulation and certification standards become key players on providing well established interconnection procedures to the electrical power system, without degrading power quality and offering fair services to all institutions. Thus, this paper presents relevant information regarding to how the local interconnection procedures occur, as well as it presents different considerations on certification requirements for grid-tied inverters and PV modules available on the Brazilian market. Moreover, an overview of current constraints is raised, based on the comparison with other worldwide known standards and conditions for distributed energy systems.

关键词： Inverters Certification Biological system modeling IEC Standards Power generation Power quality

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Creating Mathematical Models to Help Formulate Company Strategies for Knowledge Management System Implementation

Creating Mathematical Models to Help Formulate Company Strat...

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International Conference on Information Management and Technology (ICIMTech)

作者： Wahyu Sardjono Widhilaga Gia Perdana Dewi Sagita Pranata Information Systems Management Department BINUS Graduate Program Master of Information Systems Management Bina Nusantara University Jakarta Indonesia Post Graduate Program of Management Science State University of Jakarta Jakarta Indonesia Department of Informatics Cyber Security Studi Program Faculty of Natural Mathematical & Engineering Sciences King's College London Strands West Minster UK

ISBN: (数字)9798350390025

ISBN: (纸本)9798350390032

This research aims to build a mathematical model to formulate the problems of implementing knowledge management systems in companies that often face obstacles in achieving the desired objectives and goals. With increasing competition in the business sector, organizations or organizations realize the importance of utilizing the knowledge assets that reside in each individual and organization. If this knowledge can be managed optimally, it can become a competitive advantage for the company due to the emergence of innovative ideas by the concepts of knowledge management theory. By implementing optimal knowledge management (KM), companies can design innovative solutions to improve business operations and increase overall revenue. The factor analysis method will be used to find the determining factors for the success of the implementation of knowledge management systems (KMS) and the regression analysis method will also be used to form a mathematical model of several new factors which are formed as independent variables with the current level of community understanding of KMS as the dependent variable. The research results provide insight into strategies to improve success factors to successfully facilitate KMS implementation. This study contributes to existing knowledge management by providing insight into dynamics that go beyond the technical aspects of KMS, ultimately developing strategies for more effective and efficient utilization of knowledge and organizational growth and supporting competitive advantage for companies.

关键词： Performance evaluation Knowledge acquisition Collaboration Companies Knowledge management Mathematical models Regression analysis Information management Problem-solving System implementation

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