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检索条件"任意字段=21st Conference on System Modeling and Optimization"

共 3611 条记录，以下是91-100 订阅

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Fuzzy Logic Empowerment for Thermoelectric Transducer Performance optimization 21

Fuzzy Logic Empowerment for Thermoelectric Transducer Perfor...

引用

21st International Multi-conference on systems, Signals and Devices, SSD 2024

作者： Derbel, Achraf Trigona, Carlo Baccar, Noura Mediterranean Institute of Technology South Mediterranean University Departement of Computer Systems Eng. Tunisia Università Degli Studi di Catania DIEEI Dipartimento di Ingegneria Elettrica Elettronica e Informatica Italy

ISBN: (纸本)9798350374131

This research paper explores the integration of Thermoelectric Generators (TEGs) as dual-function components in wearable devices, serving as both energy harvesters and fuzzy logic-enhanced actuators. The study presents experi-mental results highlighting the TEG's performance in harvesting energy from applied temperature gradients. The harvested energy can power the wearable device, addressing the demand for sus-tainable power sources in various fields including healthcare applications. Additionally, the paper introduces the application of fuzzy logic systems to refine the TEG's role as an actuator. It is worth noting that the TEG's voltage output is utilized to measure temperature variations, and the fuzzy logic system interprets these inputs to optimize alert system responses. This amalgamation of TEGs and fuzzy logic offers a novel approach to enhance the accuracy and responsiveness of temperature-sensitive alert systems. The research findings provide valuable insights into the potential of this integrated system for advancing wearable and medical device technology. © 2024 IEEE.

关键词： Energy harvesting

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Parameter Identification and Fault Diagnosis of Servo system Based on Improved PSO Algorithm 21

Parameter Identification and Fault Diagnosis of Servo System...

引用

21st IEEE International conference on Mechatronics and Automation (IEEE ICMA)

作者： Jiao, Shiting Wang, Youming Miao, Xuyang Li, Zhen Pang, Ji Wang, Xianzhi Xian Univ Posts & Telecommun Sch Automat Xian 710121 Peoples R China

ISBN: (纸本)9798350388084;9798350388077

The capture of nonlinearity in servo systems during operation is significant for fault diagnosis, which can greatly reduce the probability of system failure throughout the life cycle. To address the problem, a step-by-step identification method based on iterative optimization mutation particle swarm optimization (S-IPV-PSO) is proposed for fault diagnosis. Firstly, an iterative optimization mutation particle swarm optimization (IPV-PSO) is presented to improve convergence speed and algorithm accuracy by optimizing the learning factor and inertia weight coefficient. Secondly, a Hammerstein model is established to identify the parameters for predicting different states of the system by using the IPV-PSO algorithm, where inverse M signal is used as an output to separate between the nonlinear and linear parts of the system. Finally, a servo system simulation with dead time characteristics is built to verify the effectiveness of the proposed algorithm. Extensive experiments demonstrate that the proposed method can effectively identify fault states and has better convergence speed and recognition error.

关键词： Servo system Fault diagnosis Iterative optimization mutation particle swarm optimization Hammerstein model

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modeling and Exploiting Dominance Rules for Discrete optimization with Decision Diagrams 1

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21st International conference on the Integration of Constraint Programming, Artificial Intelligence, and Operations Research (CPAIOR)

作者： Coppe, Vianney Gillard, Xavier Schaus, Pierre UCLouvain Louvain La Neuve Belgium

ISBN: (数字)9783031605970

ISBN: (纸本)9783031605963;9783031605970

Discrete optimization with decision diagrams is a recent approach to solve combinatorial problems that can be formulated with dynamic programming. It consists in a branch-and-bound algorithm that iteratively explores the search space by compiling bounded-width decision diagrams. Those decision diagrams are used both to subdivide a given problem into smaller subproblems - in a divide-and-conquer fashion - and to compute primal and dual bounds for those. It has been previously shown that pruning performed during the compilation of those decision diagrams can greatly impact the quality of the bounds, and consequently the performance of the branch-and-bound algorithm. In this paper, we study the integration of dominance rules inside the decision diagram-based optimization framework. We propose a modeling language for consistently formulating dominance rules for dynamic programming models, and describe how they can be exploited to systematically detect and prune dominated nodes during the search. Furthermore, we explain how to combine this additional filtering mechanism with caching techniques to further improve the performance of the algorithm. Dominance rules are shown to significantly reduce the number of nodes expanded and the running time of the algorithm on four optimization problems.

关键词： Decision diagrams Branch-and-bound Dominance rules

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Proceedings of the 21st International conference on Smart Business Technologies, ICSBT 2024

Proceedings of the 21st International Conference on Smart Bu...

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21st International conference on Smart Business Technologies, ICSBT 2024

ISBN: (纸本)9789897587108

The proceedings contain 16 papers. The topics discussed include: computing: looking back and moving forward;hidden champions revised: towards a new conceptual framework;enhancing returns management in fashion e-commerce: industry insights on AI-based prediction and recommendation systems;comparative analysis of machine learning techniques for DDoS intrusion detection in IoT environments;artificial neural network model for predicting excavator downtime;framework for modeling the propagation of disturbances in smart construction sites;sentiment analysis-based chatbot system to enhance customer satisfaction in technical support complaints service for telecommunications companies;Business-RAG: information extraction for business insights;and speech recognition for inventory management in small businesses.

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CEFC 2024 - 21st IEEE Biennial conference on Electromagnetic Field Computation

CEFC 2024 - 21st IEEE Biennial Conference on Electromagnetic...

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21st IEEE Biennial conference on Electromagnetic Field Computation, CEFC 2024

ISBN: (纸本)9798350348958

The proceedings contain 305 papers. The topics discussed include: loss calculation of iron core under dc bias and harmonic disturbance conditions;physics-informed conditional generative adversarial network for inverse electromagnetic problems;a study on the design of novel slotless axial flux motor through comparison with radial flux motor for collaborative robot;study on rotor bar loss due to space harmonics of line start synchronous reluctance motor;electromagnetic field analysis using physics informed neural network considering eddy current;characteristic analysis of two-phase stator-permanent-magnet hybrid stepping machines with radial and tangential magnetization;DC-link voltage control strategy considering vessel condition for efficiency improvement of IH cooktops with PFC rectifier;measurement uncertainty of Schumann resonances with the EFIELD experiment on board dragonfly;fast estimation system of permanent magnet magnetization using 2D-arrayed hall sensors combined with deep neural network;and simplified optimization of curved barrier in synchronous reluctance motor.

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2024 21st Annual IEEE International conference on Sensing, Communication, and Networking, SECON 2024

2024 21st Annual IEEE International Conference on Sensing, C...

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21st Annual IEEE International conference on Sensing, Communication, and Networking, SECON 2024

ISBN: (纸本)9798331519186

The proceedings contain 42 papers. The topics discussed include: resource-efficient sensor fusion via system-wide dynamic gated neural networks;a large-scale P2P botnet detection framework via topology and traffic co-verification;resource allocation and task offloading for slicing-based communication and computing in space-air-ground integrated networks;topology design with resource allocation and entanglement distribution for quantum networks;driving important scene detection based on user preferences;beta: a novel learning-based adaptive streaming approach with spatial and temporal optimization;scalable and distributed optimization of shared 3D object quality for large-scale hybrid-metaverses;budget-constrained traveling salesman problem: a cooperative multi-agent reinforcement learning approach;and an intelligent prefetch strategy with multi-round cell enhancement in volumetric video streaming.

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optimization Scheduling Method for County-level Distribution Network Considering Multi-function Reuse of Mobile Energy storage system 21

Optimization Scheduling Method for County-level Distribution...

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21st International conference on Harmonics and Quality of Power

作者： Zhu, Xinyi Ma, Longyi Shen, Zikang Shen, Xinhao Lu, Dongxu Guo, Jiacai Lin, Zhenzhi Zhejiang Univ Coll Elect Engn Hangzhou Peoples R China Huizhou Power Supply Co Guangdong Power Grid Co Ltd Huizhou Peoples R China

ISBN: (纸本)9798350382570;9798350382563

In the context of the carbon neutrality goal and the rising penetration of renewable energies, the electrical power system's dependency on renewable energy sources, including photovoltaic (PV) and wind generation, has markedly increased. However, the generation of renewable energy is heavily dependent on climatic conditions, and its volatility can bring pressure to the power balance of the distribution network. The application of mobile energy storage system (MESS) will become a strong support for the extensive expansion of renewable energy sources. Hence, an optimal scheduling method for county-level distribution networks (CDNs) considering the multi-function reuse of MESS is proposed. Firstly, the application scenarios and necessity of multi-function reuse of MESS under the context of a significant share of renewable energy sources are analyzed. Then, an optimal scheduling method considering MESS is constructed, aiming at reducing the overall operating expenses of the CDN, as well as the constraints such as the spatiotemporal dynamic scheduling of MESS. Finally, a revised 33-bus distribution network is applied for case studies. The simulation results demonstrate that the proposed model is applicable to different scenarios of the CDN under various application functions of MESS, effectively reducing the operational costs of the CDN and ensuring the power supply for load demand.

关键词： mobile energy storage system county-level distribution network short-term overload peak regulation emergency response optimal scheduling renewable energy integration

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An adapation Framework for Industry 4.0 Responsive Production systems 21

An adapation Framework for Industry 4.0 Responsive Productio...

引用

IEEE 21st International conference on Industrial Informatics (INDIN)

作者： Mabkhot, Mohammed M. Lohse, Niels Ferreira, Pedro Loughborough Univ Wolfson Sch Mech Elect & Mfg Engn Intelligent Automat Ctr Loughborough Leics England

ISBN: (纸本)9781665493130

One of the key aims of Industry 4.0 is to create more responsive systems. Responsiveness and adaptation enable coping with new market requirements or introducing new products, as demonstrated by the challenges posed by COVID-19. Despite the economic and sustainability benefits, practitioners often only consider adapting their systems for limited cases. They rely on simple, intuitive estimates of adaptation metrics and do not optimize these milestone decisions, leading to missed opportunities. Currently, there are no reliable methods for measuring system adaptability, quantifying the effort required to adapt it from one state to another, or optimizing the adaptation decision. This paper proposes a comprehensive adaptation framework based on complexity index quantification, graph network estimation, and multi-objective optimization. The framework outlines three approaches for estimating efforts in adapting the physical system design, upgrading control software, and optimizing the adaptation decision. The application on a lab-sized cell demonstrates the framework's ability to estimate the adaption processes metric and generate a set of optimized cell states. The application reveals potentials for improvement and extension of the three approaches.

关键词： Effort estimation physical redesign adaptation software control upgrade adaptation optimization system resilience and responsiveness

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optimization of Transmit Beamforming Using Channel Covariances for MISO Downlink Assisted by Reconfigurable Intelligent Surfaces 21

Optimization of Transmit Beamforming Using Channel Covarianc...

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21st International conference on Electrical Engineering/Electronics, Computer, Telecommunications and Information Technology (ECTI-CON)

作者： Kyaw, Khin Thandar Santipach, Wiroonsak Mamat, Kritsada Kaemarungsi, Kamol Fukawa, Kazuhiko Kasetsart Univ Fac Engn Dept Elect Engn Bangkok Thailand King Mongkuts Univ Technol North Bangkok Coll Ind Technol Dept Elect Engn Technol Bangkok Thailand Natl Sci & Technol Dev Agcy Natl Elect & Comp Technol Ctr Pathum Thani Thailand Tokyo Inst Technol Sch Engn Dept Informat & Commun Engn Tokyo Japan

ISBN: (纸本)9798350381566;9798350381559

We propose an unsupervised beamforming neural network (BNN) to optimize transmit beamforming in downlink multiple input single output (MISO) channels. Reconfigurable intelligent surface (RIS) panels are used to assist user equipment that does not receive sufficiently s trong s ignals f rom t he base station. To avoid frequent beam updates, the proposed BNN is based on slow-changing channel covariances and is different from most other BNNs that utilize instant channel state information. Numerical simulations show that the proposed BNN can achieve much higher sum rates than zeroforcing beamforming does when the system is heavily loaded and can drastically reduce computation time for large-scale communication systems.

关键词： Beamforming optimization downlink RIS channel covariance MISO neural network

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A Comprehensive study of Artificial Neural Networks in Power system stability 21

A Comprehensive Study of Artificial Neural Networks in Power...

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21st International Multi-conference on systems, Signals and Devices, SSD 2024

作者： Alhalim, Shaimaa Shukri Abd. Bahloul, Wissem Chtourou, Mohamed Derbel, Nabil University of Technology Department of Electrical Engineering Baghdad Iraq Sfax Tunisia

ISBN: (纸本)9798350374131

The stability of the power system is important for ensuring the power grid's reliable operation. Traditional stability analysis and stabilization methods have limitations in handling the complexity and nonlinearity of modern power systems. The combination of artificial neural network (ANN)based approaches holds particular promise for power system stability and addressing stabilization challenges. This paper aims to investigate the use of neural methods to improve the analysis and stabilization of complex power systems. Research will focus on neural network architectures and algorithms that can accurately predict and ensure the stability of power systems under various operating conditions. By using neural networks, the research aims to overcome the limitations of traditional methods and provide intelligent solutions to ensure the stability and the robustness of power systems in the face of challenges in the ongoing process. This comprehensive review provides in-depth insights into the applications, techniques, and advancements of ANN in power system stability analysis and control. The study includes ANN basic principles and appropriateness to model complex nonlinear relationships in dynamical systems and evaluate them, including feedforward. This study looks into how ANNs can be used to improve system stability and response to disturbances in areas like fault detection, dynamic modeling, control strategies, and stability assessment. © 2024 IEEE.

关键词： Neural networks

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