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检索条件"任意字段=Conference on Simulation-Driven Modeling and Optimization"

共 1171 条记录，以下是211-220 订阅

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A Tool for the Automation of Efficient Multi-Robot Choreography Planning and Execution 22

A Tool for the Automation of Efficient Multi-Robot Choreogra...

引用

ACM/IEEE 25th International conference on Model driven Engineering Languages and Systems (MODELS)

作者： Wete, Eric Greenyer, Joel Kudenko, Daniel Nejdl, Wolfgang Flegel, Oliver Eisner, Dennes Leibniz Univ Hannover Hannover Germany Volkswagen AG Wolfsburg Germany FHDW Hannover Hannover Germany

ISBN: (纸本)9781450394673

In the automotive industry, the design, modeling, and planning of multi-robot cells are manual error-prone, and time-expensive tasks. A recent work investigated, using reactive synthesis, approaches to automate robot task planning, and execution. In this paper, we present a tool that realizes a model-at-runtime approach. The tool is integrated with a robot simulation tool, to automate efficient multi-robot choreography planning, and execution. We illustrate the tool using a multi-robot spot welding cell, inspired from an industrial case. Given a virtual model of the production cell, and user constraints definition, the tool can derive a specification for the reactive synthesis. The tool integrates the synthesized controller with the production cell execution, and in real time, optimizes the strategies by considering the uncertainties. The system can select among several correct, and safe actions, the optimal action using AI-based planning techniques, such as the Monte Carlo Tree Search (MCTS) algorithm. We showcase our tool, illustrate its implementation architecture, including how it can support robot experts for automated planning and execution of production cells.

关键词： model-driven engineering multi-robot motion planning task scheduling reactive synthesis AI-based optimization

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AMPM 2021 - Proceedings of the 1st Workshop on Agent-Based modeling and Policy-Making, co-located with 34th International conference on Legal Knowledge and Information Systems, JURIX 2021

AMPM 2021 - Proceedings of the 1st Workshop on Agent-Based M...

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1st Workshop on Agent-Based modeling and Policy-Making, AMPM 2021

The proceedings contain 10 papers. The topics discussed include: applications of ABM in international legal research: the case of compliancee;dissecting crime through ABM. from theory testing to policy design;exploring the boundaries between law, ABM and policy-making: on the clash between formal and informal norms;at the boundary of law and software: toward regulatory design with agent-based modeling;empirically grounded agent-based policy evaluation of the adoption of sustainable lighting under the European ecodesign directive;simulating pandemic emergency scenarios considering mobility patterns through an agent-based model;portfolio optimization and trading strategies: a simulation approach;using agent-based simulation to investigate behavioral interventions in a pandemic using mobility data;using decentralized conflict-abduction-negation in policy-making;and multi-paradigm modelling for policy-driven socio-technical systems.

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Collaborative optimization of energy management in integrated energy system group based on digital twin technology

Collaborative optimization of energy management in integrate...

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2022 Power System and Green Energy conference, PSGEC 2022

作者： Wang, Xinying Zhao, Rixiao Zhao, Qi Liu, Fengkui Sun, Qingkai Lv, Jinling China Electric Power Research Institute Artificial Intelligence Application Research Department Beijing China School of Electrical Engineering Beijing Jiaotong University Beijing China

ISBN: (数字)9781665499934

ISBN: (纸本)9781665499934

Under the dual pressure of environment and resources, the traditional energy model no longer meets the needs of today's social development, and the energy industry urgently needs transformation and upgrading. Combining integrated energy system groups and digital twin technology has become the primary means of assistance in the transformation process. Therefore, this paper first constructs the technical system framework suitable for the integrated energy system group using digital twin technology. Secondly, the collaborative optimization of energy management among different subjects in the integrated energy system group is carried out under this framework. Finally, the example results show that the technical framework based on digital twin technology can effectively guide the optimization of energy management among different subjects of the integrated energy system group. © 2022 IEEE.

关键词： Energy management

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Ensemble-based Offline Data-driven Evolutionary optimization for Operation Parameter of Blast Furnace

Ensemble-based Offline Data-driven Evolutionary Optimization...

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International conference on Fuzzy Systems and Knowledge Discovery (FSKD)

作者： Qiucheng Ye Hongxia Cai Yunqi Bian Shanghai Key Laboratory of Intelligent Manufacturing and Robotics School of Mechatronic Engineering and Automation Shanghai University Shanghai China

ISBN: (数字)9798350356328

ISBN: (纸本)9798350356335

Stable control of the iron-making process through the adjustment of operating parameters is essential to improve blast furnace productivity. However, due to the complex and dynamic nature of the reaction process, it is difficult to perform accurate modeling and simulation experiments for a blast furnace. This poses great difficulties in performing the evaluation of control strategies in real-time. Offline evolutionary optimization, as an optimization technique that relies only on historical data, enables the search for optimal operation parameters through the introduction of surrogates. Based on the characteristics of historical time-series data of the iron-making process, this study proposes an offline evolutionary optimization method based on advanced time-series surrogates. Ensemble strategy combining surrogates with different prediction time windows contributes robustness during the optimization process. Additionally, multiple sub-regions are maintained to enable extensive searching of the decision space with a multi-objective nature. The efficiency of the proposed pooling method is demonstrated through verification in actual production cases.

关键词： Productivity Accuracy Computational modeling Process control optimization methods Blast furnaces Knowledge discovery Robustness Real-time systems Fuzzy systems

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An Operational Chain optimization Model for Unmanned Swarm Under Dynamic Task Scenarios driven by Resilience

An Operational Chain Optimization Model for Unmanned Swarm U...

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IEEE International conference on Unmanned Systems (ICUS)

作者： Yuanfu Zhong Yuepeng Cai Xuebin Zhuang School of Systems Science and Engineering Sun Yat-sen University Guangzhou China

ISBN: (数字)9798350384185

ISBN: (纸本)9798350384192

In persistent battlefield confrontation, combat tasks present dynamic characteristics, i.e., new tasks continuously emerge as old tasks are executed. Therefore, how to enhance the battlefield resilience of unmanned swarm (US) through the rational allocation of limited resources in this scenario has become the focus of research. In response, this paper proposes an operational chain optimization model for the US, which provides modeling and resilience enhancement ideas for the dynamic nature of battlefield tasks. Subsequently, the feasibility and effectiveness of the proposed model is demonstrated under simulation experiments in different attack scenarios.

关键词： Location awareness Autonomous systems optimization models Decision making Feature extraction Trajectory Resource management Artificial intelligence optimization Resilience

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Fast History Matching with a Customized Physics-Based Data-driven Flow Network Model GPSNet: Application to a Giant Deep-Water Gas Field

Fast History Matching with a Customized Physics-Based Data-D...

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2024 SPE Annual Technical conference and Exhibition, ATCE 2024

作者： Guan, X. Wang, Z. Ren, G. Hui, M. Kazanov, D. Wen, X.-H. Chevron Technical Center United States Chevron Corporation United States

ISBN: (纸本)9781959025375

History matching with full-fidelity reservoir models could be a computationally expensive task. We have previously implemented a novel physics-based data-driven surrogate model (GPSNet) and used it for rapid history matching and optimization for waterflood and steamflood applications in mature fields. In this work, we construct a GPSNet model with customized network configurations to capture reservoir volume and connectivity distributions with associated uncertainties and demonstrate a successful application to a deep-water giant gas reservoir in Northern Carnarvon Basin offshore Australia. This GPSNet model incorporates both current wells in-production and pseudo wells placed across the reservoir. A flow network is constructed using a network of one-dimensional (1-D) connections that link production-production wells, production-pseudo wells, and pseudo-pseudo wells. Both pseudo wells and connections in the network were designed following our best understanding of reservoir connectivity and uncertainty. Connections are grouped into different categories to account for regional variations at different scales. Reservoir properties are calibrated from historical data through a sequential history match process typical for GPSNet modeling: The average reservoir properties of each connection group were first inferred using Design of Experiment (DoE) and Generic Algorithm (GA);Then, excellent history matching results were achieved by adjusting pore volumes and transmissibilities to match build-up pressures and by adjusting completion-level producer well index and non-Darcy effects to match flowing bottom hole pressures using Ensemble Smoother with Multiple Data Assimilation (ESMDA). With 200 connections among 39 producers and pseudo wells, the typical run time of this GPSNet model is several minutes which is almost two orders of magnitude faster than a full-physics 3-D model. The integration with a commercial simulator also makes it feasible to extend GPSNet to depict compl

关键词： Decision making

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DEVS-Based modeling and simulation of Data-driven Exploration Algorithms of Lentic Water Bodies with AN ASV

DEVS-Based Modeling and Simulation of Data-Driven Exploratio...

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Annual modeling and simulation conference (ANNSIM)

作者： Samuel Ferrero-Losada Eva Besada-Portas José L. Risco-Martín José A. López-Orozco Department of Computer Architecture and Automation Universidad Complutense de Madrid Madrid Spain

This paper presents a Discrete Event System Specification (DEVS) modular architecture for modeling and simulating the behavior of an Autonomous Surface Vehicle (ASV), guided by gradient-free optimization and contour detection algorithms, while searching the extreme points and constant curves of a variable of interest in a water body. The ASV model integrates its dynamic differential equations and is controlled by a Guidance, Navigation, and Control (GNC) system implemented through several atomic models to facilitate changes in the behavior of any of them and test different types of regulators and guidance approaches in the future. The paper results show that the system is working correctly for the already supported missions (seeking extreme points and contour curves) and that adapting the specification to each of them is possible by modifying one of the models of the GNC.

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Radio-in-the-Loop simulation modeling for Energy-Efficient and Cognitive IoT in Smart Cities: A Cross-Layer optimization Case Study

Radio-in-the-Loop Simulation Modeling for Energy-Efficient a...

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Annual conference on Wireless On Demand Network Systems and Services (WONS)

作者： Sebastian Boehm Hartmut Koenig Communications Department ZITiS Munich Germany

Wireless communication technologies and Internet of Things (IoT) applications are the main drivers of upcoming sustainable Smart City networks which require an effective resource management. The reduction of the transmission energy consumption and the efficient utilization of the available spectrum for wireless communication, for instance, have to be enabled by energy-efficient and cognitive IoT networks. These are implemented through optimized communication protocol stacks and algorithms that rely on actual physical layer and channel state information. The modeling and the prototype evaluation of protocol optimization approaches are mainly driven by pure simulation studies with abstracted physical layer and channel models. With the Radio-in-the-Loop (RIL) simulation [1] and modeling [2], we have created an evaluation approach that integrates real wireless hardware and radio environments into the simulation of protocol sequences and algorithms. In this paper, we demonstrate a cross-layer optimization case study for energy efficient modeling using software-defined radios alongside this basic methodology. We exemplary show the scenario of a receiver-sensitivity control to increase the energy efficiency of receiver-dominated IoT nodes in Smart City networks.

关键词： Wireless sensor networks Cross layer design Protocols Smart cities Physical layer Energy efficiency Internet of Things

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Two-Stage Optimal Dispatching for Active Distribution Networks Considering the modeling of Power and Energy Balance

Two-Stage Optimal Dispatching for Active Distribution Networ...

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Electrical Engineering and Control Technologies (CEECT), conference on

作者： Yuyuan Cao Dawen Huang Feng Li Biwei Li Lei Chen Man Yang Musi Li Hongkun Chen Zhaoqing Power Supply Bureau Guangdong Power Grid Co. Ltd. CSG Zhaoqing China School of Electrical Engineering and Automation Wuhan University Wuhan China

ISBN: (数字)9798331528096

ISBN: (纸本)9798331528102

driven by the global energy transformation and carbon neutrality goals, the efficient operation and optimal dispatching of distribution networks are essential. This paper proposes a two-stage dispatching strategy that combines economic optimization and reactive power optimization for active distribution networks (ADNs) by considering the power and energy balance. When constructing the economic optimization model, the power and energy balance constraints are fully considered to guarantee the supply as well as demand balance in each period. The improved NSGAII-MOPSO algorithm solves the model to decrease the operating costs and carbon emissions of the ADNs. The dispatching strategy also optimizes the adjustable loads to achieve peak shaving and valley filling, thereby improving flexibility and economy. The simulation validations are implemented on the IEEE 33-node system containing renewable energy sources, which verifies the effectiveness of the proposed two-stage strategy.

关键词： Renewable energy sources Reactive power Costs optimization models Dispatching Stability analysis Scheduling Active distribution networks optimization Load modeling

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Research on Hybrid Mechanistic and Data-driven modeling of Wind Turbines Based on Particle Swarm optimization

Research on Hybrid Mechanistic and Data-Driven Modeling of W...

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IEEE International conference on Energy Internet (ICEI)

作者： Zhanyang Ji Xiyang Wang Shuai Wang School of Control and Computer Engineering North China Electric Power University China

ISBN: (数字)9798331523558

ISBN: (纸本)9798331523565

In response to the complex nonlinear operational characteristics of large wind turbines, a hybrid semi-mechanistic modeling method for multi-condition operations is proposed, based on a refined 5MW wind turbine model and co-simulation using FAST and Simulink. First, a complex nonlinear mechanistic model is constructed through mechanistic analysis, identifying the input and output variables, and completing data collection. Then, the aerodynamic system is linearized using a Taylor expansion, and an incremental model is built for key nonlinear components at steady-state operating points. Finally, guided by mechanistic insights, the particle swarm optimization (PSO) algorithm is applied to refine the aerodynamic partial derivatives, optimizing the results of the model linearization. The conclusions show that the proposed modeling method retains advantages of speed and precision under various operating conditions, while preserving the physical meaning of model parameters. This method effectively captures the complex nonlinear response characteristics of wind turbines across different operating conditions, laying the foundation for wind turbine condition monitoring and controller research.

关键词： Parameter estimation Software packages Wind speed Aerodynamics Taylor series Mathematical models Wind turbines Steady-state Particle swarm optimization MATLAB

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