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检索条件"任意字段=International Conference on Complex Systems: Control and Modeling Problems"

共 12202 条记录，以下是211-220 订阅

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28th international conference on Engineering of complex Computer systems, ICECCS 2024

28th International Conference on Engineering of Complex Comp...

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28th international conference on Engineering of complex Computer systems, ICECCS 2024

ISBN: (纸本)9783031664557

The proceedings contain 22 papers. The special focus in this conference is on Engineering of complex Computer systems. The topics include: Automated Parameter Determination for Enhancing the Product Configuration System of Renault: An Experience Report;optimal Solution Guided Branching Strategy for Neural Network Branch and Bound Verification;AccMILP: An Approach for Accelerating Neural Network Verification Based on Neuron Importance;Word2Vec-BERT-bmu:Classification of RISC-V Architecture Software Package Build Failures;Test Architecture Generation by Leveraging BERT and control and Data Flows;less is More: An Empirical Study of Undersampling Techniques for Technical Debt Prediction;modeling and Verification of Solidity Smart Contracts with the B Method;template-Based Smart Contract Verification: A Case Study on Maritime Transportation Domain;QuanSafe: A DTBN-Based Framework of Quantitative Safety Analysis for AADL Models;a Event-B-Based Approach for Schedulability Analysis For Real-Time Scheduling Algorithms through Deadlock Detection;Validation of RailML Using ProB;reachability Analysis of Concurrent Self-modifying Code;an Iterative Formal Model-Driven Approach to Railway systems Validation;an Efficient Distributed Dispatching Vehicles Protocol for Intersection Traffic control;confidentiality Management in complex systems Design;analyzing Excessive Permission Requests in Google Workspace Add-Ons;formal Verification Techniques for Post-quantum Cryptography: A Systematic Review;autoWeb: Automatically Inferring Web Framework Semantics via Configuration Mutation;safePtrX: Research on Mitigation of Heap-Based Memory Safety Violations for Intel x86-64;towards Efficiently Parallelizing Patch-Space Exploration in Automated Program Repair.

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Formation of the Flight Path of a Quadcopter under Overland Monitoring by the Hybrid modeling System 5

Formation of the Flight Path of a Quadcopter under Overland ...

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5th international conference on problems of Cybernetics and Informatics, PCI 2023

作者： Abbasov, Ali Rzayev, Ramin Habibbayli, Tunjay Institute of Control Systems of the Ministry of Science and Education of Republic of Azerbaijan Laboratory of Information Decision Support Systems Baku Azerbaijan Institute of Control Systems of the Ministry of Science and Education of Republic of Azerbaijan Baku Azerbaijan Inst. of Information Technology of the Ministry of Science and Education of Republic of Azerbaijan Baku Azerbaijan

ISBN: (纸本)9798350319064

The purpose and objectives of this work are to develop methods for designing hybrid control systems for poorly formalized technical objects related to helicopter-type unmanned aerial vehicles, namely quadcopters. The result of the article is to obtain analytical information regarding the appropriate structure of a hybrid (neuro-fuzzy) controller, understanding the features of its design and practical use. The results obtained differ from analogues by a greater orientation in relation to the control of quadcopters based on the Neural Network based Fuzzy Inference System. © 2023 IEEE.

关键词： Fuzzy inference

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Methodology for Energy-efficient Heat Removal control of the Transmitting complex of a High-Potential Space Monitoring Radar 5

Methodology for Energy-efficient Heat Removal Control of the...

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5th international conference on control systems, Mathematical modeling, Automation and Energy Efficiency, SUMMA 2023

作者： Timoshenko, Alexander V. Perlov, Anatoly Yu. Shafir, Roman S. Zager, Igor B. Lvov, Kirill V. Moscow Aviation Institute Moscow Russia Moscow Institute of Electronic Technology Moscow Russia Moscow State University Moscow Russia

ISBN: (纸本)9798350309126

This work is devoted to the development of a technique for energy-efficient heat removal control in a modern space monitoring radar station. For this purpose, a thermal model of a power amplification unit operating inside the transmitting radio-electronic complex is constructed. The method of a quasi-homogeneous anisotropic body was used, which allows minimizing the computational costs of calculations by replacing a unit with a complex internal structure with a quasi-homogeneous body. The algorithm for energy-efficient control of heat removal from the power amplification unit is based on a thermal model that provides a forecast of the unit's temperature. According to the proposed algorithm, control actions on the cooling system are formed based on the temperature forecast. To evaluate the effectiveness of the developed algorithm in practice, a demonstration computational experiment was carried out. The constructed thermal model makes it possible to use this model and the developed heat removal technique at the operational stage of the radar station. © 2023 IEEE.

关键词： Energy efficiency

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Optimizing Energy Saving for Wireless Networks via Offline Decision Transformer 59

Optimizing Energy Saving for Wireless Networks via Offline D...

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59th Annual IEEE international conference on Communications (IEEE ICC)

作者： Xu, Yi Tian Wu, Di Jenkin, Michael Jang, Seowoo Liu, Xue Dudek, Gregory Samsung AI Ctr Montreal PQ Canada Samsung Elect Suwon South Korea

ISBN: (纸本)9781728190549

With the global aim of reducing carbon emissions, energy saving for communication systems has gained tremendous attention. Efficient energy-saving solutions are not only required to accommodate the fast growth in communication demand but solutions are also challenged by the complex nature of the load dynamics. Recent reinforcement learning (RL)-based methods have shown promising performance for network optimization problems, such as base station energy saving. However, a major limitation of these methods is the requirement of online exploration of potential solutions using a high-fidelity simulator or the need to perform exploration in a real-world environment. We circumvent this issue by proposing an offline reinforcement learning energy saving (ORES) framework that allows us to learn an efficient control policy using previously collected data. We first deploy a behavior energy-saving policy on base stations and generate a set of interaction experiences. Then, using a robust deep offline reinforcement learning algorithm, we learn an energy-saving control policy based on the collected experiences. Results from experiments conducted on a diverse collection of communication scenarios with different behavior policies showcase the effectiveness of the proposed energy-saving algorithms.

关键词： Offline reinforcement learning energy saving on/off control 5G cellular network

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A Decomposition-based Encoder-Decoder Framework for Multi-step Prediction of Burn-Through Point in Sintering Process 6

A Decomposition-based Encoder-Decoder Framework for Multi-st...

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IEEE 6th international conference on Industrial Cyber-Physical systems (ICPS)

作者： Xie, Yuhan He, Bocun Zhang, Xinmin Song, Zhihuan Zhejiang Univ Coll Control Sci & Engn State Key Lab Ind Control Technol Hangzhou Peoples R China

ISBN: (纸本)9798350311259

Sintering process is a critical step in the ironmaking process. Burn-through point (BTP), as a key performance index of sintering ore, has a great influence on the quality of the sintering product. The existing prediction methods attempt to use a single model to establish the relationship between variables. However, due to the strong volatility, uncertainty, and multivariable coupling of sintering process, the traditional prediction model cannot produce reliable predictions. In order to deal with the complex characteristics of sintering process, this paper proposes a decomposition-based encoder-decoder modeling framework, in which a sequence decomposition module is designed to decompose the input time series into different sub-sequences. Then, these sub-sequences are constructed by the encoder-decoder models separately. The effectiveness of the proposed multi-step ahead prediction modeling framework was evaluated in a real-world sintering process. Compared with the traditional prediction modeling framework, the proposed modeling framework has more accurate results in multi-step ahead prediction.

关键词： Sintering process burn-through point multi-step ahead prediction encoder-decoder series decomposition

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Can ChatGPT Enable ITS? The Case of Mixed Traffic control via Reinforcement Learning 26

Can ChatGPT Enable ITS? The Case of Mixed Traffic Control vi...

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IEEE 26th international conference on Intelligent Transportation systems (ITSC)

作者： Villarreal, Michael Poudel, Bibek Li, Weizi Univ Tennessee Dept Elect Engn & Comp Sci Knoxville TN 37996 USA

ISBN: (纸本)9798350399462

The surge in Reinforcement Learning (RL) applications in Intelligent Transportation systems (ITS) has contributed to its growth as well as highlighted key challenges. However, defining objectives of RL agents in traffic control and management tasks, as well as aligning policies with these goals through an effective formulation of Markov Decision Process (MDP), can be challenging and often require domain experts in both RL and ITS. Recent advancements in Large Language Models (LLMs) such as GPT-4 highlight their broad general knowledge, reasoning capabilities, and commonsense priors across various domains. In this work, we conduct a large-scale user study involving 70 participants to investigate whether novices can leverage ChatGPT to solve complex mixed traffic control problems. The participants' task is to develop the state space and reward function for three RL mixed traffic control environments, including ring road, bottleneck, and intersection. We find ChatGPT has mixed results. For intersection and bottleneck, ChatGPT increases number of successful policies by 150% and 136% compared to solely beginner capabilities, with some of them even outperforming experts. However, ChatGPT does not provide consistent improvements across all scenarios.

关键词： Reinforcement learning

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An Improved Transformer-Based High-Performance Object Detection Method 6

An Improved Transformer-Based High-Performance Object Detect...

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6th international conference on Information Science, Electrical, and Automation Engineering, ISEAE 2024

作者： Sun, Ziwen Tian, Zonghao Shi, Shengbin Ling, Chong Laboratory of Guidance Control and Information Perception Technology of High Overload Projectiles Army Academy of Artillery and Air Defense Hefei230031 China

ISBN: (纸本)9781510682924

The Transformer architecture is widely used in the field of computer vision due to its ability to relate context and global modeling, and Transformer-based object detection methods have achieved very bright results. However, the existing methods have the problems of underutilizing background images and the model structure is too complex and redundant. In order to solve such problems, an improved high-performance object detection method based on Transformer is proposed. The method first extracts the depth features of the object by means of feature pyramid extraction, then extracts the large, medium and small object regions present in the object image by means of RPN and ROI Pooling, and finally seeks the extrinsic connection between different regions by means of the attention mechanism in the Transformer method, and predicts the object location and category using the proposed loss function. Compared with state-of-the-art object detection methods on MS-COCO datasets, The effectiveness and superiority of the proposed method were demonstrated. © 2024 SPIE.

关键词： Object detection Transformers Feature extraction Bismuth Detection and tracking algorithms Education and training Ablation Computer programming Machine learning modeling

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Adaptive Autonomous Script Model with Appropriate Behavior 4

Adaptive Autonomous Script Model with Appropriate Behavior

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4th international conference on control systems, Mathematical modeling, Automation and Energy Efficiency, SUMMA 2022

作者： Kozyr', Olga Krivonosov, Vladimir Stary Oskol Technol. Inst. Br. of the Natl. Res. Technol. Univ. of Moscow Inst. of Stl. and Alloys Named Afte A. A. Ugarov Department of Automation and Information Control Systems Stary Oskol Russia

ISBN: (数字)9781665456593

ISBN: (纸本)9781665456593

The problem of using adaptive autonomous scripts in solving the problems of information resource management of computing systems is considered. A model of adaptive autonomous scripts using frames and finite state machines is developed, which extends the possibilities of automating complex tasks of information resources management. © 2022 IEEE.

关键词： Information management

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Prediction for Combustion States of Waste-to-Energy Plants with Fuzzy Relational Maps of Sensors

Prediction for Combustion States of Waste-to-Energy Plants w...

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IEEE international conference on Fuzzy systems (FUZZ-IEEE)

作者： Ise, Akifumi Umano, Motohide Kohigashi, Kiyotaka Environm Business Headquarters Hitachi Zosen Corp Business & Prod Dev Ctr Osaka Japan Tech Res Inst R&D Headquarters Hitachi Zosen Corp Osaka Japan Environm Business Headquarters Hitachi Zosen Corp Environm West Japan Management Dept Osaka Japan

ISBN: (纸本)9798350319552;9798350319545

In waste-to-energy plants, keeping a stable combustion state is required to decrease hazardous gases and keep the steam volume appropriate for generating electricity. Since waste has various properties and plants have many sensors intricately related to each other, it is very difficult to find a very complex relation of many sensors for keeping a stable combustion state. In this paper, we propose a fuzzy relational map of sensors, FuRMS, as a method to represent relations of many sensors. For data of unknown state, we calculate evaluation values with the map. We apply it to a waste-to-energy plant. We construct a map using 14110 data of the stable state and evaluate other 390 data of unknown state. The result shows that the map can predict combustion states, that is, the evaluation value begins to decrease 10 to 30 minutes earlier than beginnings of unstable states. We propose some methods to extend this method to be more useful in the future.

关键词： fuzzy set relation of fuzzy sets fuzzy modeling waste-to-energy plants automatic combustion control

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A Novel Method Implemented for Deadlock problems in FMSs Modeled with Petri Nets 7

A Novel Method Implemented for Deadlock Problems in FMSs Mod...

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7th international conference on Vocational Education and Electrical Engineering, ICVEE 2024

作者： Abdul-Hussin, Mowafak Hassan University of Technology Dept. of Communication Engineering Baghdad Iraq

ISBN: (纸本)9798331505103

A novel method implemented for deadlock problems is specified to perfectly liveness, which is crucial to Petri Net(PN) models. In this article, we apply four classes of PN execution to models of complex Flexible Manufacturing systems (FMSs) environments. The significant paradigm presented for S4PR-net is characterized by high efficiency in the distribution of modeling complex interactive FMSs. We formulate this problem as a complete multi-resource production system using advanced automation technologies in response to it. The optimal reconfigurable FMS is implemented by designing the controller transitions (CTs) in the PNs models, and this approach eliminates all deadlock statuses. The methodology and models developed can be used CTs are provided effectively for PNs when adding the recapture transitions usually associated with deadlock (DL)-free, which conserved all markings. More specifically, this framework permits PN's Reachability Graphs (RG) to guarantee maximum permissive for FMS allowing multiple active resources. Several examples have been experimental results to demonstrate PNs that contain computer simulation models and are much more efficient. simulation models and are much more efficient. © 2024 IEEE.

关键词： Flexible manufacturing systems

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