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检索条件"任意字段=7th International Conference on the Art, Science, and Engineering of Programming, Programming 2023"

共 1136 条记录，以下是841-850 订阅

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GPGPU vs multiprocessor SPSO implementations to solve electromagnetic optimization problems

GPGPU vs multiprocessor SPSO implementations to solve electr...

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international Joint conference on Computational Intelligence (IJCCI)

作者： Anton Duca Laurentiu Duca Gabriela Ciuprina Daniel Ioan Politehnica University of Bucharest Faculty of Electrical Engineering Bucharest Romania Faculty of Computer Science Politehnica University of Bucharest Bucharest Romania

ISBN: (纸本)9781509019687

this paper studies two parallelization techniques for the implementation of a SPSO algorithm applied to optimize electromagnetic field devices, GPGPU and Pthreads for multiprocessor architectures. the GPGPU and Pthreads implementations are compared in terms of solution quality and speed up. the electromagnetic optimization problems chosen for testing the efficiency of the parallelization techniques are the TEAM22 benchmark problem and Loney's solenoid problem. As we will show, there is no single best parallel implementation strategy since the performances depend on the optimization function.

关键词： Graphics processing units Optimization Linear programming Synchronization Kernel Electromagnetics Instruction sets

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Demand Response Potential Assessment of Steel Plant Based on Refined Simulation

Demand Response Potential Assessment of Steel Plant Based on...

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Power and Energy engineering (ICPEE), international conference on

作者： Bokang Zou Yuanshi Zhang Qirui Chen Yiyuan Ding Xiaorong Yu Qinran Hu Qi Wang School of Electrical & automation Engineering Nanjing Normal University Nanjing China School of Electrical Engineering Southeast University Nanjing China State Grid International Development Co. Ltd Nanjing China Taizhou Power Supply Company State Grid Jiangsu Electric Power Co. Ltd Nanjing China

the steel industry has witnessed a progressive increase in the electrification degree of its production process due to advancements in decarburization technology. Consequently, there will be a substantial rise in electricity usage within the steel sector. the transition in energy consumption patterns is a significant obstacle to the functioning of the power system. One of the potential methods for achieving zero-carbon steel manufacturing is through the utilization of the direct reduction iron (DRI) - electric arc furnace (EAF) production route. this particular route is characterized by its high energy consumption and intricate production load characteristics. this paper attempts to examine the demand response capabilities of power loads throughout the DRI-EAF production process. A nonlinear programming model, encompassing the DRI-EAF steel plant, is constructed in light of the dependency of each link in the DRI-EAF production process. this study aimed to examine the impact of various production plans on the possible demand response of hydrogen-based steel plants, with a focus on minimizing the operating costs of these mills. the findings indicate that the scheduling model proposed in this study effectively utilizes the scheduling benefits offered by adjustable resources in the iron and steel production process, hence facilitating the economic scheduling of iron and steel plants.

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Ant Colony Algorithm Research Based on Pheromone Update Strategy

Ant Colony Algorithm Research Based on Pheromone Update Stra...

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international conference on Intelligent Human-Machine Systems and Cybernetics, IHMSC

作者： Yahong Zhai Longyan Xu Yanxia Yang School of Electrical and Information Engineering Hubei University of Automotive Technology Shiyan China Fac. of Inf. Eng. Wuhan University of Science and Technology Wuhan Hubei CN

ISBN: (纸本)9781479986477

A new pheromone control strategy based on knowledge guide is presented. the main idea is to use the prior knowledge and group knowledge from statistical learning to guide the ant search. It has more targeted for ants search which combined with new pheromone updating strategy, thus contributing to a better solution for the algorithm. the experimental results indicate that the overall performance of the ant colony algorithm based on knowledge guiding pheromone control strategy is obviously better than other ant colony optimization algorithm.

关键词： Algorithm design and analysis Ant colony optimization Search problems Linear programming Convergence Optimized production technology Knowledge engineering

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A New Genetic programming-Based Approach to Object Detection in Mussel Farm Images

A New Genetic Programming-Based Approach to Object Detection...

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international conference on Image and Vision Computing New Zealand, IVCNZ

作者： Dylon Zeng Ying Bi Ivy Liu Bing Xue Ross Vennell Mengjie Zhang Centre for Data Science and Artificial Intelligence & School of Engineering and Computer Science & School of Mathematics and Statistics Victoria University of Wellington New Zealand Coastal and Freshwater Group Cawthron Institute Nelson New Zealand

Mussel farms are vital contributors to New Zealand’s booming aquaculture industry, driving economic growth and generating employment opportunities across the country. To meet the demand for sustainable mussel production, innovative computer vision and AI solutions are essential in detecting mussel floats that maintain crop line buoyancy. However, object detection in mussel farm images faces considerable challenges such as poor image quality, partial occlusion, and high variability in image conditions. In this paper, we propose a new genetic programming-based approach tailored for object detection in mussel farm images. the approach features a new waterline detection algorithm for image segmentation and a new genetic programming method, called 3-Tree GP, for object detection (mussel buoy/float). Experimental results show that the proposed approach achieves a detection F1 score of 94.4%, surpassing the state-of-the-art YOLOv8 by over 4%. In particular, the approach excels in identifying objects that are partially occluded, or located far away from the camera, making it suitable for real-world applications.

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Risk-Aware Motion Planning for Very-Large-Scale Robotics Systems Using Conditional Value-at-Risk 1

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16th international conference on Intelligent Robotics and Applications, ICIRA 2023

作者： Yang, Xuru Gao, Han Zhu, Pingping Liu, Chang Department of Advanced Manufacturing and Robotics College of Engineering Peking University Beijing100871 China Marshall University HuntingtonWV25755 United States

ISBN: (数字)9789819964987

ISBN: (纸本)9789819964970

the field of Very-Large-Scale Robotics (VLSR) has garnered significant attention due to its ability to tackle complex and coordinated tasks. However, current motion planning methods for VLSR face challenges related to scalability and ensuring safety. To address these limitations, we propose a novel risk-aware motion planning framework for VLSR. Our approach formulates a finite-time optimal control (FTOC) problem based on the macroscopic state of VLSR and incorporates conditional value-at-risk (CVaR) to avoid collision. We present a systematic approach that leverages the linearized Signed Distance Function to efficiently compute the CVaR of the distance between VLSR and obstacles. Subsequently, we develop an approximation approach to reformulate the nonlinear FTOC as a linear programming problem using the discretized workspace, resulting in computationally efficient online motion planning. Simulations on VLSR consisting of five hundred robots demonstrate the effectiveness of the proposed approach in both computational efficiency and risk mitigation. © the Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2023.

关键词： Motion planning

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Parameters Tuning and Optimization of Linear Active Disturbance Rejection Control Subject to Actuator Rate Limit

Parameters Tuning and Optimization of Linear Active Disturba...

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international conference on Information science and Control engineering (ICISCE)

作者： Feng Yang Kaimin Wang Minjun Zhang Yi Dai Zijie Pan Ming Sun Inner Mongolia Datang International Tuoketuo Power Generation Co. Ltd Huhhot China School of Control and Computer Engineering North China Electric Power University Baoding China

the traditional empirical tuning method of Linear Active Disturbance Rejection Control (LADRC) parameters is obtained without considering the actuator rate limit. Once the actuator rate is limited, then the input and output signals of the actuator cannot be synchronized. Considering that there is no efficient strategy for tuning LADRC parameters when the actuator rate is limited. And the parameters tuning method of LADRC is complex and difficult. Taking the traditional LADRC parameter tuning value as the benchmark and combining with the Pigeon Inspired Optimization (PIO) algorithm, a LADRC parameter tuning method is proposed by constructing the quadratic objective function and changing the weight factor of the control increment. the simulation results show that the LADRC parameters optimization method based on PIO can keep the input and output signals of the actuator synchronized.

关键词： Robust control Actuators Information science Simulation Optimization methods Linear programming Stability analysis

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A preliminary study of the RADOE project

A preliminary study of the RADOE project

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IEEE conference on Cybernetics and Intelligent Systems

作者： Haibin Yan YuanRui Yang Renjun Li Masood Dehghan Marcelo H. Ang Advanced Robotics Center and SIMTech-NUS Joint Laboratory (Industrial Robotics) National University of Singapore Singapore Institute for Infocomm Research (I2R) Singapore Department of Mechanical Engineering National University of Singapore Singapore

ISBN: (纸本)9781467373395

Robotic softwares with convenient operation and programming are desirable to increase the efficiency and efficacy of industrial robots which work in complex and fickle environments. To develop such softwares, we aim to develop a new robotic software called RADOE (Robot Application Development and Operating Environment), under the support from the science and engineering Research Council, Singapore. In this paper, we introduce some of our preliminary results of the RADOE project, particularly on the system architecture design. the key objective of our RADOE is to define robotic tasks in a simple way, communicate with different industrial robots and control them under varying environmental conditions. To achieve this, we employ a hierarchical system structure with state machines to make it modular, extendible, robust, and maintainable. Experimental results on KUKA LBR iiwa robot show that RADOE combined with the developed system architecture demonstrates good performance for motion planning and tasks execution.

关键词： Service robots Robot kinematics Planning Software Graphical user interfaces programming

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Task-Oriented Service Provision and Scheduling for Non-Terrestrial Networks: A Deep Reinforcement Learning Based Approach 16

Task-Oriented Service Provision and Scheduling for Non-Terre...

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16th international conference on Wireless Communications and Signal Processing, WCSP 2024

作者： Cao, Yilu Jia, Ziye Zhang, Yu Dong, Chao Zhou, Fuhui Wu, Qihui Nanjing University of Aeronautics and Astronautics The Key Laboratory of Dynamic Cognitive System of Electromagnetic Spectrum Space Ministry of Industry and Information Technology Jiangsu Nanjing211106 China Southeast University National Mobile Communications Research Laboratory Jiangsu Nanjing211111 China School of Engineering Newcastle University Newcastle upon TyneNE1 7RU United Kingdom

ISBN: (纸本)9798350390643

the non-terrestrial network (NTN) receives considerable attentions due to the development of the sixth generation technologies in recent years. However, the mobility and heterogeneity of satellites and unmanned aerial vehicles in NTN lead to increasing challenges in resource allocation and management. As such, the network function virtualization technology is introduced, by deploying service function chains (SFCs) to achieve requirements. However, it brings conflicts and resource competition due to urgent unexpected tasks. therefore, scheduling multiple SFCs in NTN is a crucial issue. In this paper, a task-oriented service provision and scheduling model is proposed to tackle the dynamic complexity of NTN by designing the reconfigurable time extension graph. Subsequently, the SFC scheduling problem is formulated to maximize the number of completed tasks within limited resources and time constraints. Due to the problem form of integer linear programming, we propose a deep reinforcement learning based algorithm. Finally, simulation results validate the effectiveness of the proposed algorithm, indicating its superior performance over other benchmark algorithms. © 2024 IEEE.

关键词： Deep reinforcement learning

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Using randomized rounding to satisfy timing constraints of real-time preemptive tasks

Using randomized rounding to satisfy timing constraints of r...

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Asia and South Pacific Design Automation conference

作者： A. Datta S. Choudhury A. Basu Computer Science Department University of Stanford USA Department of Computer Sciences University of Texas Austin USA Department of Computer Science & Engineering Indian Institute of Technology Kharagpur India

ISBN: (纸本)0769514413

In preemptive real-time systems, a tighter estimate of the Worst Case Response Time (WCRT) of the tasks can be obtained if the layout of the tasks in memory is included in the estimation procedure. this is because the Cache Related Preemption Delay (CRPD) depends on the inter-task interference in the cache. We develop a response time analysis framework which takes the layout of the tasks into account. We present an ILP formulation which generates a layout of the tasks such that all timing constraints are satisfied. To overcome the issue of non-scalability associated with an ILP solution, we also present a linear programming relaxation of the ILP formulation, which offers an approximate solution. the performance of the proposed formulation is demonstrated.

关键词： Timing Real time systems Computer science Linear programming Interference constraints Resumes Delay effects Integer linear programming Dynamic programming Polynomials

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Influence Maximization in Microblog Social Network

Influence Maximization in Microblog Social Network

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international conference on Information science and Control engineering (ICISCE)

作者： Zhengyi Ma Yan Yang School of Computer Science Technology Heilongjiang University Harbin China Key Laboratory of Database and Parallel Computing Harbin Heilongjiang Province China

In recent years, the continuous rise of social networks has promoted the research of maximizing influence. therefore, it is more and more important to mine a group of users with the largest influence range in social network, which is also of great significance for the promotion of some products. To solve the above problems, this paper studies the influence maximization in microblog social network, and proves that the problem is NP hard, and the objective function of the problem satisfies monotonicity and submodule. An effective algorithm is proposed to solve this problem. the algorithm fully considers the nature of microblog social network and microblog users, and measures the influence of users themselves with activity, communication power and coverage. Based on the independent cascade model, a communication model is designed according to the influence of users and the interaction times between users. through the experiment on the real microblog data set, it is proved that the algorithm has good performance in the propagation range and operation efficiency, and the propagation effect is more in line with the reality.

关键词： Information science Power measurement Control engineering Social networking (online) Blogs Linear programming

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