COLLABORATIVE

作品数：591被引量：702H指数：10
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相关领域：自动化与计算机技术更多>>
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相关机构：第二炮兵工程学院北京师范大学浙江大学西安外国语大学更多>>
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Vehicle and onboard UAV collaborative delivery route planning:considering energy function with wind and payload
《Journal of Systems Engineering and Electronics》2025年第1期194-208,共15页GUO Jingfeng SONG Rui HE Shiwei 
Fundamental Research Funds for the Central Universities(2024JBZX038);National Natural Science F oundation of China(62076023)。
The rapid evolution of unmanned aerial vehicle(UAV)technology and autonomous capabilities has positioned UAV as promising last-mile delivery means.Vehicle and onboard UAV collaborative delivery is introduced as a nove...
关键词：vehicle and onboard unmanned aerial vehicle(UAV)collaborative delivery energy consumption function route planning mixed integer linear programming model adaptive large neighborhood search(ALNS)algorithm 
Delay-optimal multi-satellite collaborative computation offloading supported by OISL in LEO satellite network
《Journal of Systems Engineering and Electronics》2024年第4期805-814,共10页ZHANG Tingting GUO Zijian LI Bin FENG Yuan FU Qi HU Mingyu QU Yunbo 
This work was supported by the National Key Research and Development Program of China(2021YFB2900600);the National Natural Science Foundation of China(61971041;62001027);the Beijing Natural Science Foundation(M22001);the Technological Innovation Program of Beijing Institute of Technology(2022CX01027).
By deploying the ubiquitous and reliable coverage of low Earth orbit(LEO)satellite networks using optical inter satel-lite link(OISL),computation offloading services can be provided for any users without proximal serv...
关键词：low Earth orbit(LEO)satellite network computation offloading task migration resource allocation 
Distributed collaborative complete coverage path planning based on hybrid strategy
《Journal of Systems Engineering and Electronics》2024年第2期463-472,共10页ZHANG Jia DU Xin DONG Qichen XIN Bin 
supported by the National Natural Science Foundation of China (61903036, 61822304);Shanghai Municipal Science and Technology Major Project (2021SHZDZX0100)。
Collaborative coverage path planning(CCPP) refers to obtaining the shortest paths passing over all places except obstacles in a certain area or space. A multi-unmanned aerial vehicle(UAV) collaborative CCPP algorithm ...
关键词：multi-agent cooperation unmanned aerial vehicles(UAV) distributed algorithm complete coverage path planning(CCPP) 
Radar emitter signal recognition method based on improved collaborative semi-supervised learning
《Journal of Systems Engineering and Electronics》2023年第5期1182-1190,共9页JIN Tao ZHANG Xindong 
Rare labeled data are difficult to recognize by using conventional methods in the process of radar emitter recogni-tion.To solve this problem,an optimized cooperative semi-supervised learning radar emitter recognition...
关键词：emitter signal identification time series BOOTSTRAP semi supervised learning cross entropy function homogeniza-tion dynamic time warping(DTW) 
Mission scheduling of multi-sensor collaborative observation for space surveillance network
《Journal of Systems Engineering and Electronics》2023年第4期906-923,共18页LONG Xi CAI Weiwei YANG Leping WANG Tianyu 
supported by the National Natural Science Foundation of China(11802333);the Scientific Research Program of the National University of Defense Technology(ZK19-31)。
With increased dependence on space assets,scheduling and tasking of the space surveillance network(SSN)are vitally important.The multi-sensor collaborative observation scheduling(MCOS)problem is a multi-constraint and...
关键词：multi-sensor observation resource scheduling subtime window evolution heuristic algorithm 
Solving flexible job shop scheduling problem by a multi-swarm collaborative genetic algorithm被引量：8
《Journal of Systems Engineering and Electronics》2021年第2期261-271,共11页WANG Cuiyu LI Yang LI Xinyu 
supported by the National Key R&D Program of China(2018AAA0101700);the Program for HUST Academic Frontier Youth Team(2017QYTD04).
The flexible job shop scheduling problem(FJSP),which is NP-hard,widely exists in many manufacturing industries.It is very hard to be solved.A multi-swarm collaborative genetic algorithm(MSCGA)based on the collaborativ...
关键词：flexible job shop scheduling problem(FJSP) collaborative genetic algorithm co-evolutionary algorithm 
Evolutionary game analysis of problem processing mechanism in new collaboration被引量：1
《Journal of Systems Engineering and Electronics》2021年第1期136-150,共15页ZHANG Ming ZHU Jianjun WANG Hehua 
supported by the National Natural Science Foundation of China(71171112;71502073)。
This paper analyzes a problem processing mechanism in a new collaboration system between the main manufacturer and the supplier in the"main manufacturer-supplier"mode,which has been widely applied in the collaborative...
关键词：collaborative development management unpredicted problem problem processing mechanism evolutionary game theory 
Collaborative beamforming based on directional perturbation using one bit feedback被引量：2
《Journal of Systems Engineering and Electronics》2016年第3期549-554,共6页Haifen Yang Ning Ding Zhi Zheng Shuisheng Lin Zhongpei Zhang Guangjun Li 
supported by the National Natural Science Foundation of China(61301155;61571003);the Ministry of Education(MCM20130111);the Funds for the Central Universities(ZYGX2014J001);the State Grid Power(W2015000333)
A novel collaborative beamforming algorithm is proposed in a wireless communication system with multiple transmitters and one receiver. All transmitters take part in the collaboration and the weighted message is trans...
关键词：collaborative beamforming one-bit feedback directional perturbation convergent speed 
Collaborative multi-agent reinforcement learning based on experience propagation被引量：5
《Journal of Systems Engineering and Electronics》2013年第4期683-689,共7页Min Fang Frans C.A. Groen 
supported by the National Natural Science Foundation of China (61070143; 61173088)
For multi-agent reinforcement learning in Markov games, knowledge extraction and sharing are key research problems. State list extracting means to calculate the optimal shared state path from state trajectories with c...
关键词：MULTI-AGENT Q learning state list extracting experience sharing. 
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