A Task Allocation Strategy of the UAV Swarm Based on Multi-Discrete Wolf Pack Algorithm

Xu, Sheng; Li, Linlin; Zhou, Ziyun; Mao, Yingchi; Huang, Jianxin

doi:10.3390/app12031331

Cited by 24 publications

(9 citation statements)

References 30 publications

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“…Experiments have shown that the algorithm is more accurate and converges faster [7]. Literature proposed the cultural wolf optimization algorithm, and found that the cultural wolf optimization algorithm has faster convergence speed and higher accuracy than other algorithms in the actual use process [8]. Literature adds new random survival rules on the basis of WPA, and ensures the diversity of algorithms by adding new rules [9].…”

Section: Related Workmentioning

confidence: 99%

RETRACTED ARTICLE: Research on reliability of sports intelligent training system based on hybrid wolf pack algorithm and IoT

Chen¹,

Huang

2023

Soft Comput

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To expand the application scope of the WCA algorithm in the actual process, this research has optimized the problems in the algorithm in two aspects: The first aspect further improves the operating mechanism of the WCA algorithm and improves the performance of optimization problem. In the second aspect, other optimization strategy mechanisms of the WCA algorithm are introduced to enable the algorithm to optimize multi-objective and multidimensional problems. This paper studies a physical test system and sports intelligent based on hybrid wolf pack algorithm and IoT. The system collects and sends data from the data collection terminal of the Web server, receives the data through the wireless module, and sends it to the Web server through the network. The web server processes and stores the data information to generate a database, and users can view their own sports information by logging in to the web service program with the account password. In addition, the teacher and administrator accounts have the ability to view all users' exercise information. The system adds three sports items, pull-ups, squats, and standing long jumps. At the same time, the system uses a general motion recognition algorithm, which can effectively reuse and add new sports items. According to the actual needs of intelligent sports training, this paper combines somatosensory technology, bone tracking technology and motion recognition algorithm to realize a high-precision, low-latency intelligent sports training system.

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Section: Related Workmentioning

confidence: 99%

RETRACTED ARTICLE: Research on reliability of sports intelligent training system based on hybrid wolf pack algorithm and IoT

Chen¹,

Huang

2023

Soft Comput

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“…The fish swarm algorithm incorporates four behaviors: foraging, aggregation, tail chasing, and random [32], while the wolf pack algorithm includes three behaviors: wandering, summoning, and siege [33]. Despite differences, there are similarities between these behaviors.…”

Section: Solving Based On Wf-csa Optimization Algorithmmentioning

confidence: 99%

“…Substitute x i into (33),and reorder according to the fitness value from small to large, to get the position of the leader fish, scout fish, and hunter fish x a , x b , x c Substitute x a into (33) to get best f itness 21: end while…”

mentioning

confidence: 99%

Blockchain-based 6G Task Offloading and Cooperative Computing Resource Allocation Study*

Tian,

Zhang,

et al. 2024

Preprint

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In the upcoming era of 6G, the accelerated development of the Internet of Everything and high-speed communication is poised to provide people with an efficient and intelligent life experience. However, the exponential growth in data traffic is expected to pose substantial task processing challenges. Relying solely on the computational resources of individual devices may struggle to meet the demand for low latency. Additionally, the lack of trust between different devices poses a limitation to the development of 6G networks. In response to this issue, this study proposes a blockchain-based 6G task offloading and collaborative computational resource allocation (CERMTOB) algorithm. The proposed first designs a blockchain-based 6G cloud-network-edge collaborative task offloading model. It incorporates a blockchain network on the edge layer to improve trust between terminals and blockchain nodes. Subsequently, the optimization objective is established to minimize the total latency of offloading, computation, and blockchain consensus. The optimal offloading scheme is determined using the wolf fish collaborative search algorithm(WF-CSA) to minimize the total delay. The simulation results demonstrate that the WF-CSA algorithm achieves a remarkable reduction in total delay, with improvements of up to 42.58% compared to both the fish swarm algorithm and the wolf pack algorithm. Furthermore, the introduction of blockchain to the cloud-side-end offloading system improves the communication success rate by a maximum of 14.93% compared to the blockchain-free system.

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“…The adjustment of impact degree. In the initial stage of dispersion, if the judgment of influence degree cannot guarantee the comprehensiveness, the overall performance of the judgment result of influence degree will be reduced Xu et al [ 11 ]. Therefore, in the process of influencing factor analysis, we should try our best to expand the judgment range, narrow the judgment range near the main influencing factors of habit formation, and constantly adjust the factors to improve the success rate of habit formation.…”

Section: Concepts Related To the Continuous Discrete Algorithmmentioning

confidence: 99%

Analysis of Influencing Factors of College Students’ Physical Exercise Habits Based on the Continuous Discrete Algorithm

Zhang

Jiang

Shi

et al. 2022

Journal of Environmental and Public Health

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At present, college students give great importance to their physical training, but their physical habits are poor and they cannot exercise regularly. In view of the influencing factors in the habit formation of physical exercise, this paper puts forward a continuous discrete algorithm to provide students with a scientific and reasonable habit formation scheme. First, the data of college students’ physical exercise habits are collected, and the data are cleaned and continuously analyzed to initially form a habit formation data set; Then, the information gain and clustering thought in the discrete algorithm are used to judge the data change, and the ordered relationship among the factors is obtained. Finally, in judging the influence degree of each factor, we find out the final influencing factors. MATLAB simulation shows that the continuous discrete algorithm can accurately analyze the problem of physical exercise habit formation and sort the influencing factors, with an accuracy rate of 90% and a calculation time of less than 19 minutes, which is significantly better than the original discrete algorithm.

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A Task Allocation Strategy of the UAV Swarm Based on Multi-Discrete Wolf Pack Algorithm

Cited by 24 publications

References 30 publications

RETRACTED ARTICLE: Research on reliability of sports intelligent training system based on hybrid wolf pack algorithm and IoT

RETRACTED ARTICLE: Research on reliability of sports intelligent training system based on hybrid wolf pack algorithm and IoT

Blockchain-based 6G Task Offloading and Cooperative Computing Resource Allocation Study*

Analysis of Influencing Factors of College Students’ Physical Exercise Habits Based on the Continuous Discrete Algorithm

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