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International Conference on Machine Intelligence and Digital Applications (MIDA)

作者： Cai, Xiaocheng Yang, Hongqiang Fu, Zongchun Hunan Railway Profess Technol Coll Zhuzhou Peoples R China

ISBN: (纸本)9798400718144

For the problem of uplink signal detection of the transponder, this paper proposes a transponder signal detection method based on ant colony algorithm bistable stochastic resonance. Firstly, according to the method of detecting weak signals based on the theory of stochastic resonance, a bistable stochastic resonance function is constructed, and the relationship between system parameters, signal amplitude, noise intensity and signal-to-noise ratio is introduced in detail. Then, according to the characteristics of the transponder uplink signal, a transponder characteristic signal function is constructed. In view of the problem that the transponder signal belongs to a non-slowly varying signal, the transponder uplink signal is subjected to variable-scale normalization processing to make the signal conform to the characteristics of a slowly varying signal, thereby meeting the requirements of signal detection by the principle of stochastic resonance. Finally, taking the signal-to-noise ratio as the judgment condition, the ant colony algorithm is used to find the optimal system parameters of the bistable stochastic resonance system to realize the synergy of the transponder signal, the bistable stochastic resonance system and the noise, so that the system has the best transponder signal detection performance. The simulation results show that when the system parameters a = 5"41 x 10(6), the bistable stochastic resonance system based on the ant colony algorithm can effectively detect the transponder uplink signal under the strong noise background, and this method has a relatively strong output signal-to-noise ratio, providing a reference for improving the performance of the transponder transmission system.

关键词： Bistable Stochastic resonance ant colony algorithm Transponder Signal detection

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Research on the Construction of Digital Education Cloud Resource Database Based on ant colony algorithm 5th

Research on the Construction of Digital Education Cloud Reso...

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5th International Conference on Big Data and Security (ICBDS)

作者： Li, Na Jiangxi Univ Appl Sci Nanchang 330008 Jiangxi Peoples R China

ISBN: (纸本)9789819743896;9789819743902

Cloud computing has become one of the hot research directions in academia. With the help of virtualization technology, cloud computing transforms the large-scale and complex physical resources in the cloud environment into different kinds of virtual resource pools for unified management, and automatically deploys the tasks submitted by the cloud, so that service buyers can use computing resources without increasing the cost of purchasing and maintaining resources. One of the key problems to be solved in the implementation of such a platform is how to schedule resources effectively. ant colony algorithm is essentially a swarm intelligence search algorithm, which searches for the optimal path through positive feedback and distributed cooperation. Because each ant searches for food independently, and there is no internal information correlation and dependence, a large number of ants exchange information and communicate with each other through pheromones. This parallel and independent search capability not only increases the reliability of the algorithm and reduces the time for the whole system to complete the search, but also has a strong global search capability. ant colony algorithm has good adaptability for solving combinatorial optimization problems. The mapping between resources and tasks in cloud environment is essentially a combinatorial optimization problem, so this paper uses ant colony algorithm to discuss the resource scheduling problem of cloud computing.

关键词： ant colony algorithm Digital education Cloud resource library

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Distribution network path planning method based on fusion improved A* and ant colony algorithm 7

Distribution network path planning method based on fusion im...

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7th International Conference on Automation Electronics and Electrical Engineering

作者： Wang Yating Su Rui Yan Runzhen Lei Hui Wen Jinmei State Grid Gansu Elect Power Co Digital Div Lanzhou 730000 Peoples R China

ISBN: (数字)9798350377033

ISBN: (纸本)9798350377040;9798350377033

The planning of distribution network has a crucial impact on the reliability, economy and stability of the power network. In order to improve the rationality of distribution network path planning, A research method of path planning based on fusion improved A* and ant colony algorithm is proposed. The differential distribution of pheromones accelerated the initial convergence of ant colonies. Three influencing factors are introduced into the heuristic function and the distance bias function is integrated into the transfer probability, so that ants can better search the path towards the target point and improve the search efficiency. At the same time, a special reward and punishment mechanism is used to update pheromone to solve the problem that the algorithm is easy to fall into local optimal. By comparing with the ACO algorithm and the improved ACO algorithm, the effectiveness of the improved algorithm is verified.

关键词： distribution network ant colony algorithm path planning

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Research on ship path planning in ice area based on improved ant colony algorithm 6

Research on ship path planning in ice area based on improved...

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6th International Conference on Robotics, Intelligent Control and Artificial Intelligence, RICAI 2024

作者： Lin, Yutong Qi, Yin Shao, Guoyu Zhao, Lei College of shipping Bohai University Jinzhou China

ISBN: (纸本)9798331541699

In order to meet the practical needs of safe navigation in the ice area of ships, a path planning method with improved ant colony algorithm was proposed. The traditional ant colony algorithm has the characteristics of strong path search ability and high real-time performance in the path planning of ships in ice areas, but it still has the shortcomings of long search path and slow convergence speed. By introducing the Tent chaotic map, the initial value of the ant pack was optimized, which enhanced the diversity of the wolf pack and improved the global search ability. The Levy flight and random walk strategies were used to enhance the global and local optimization capabilities, respectively. Add the greedy mechanic to retain the more adaptable path solution. Experimental results show that, compared with the traditional algorithm, the proposed improved algorithm has a great improvement in the planning path length and smoothness, which can better meet the path planning needs of ships in the complex navigation environment of ice areas. © 2024 IEEE.

关键词： ant colony algorithm component path planning ship ice navigation Tent chaos

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Fault Detection and Diagnosis Based on ant colony algorithm 8

Fault Detection and Diagnosis Based on Ant Colony Algorithm

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8th International Conference on Robotics and Automation Sciences (ICRAS)

作者： Da, Gula Zhao, Jinxing Inner Mongolia Univ Pioneer Coll Foreign Languages Sch Hohhot Peoples R China Inner Mongolia Univ Sch Math Sci Hohhot Peoples R China

ISBN: (纸本)9798350352511;9798350352504

In this paper, the fault diagnosis problem is transformed into an optimization problem and solved by biological heuristic algorithm ant colony algorithm. Combined with the nearest neighbor function criterion in pattern recognition, this method optimizes the initial pheromone matrix and the value of nearest neighbor function, which greatly improves the speed of the algorithm. In the process of algorithm analysis, the errors in literature [1] are corrected. Finally, an empirical analysis is carried out to prove that our method can greatly improve the diagnosis efficiency.

关键词： ant colony algorithm fault diagnosis nearest neighbor function

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Link Design for Wireless Optical Communication Network based on ant colony algorithm

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JOURNAL OF COMMUNICATIONS AND NETWORKS 2022年第2期24卷 184-191页

作者： Wang, Xiaorui Chen, Dongdong Zhengzhou Univ Light Ind Coll Comp & Commun Engn Zhengzhou Peoples R China

the maturation of space laser communication technologies and the development of deep-space exploration technologies, deep-space optical network (DSON) is expected to become an important foundation and inevitable development trend of future deep-space communication. According to the characteristics of DSON, we present a DSON topology structure based on flat wireless mesh network (FWMN). To improve the robustness of DSON and realize load balancing, the Routing algorithm based on ant colony algorithm (RA-ACA) for DSON is proposed in this paper. We primarily research the unidirectional links problem and node energy consumption of DSON with RA-ACA. Instead of deleting the unidirectional links in the whole networks used in traditional ant colony algorithm (TACA), we make the best of unidirectional links, and then the performance of network will be improved. Also, in order to control the energy consumption speed of nodes and prevent premature death of nodes, we put the node energy as the routing factor in the routing, thus the lifetime of the whole network will be increased. Finally, aiming to enhance the convergence speed, we reserve the node pheromone for the subsequent path finding. Simulation results demonstrate the advantages of the proposed RA-ACA compared with TACA for DSON.

关键词： ant colony algorithm deep-space optical net-work (DSON) node energy undirectional links

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Research on MIMO beam integration optimization method based on PredRNN prediction and ant colony algorithm 14

Research on MIMO beam integration optimization method based ...

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14th International Symposium on antennas Propagation and EM Theory

作者： Zhu, Zhenhai Wu, Yuan Hao, Jiajia Hangzhou Zhejiang China Mobile Communicat Grp Design Inst Branch Hangzhou Zhejiang Peoples R China

ISBN: (纸本)9798350353129;9798350353136

With the rapid advancement of 5G base station construction and application, Massive MIMO technology has become an essential key technology in 5G network optimization, and accurate and efficient optimization of MIMO antenna beam configuration has become a research focus. For the optimization of MIMO antenna beam configuration, an integrated scheme based on PredRNN prediction and ant colony optimization is proposed. The experimental demonstration shows that the PredRNN prediction model is closer to the real user distribution, and the ant colony optimization algorithm can effectively solve the difficulties of multi-base station multi-beam joint optimization, thus improving the energy efficiency of 5G network.

关键词： Massive MIMO PredRNN prediction ant colony algorithm collaboration

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Continuous space ant colony algorithm for automatic selection of orthophoto mosaic seamline network

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ISPRS JOURNAL OF PHOTOGRAMMETRY AND REMOTE SENSING 2022年第0期186卷 201-217页

作者： Wang, Qingyang Zhou, Guoqing Song, Ruhao Xie, Yongfan Luo, Mengyuan Yue, Tao Guilin Univ Technol Coll Earth Sci Guilin 541006 Peoples R China Guilin Univ Technol Guangxi Key Lab Spatial Informat & Geomat Guilin 541004 Peoples R China Guilin Univ Technol Coll Geomat & Geoinformat Guilin 541004 Peoples R China

This paper proposes a novel method for selecting orthophoto mosaic seamline network using a continuous space ant colony algorithm. The method first establishes a cost function based on gray differences and a gray gradient in the overlapping area. Then, a continuous space ant colony algorithm is established to iteratively select a least cost path for the optimal mosaic seamline. This proposed algorithm is carried out in three steps: (1) generate the initial mosaic network using area Voronoi diagrams with overlap;(2) adjust the vertices (The intersection of mosaic seamline network);and (3) search the seamlines using the continuous space ant colony algorithm to obtain the globally optimal mosaic seamline network. Two groups of experiments were performed using different numbers of orthophotos. The results demonstrate that our method saves 50 s and 53 s compared with the commercial software OrthoVista in Dataset 1 and Dataset 2, and saves 19 s and 22 s compared with Dijkstra in Dataset 1 and Dataset 2, respectively. The average cost of the mosaic seamline network generated by our method is the lowest (15.56) out of OrthoVista (21.79), Dijkstra (18.35) and Qmosaic (18.68) in Dataset 1, and the lowest (19.28) out of OrthoVista (26.33), Dijkstra (22.60) and Qmosaic (23.56) in Dataset 2.

关键词： Mosaic seamline Continuous space ant colony algorithm Automatic selection Orthophoto

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Path Planning algorithm for Unmanned Surface Vehicle Based on Optimized ant colony algorithm

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IEEJ TRANSACTIONS ON ELECTRICAL AND ELECTRONIC ENGINEERING 2022年第7期17卷 1027-1037页

作者： Cui, Yani Ren, Jia Zhang, Yu Hainan Univ Sch Informat & Commun Engn Haikou 570228 Hainan Peoples R China Shandong Univ Art & Design Inst Naval Ind Design Qingdao 266555 Peoples R China

In order to construct an efficient and reliable global path for unmanned surface vehicles (USVs), this paper proposes a USV global path planning algorithm based on an optimized ant colony algorithm (OACA). The algorithm constructs a USV global path planning model by comprehensively considering energy consumption costs and turning control costs. In order to ensure the adaptability of the model to the task environment, the USV's motion characteristics are analyzed with full consideration of external interference, and on this basis, the characterization of energy consumption costs and turning control costs is completed. In order to obtain the global optimal solution of the model and accelerate the convergence speed of the model, in the initialization process of the ant colony algorithm, the initial pheromone is distributed unevenly by introducing the distance relationship among the intermediate node, the starting point, and ending point to improve the initial search efficiency. In the iterative process of searching for the optimal solution, enhancing the guidance effect of the current optimal solution on the offspring ants by introducing a weight factor to improve the update rule of pheromone, which accelerates the convergence speed of the algorithm. In the last two steps of the deadlock path, the number of lost ants is reduced by introducing a penalty factor to punish the pheromone which can guarantee the diversity of ants, and the algorithm's premature convergence is overcome. The simulation results prove the effectiveness of this algorithm. (c) 2022 Institute of Electrical Engineers of Japan. Published by Wiley Periodicals LLC.

关键词： unmanned surface vehicle path planning kinetic model ant colony algorithm

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Practice of English Platform Based on ant colony algorithm 2

Practice of English Platform Based on Ant Colony Algorithm

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2nd IEEE International Conference on Integrated Circuits and Communication Systems, ICICACS 2024

作者： Ai, Xizhen Nanchang Institute of Science & Technology Nanchang China

ISBN: (纸本)9798350317558

This electronic document is a 'live' template and already defines the components of your paper [title, text, heads, etc.] in its style sheet. *CRITICAL: Do Not Use Symbols, Special Characters, Footnotes, or Math in Paper Title or Abstract. (Abstract)The platform information practice exploration is critical in the constructive English learning platform;however it has an issue with erroneous performance positioning. The typical Particle swarm arithmetic is unable to address the information exploration issue in the constructive English learning platform, and the result is insufficient. As a result, a ant colony algorithm-based exploration of information practice of constructed English learning platform is provided, and the exploration of information practice of constructed English learning platform is assessed. To begin, the swarm behavior theory is used to discover the influencing elements, and the indicators are split based on the platform information practice exploration's needs to decrease interference factors in the platform information practice exploration. The swarm behavior theory is then used to create a ant colony algorithm platform information practice exploration scheme, and the outcomes of the platform information practice exploration are thoroughly examined. The MATLAB simulation results reveal that, under particular evaluation conditions, the ant colony algorithm outperforms the standard Particle swarm arithmetic in terms of platform information practice exploration accuracy and time of influencing variables. © 2024 IEEE.

关键词： ant colony algorithm Constructive English Learning Hands-on exploration swarm behavior theory

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