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Comparative research on the formation of backbone media of wireless self-organizing network by DLA-GF algorithm and ant colony algorithm

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ALEXANDRIA ENGINEERING JOURNAL 2022年第2期61卷 949-961页

作者： Li, Sihao Gao, Tian Ye, Zhipeng Wang, Yaxing Xian Jiaotong Liverpool Univ Dept Elect & Elect Engn Suzhou 215123 Jiangsu Peoples R China Xian Jiaotong Liverpool Univ Comp Sci & Software Engn Suzhou 215123 Jiangsu Peoples R China

A mobile ad hoc network is a complicated distributed system organized by mobile terminals or wireless nodes through wireless connections. The mobile ad hoc network is suitable for those who lack basic communication equipment or do not have technical communication equipment, and the price is relatively high and impractical. It is agreed that the node can move and maintain the connection when connecting or leaving at any time. Wireless ad hoc network routing technology occupies an important position in wireless networks. First, wireless communication depends on wireless routing. At present, it is necessary to select an appropriate route for transmission on wireless communication. Therefore, routing of wireless ad hoc networks is the most important technology in wireless networks. Because the network is a free combination of mobile users, and the bandwidth of the wireless connection network is relatively limited. Network topology Since each node in the network can join or move freely, it is very important to find a link for forwarding data in a dynamic network. This article analyzes the common problems of hop count in MANET networks and compares the backbone of MANET. The wireless ad hoc network composed of DLA-GF algorithm and ant colony algorithm proposes an effective method to detect the routing in the wireless ad hoc network. Combined with route detection, the node sends multiple copies of the hop count packet to increase node communication Degree. The algorithm can effectively overcome the problem of ambiguity in the number of hops in wireless ad hoc networks, and achieve the effect of saving network energy and reducing power consumption. (C) 2021 THE AUTHORS. Published by Elsevier BV on behalf of Faculty of Engineering, Alexandria University

关键词： DLA-GF algorithm ant colony algorithm Structure optimization Wireless self-organizing network Routing protocol

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An inverse analysis method to identify maximum overfire temperature based on an improved ant colony algorithm

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JOURNAL OF BUILDING ENGINEERING 2022年 59卷

作者： Cui, Jing Guo, Xiaoming Zhan, Yang Pang, Rui Henan Univ Technol Sch Civil Engn Zhengzhou Peoples R China HAUT Henan Key Lab Grain & Oil Storage Facil & Safety Zhengzhou Peoples R China Southeast Univ Sch Civil Engn Nanjing Peoples R China Nanjing Inst Technol Sch Civil Engn & Architecture Nanjing Peoples R China

There are many causes of building fire incidents that can manifest in many forms. Overfire temperature is one of the most important factors affecting structural residual deformation, and it is the basic parameter for postfire structural safety evaluations. To study the overfire temperature and the temperature field distribution of a structure under fire, an overfire temperature inversion method based on an improved ant colony algorithm has been proposed, where the entire structure is discretized into multiple zones and the zonal maximum overfire temperature is assumed to be the load action. The finite element software ANSYS is used for developing a numerical model of the structure, and a positive analysis is applied to the mechanical response of the structure under fire. As a result, the residual displacements of each zone are obtained, the minimum differences between the numerical and measured displacements are considered as the target function, the overfire temperature is assumed to be the design variable, the improved ant colony algorithm is utilised to inversely analyse the structure at the overfire temperature, the highest overfire tem-perature is determined, and the temperature field distribution of the structure under fire is ob-tained. Furthermore, a scale model fire test of the space grid structure is performed, and the fire temperature and node displacements are recorded. The inverse method is applied to the fire test model to verify its feasibility and effectiveness. The results suggest that the ant colony algorithm has good applicability to structure overfire temperature inverse analysis.

关键词： ant colony algorithm Overfire temperature Inverse analysis Space grid structure

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Research on green single machine scheduling based on improved ant colony algorithm

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MEASUREMENT & CONTROL 2022年第1-2期55卷 35-48页

作者： Qiao, Dongping Wang, Yajing Pei, Jie Bai, Wentong Wen, Xiaoyu Zhengzhou Univ Light Ind Coll Mech & Elect Engn Zhengzhou Peoples R China Zhengzhou Univ Light Ind Henan Key Lab Intelligent Mfg Mech Equipment Zhengzhou Peoples R China

This paper studies the green single-machine scheduling problem that considers the delay cost and the energy consumption of manufacturing equipment and builds its integrated optimization model. The improved ant colony scheduling algorithm based on the Pareto solution set is used to solve this problem. By setting the heuristic information, state transition rules, and other core parameters reasonably, the performance of the algorithm is improved effectively. Finally, the model and the improved algorithm are verified by the simulation experiment of 10 benchmark cases.

关键词： ant colony algorithm single-machine scheduling sequence-dependent setups times weighted tardiness manufacturing energy consumption

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Design of Intelligent Test Paper Generation System for Online Psychological Testing Based on ant colony algorithm 3

Design of Intelligent Test Paper Generation System for Onlin...

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3rd Asia-Pacific Conference on Communications Technology and Computer Science (ACCTCS)

作者： Sun, Yan Bohai Univ Coll Educ Sci Jinzhou Peoples R China

ISBN: (纸本)9798350310801

In the calculation process of ant colony algorithm, the ant colony transfer is guided by the pheromone intensity and distance of each path, and the path of ant colony movement always tends to the path with the strongest information. Due to the influence of pheromone concentration, the subsequent ants have a higher probability of choosing a shorter path, thus forming a positive feedback mechanism, and eventually the entire ant colony will find an optimal path to find food sources. Intelligent paper grouping problem is actually a process of combinatorial optimization of the target according to the given constraints, so as to obtain the best solution. The traditional psychological test has many problems such as single test question, low test frequency and disclosure of personal privacy, so the results of psychological test are often not authentic. The network psychological test database is constructed, and the paper is automatically assembled based on ant colony algorithm. The convergence speed is fast, the robustness is outstanding, and it is convenient to realize the global algorithm.

关键词： ant colony algorithm network psychological test intelligent test paper generation system design mathematical model test paper generation process

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Research on the Emergency Evacuation Route in the Far Sea Based on ant colony algorithm

Research on the Emergency Evacuation Route in the Far Sea Ba...

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International Conference on SmartRail, Traffic, and Transportation Engineering, ICSTTE 2023

作者： Han, Yulong Lin, Zheng Zhang, Ruiyi Zheng, Wenpei Zhang, Yaru Co. Ltd. Zhanjiang Branch Zhanjiang China School of Safety and Ocean Engineering China University of Petroleum Beijing China

ISBN: (纸本)9789819736812

In order to improve the two-dimensional path planning and dynamic obstacle avoidance capabilities of emergency evacuation in the South China Sea, the emergency evacuation path planning in the exploration area of offshore platforms was carried out. According to the current distribution of islands in a certain area of the ocean, combined with the factors such as offshore islands, reefs, and reef depths, the regional environmental model of floating wharf is constructed, and the structure of the genetic algorithm is optimized by distinguishing the obstacle area and the free navigation area, and the optimal navigation route is searched based on the improved ant colony algorithm, the actual island parameters are selected, and the case planning is carried out based on the ant colony algorithm. After 100 iterations, the ship path fluctuated from the initial 40 times to the final stable 27 times, which shows that the algorithm found the shortest path, calculated the simulation distance, and planned the shortest path, which provides a reference for ship evacuation and material transportation. © The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2024.

关键词： ant colony algorithm Emergency Evacuation Far Sea Floating Wharf

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A hybrid ant colony algorithm for the winner determination problem

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MATHEMATICAL BIOSCIENCES AND ENGINEERING 2022年第3期19卷 3202-3222页

作者： Wu, Jun Fan, Mingjie Liu, Yang Zhou, Yupeng Yang, Nan Yin, Minghao Northeast Normal Univ Informat Sci & Technol Changchun Peoples R China Beijing Univ Posts & Telecommun Sch Sci Beijing Peoples R China CHEARI Certificat & Testing Co Ltd Beijing Peoples R China Northeast Normal Univ Key Lab Appl Stat MOE Changchun Peoples R China

Combinatorial auction is an important type of market mechanism, which can help bidders to bid on the combination of items more efficiently. The winner determination problem (WDP) is one of the most challenging research topics on the combinatorial auction, which has been proven to be NP-hard. It has more attention from researchers in recent years and has a wide range of real-world applications. To solve the winner determination problem effectively, this paper proposes a hybrid ant colony algorithm called DHS-ACO, which combines an effective local search for exploitation and an ant colony algorithm for exploration, with two effective strategies. One is a hash tabu search strategy adopted to reduce the cycling problem in the local search procedure. Another is a deep scoring strategy which is introduced to consider the profound effects of the local operators. The experimental results on a broad range of benchmarks show that DHS-ACO outperforms the existing algorithms.

关键词： ant colony algorithm local search combinatorial auction winner determination problem tabu search

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Optimizing Fresh Logistics Distribution Route Based on Improved ant colony algorithm

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Computers, Materials & Continua 2022年第10期73卷 2079-2095页

作者： Daqing Wu Ziwei Zhu Dong Hu Romany Fouad Mansour College of Economics and Management Shanghai Ocean UniversityShanghai201306China Nanchang Institute of Technology Nanchang330044China Shanghai Jianqiao College Shanghai201306China Department of Mathematics Faculty of ScienceNew Valley UniversityEl-Karaga72511Egypt

With the rapid development of the fresh cold chain logistics distribution and the prevalence of low carbon concept,this paper proposed an optimization model of low carbon fresh cold chain logistics distribution route considering customer satisfaction,and combined with time,space,weight,distribution rules and other constraints to optimize the distribution *** the same time,transportation cost,penalty cost,overloading cost,carbon tax cost and customer satisfaction were considered as the components of the objective function,and the thought of cost efficiency was taken into account,so as to establish a distribution model based on the ratio of minimum total cost to maximum satisfaction as the objective ***,the improved A∗algorithm and ant colony algorithm were used to construct the model *** the simulation analysis results of different calculation examples,the effectiveness,efficiency and correctness of the design of the single target low-carbon fresh agricultural products cold chain model by using the improved ant colony algorithm were verified.

关键词： Carbon tax cost vehicle routing problem cold chain ant colony algorithm

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An improved ant colony algorithm for integrating global path planning and local obstacle avoidance for mobile robot in dynamic environment br

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MATHEMATICAL BIOSCIENCES AND ENGINEERING 2022年第12期19卷 12405-12426页

作者： Gong, Chikun Yang, Yuhang Yuan, Lipeng Wang, Jiaxin Univ Shanghai Sci & Technol Coll Mech Engn Shanghai 200093 Peoples R China Harbin Inst Technol Sch Mech & Elect Engn Harbin 15001 Peoples R China Heilongjiang Univ Fac Western Languages Harbin 150080 Peoples R China

To improve the path optimization effect and search efficiency of ant colony optimization (ACO), an improved ant colony algorithm is proposed. A collar path is generated based on the known environmental information to avoid the blindness search at early planning. The effect ofthe ending point and the turning point is introduced to improve the heuristic information for high search efficiency. The adaptive adjustment of the pheromone intensity value is introduced to optimize the pheromone updating strategy. A variety of control strategies for updating the parameters are given to balance the convergence and global search ability. Then, the improved obstacle avoidance strategies are proposed for dynamic obstacles of different shapes and motion states, which overcome the shortcomings of existing obstacle avoidance strategies. Compared with other improved algorithms in different simulation environments, the results show that the algorithm in this paper is more effective and robust in complicated and large environments. On the other hand, the comparison with other obstacle avoidance strategies in a dynamic environment shows that the strategies designed in this paper have higher path quality after local obstacle avoidance, lower requirements for sensor performance, and higher safety

关键词： path planning mobile robot ant colony algorithm local obstacle avoidance strategy

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Research on Video Object Detection algorithm for Intangible Cultural Heritage Based on ant colony algorithm

Research on Video Object Detection Algorithm for Intangible ...

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2024 International Conference on Optimization Computing and Wireless Communication, ICOCWC 2024

作者： Liu, Yiou Huang, Yingfei Huang, Haimin Network and New Media Hunan International Economics University Changsha Hunan410000 China

ISBN: (纸本)9798350383348

the level of inheritance of intangible cultural heritage, intangible cultural heritage followed. In the case of intangible cultural heritage, it is very important to collect, analyze, and process the information of the living beings in the intangible cultural heritage, so as to realize the inheritance of intangible cultural heritage. Neural network algorithms cannot accurately collect and analyze information problems in intangible cultural heritage. Therefore, an ant colony algorithm is proposed to analyze the video target detection algorithm. Firstly, computer technology is used to collect Internet information, and the indicators is divided according to the requirements of the video target detection algorithm to reduce the interference factors in the video target detection algorithm. Then, the computer technology forms a video object detection algorithm scheme based on the results of the video object detection algorithm of intangible cultural heritage, and comprehensively analyzes the results of the video object detection algorithm. © 2024 IEEE.

关键词： ant colony algorithm computer technology intangible cultural heritage Video object detection algorithm

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Computer Application in Game Map Path-Finding Based on Fuzzy Logic Dynamic Hierarchical ant colony algorithm

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INTERNATIONAL JOURNAL OF FUZZY SYSTEMS 2022年第5期24卷 2513-2524页

作者： Zhu, Qingkun Kumar, Priyan Malarvizhi Alazab, Mamoun Zhengzhou Presch Educ Coll Informat Management Dept Zhengzhou 450000 Henan Peoples R China Kyung Hee Univ Dept Comp Sci & Engn Seoul South Korea Charles Darwin Univ IT & Environm Casuarina Australia

A large number of researchers recently focused on intelligent analysis about algorithms for path-finding concerning games. Currently, the most modern application in game map path-finding is based on the fuzzy logic (FL) algorithm. It demonstrates that these strategies increase the quest performance and have a simpler direction to enhance the algorithm's game. Hence, in this paper, a Fuzzy logic-based game path-finding Framework (FLGPFF) has been proposed to reduce the search space to improve search speed and path planning on uneven surfaces. The suggested FLGPFF method uses computer vision to simulate the fuzzy dynamic game path's algorithm using possible multi-purpose platforms. A computer vision explores the whole game map path and finds a way between two remote places. The fuzzy method uses a fuzzier, center average demulsifier, and product inference engine. The ant colony algorithm is used for the complex environment with many moving obstacles and, using a weighted artificial field method, it calculates a trajectory from the target's initial location. Thus, the experimental results show the FLGPFF to enhance path allocation prediction and less delay time than other popular methods. The simulation outcome recommended that FLGPFF can improve the accuracy ratio (95.2%), search timer per map (96.3%), game quality improvement ratio (98.5%), performance ratio (97.8%), and comparison of the path-finding model (95.1%).

关键词： ant colony algorithm Computer application Fuzzy logic Game map path-finding

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