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Node topology location method of SDN social network based on ant colony algorithm

JOURNAL OF COMPUTATIONAL METHODS IN SCIENCES AND ENGINEERING 2022年第3期22卷 925-933页

作者： He, Lichun Li, Jing Xian Technol Univ Sch Elect Informat Engn Xian 710000 Shaanxi Peoples R China

Due to the convergence defect of the existing SDN social network node topology location methods, there is a large node topology location error problem. In order to solve the above problems, this paper proposes a topology location method of SDN social network nodes based on ant colony algorithm. Firstly, the ant colony algorithm is introduced, and then the biological principle of ant colony algorithm is analyzed to determine the basic steps of ant colony algorithm. According to the number of mobile beacon launch positions and specific launch coordinates in ROI, ant colony algorithm is introduced into the mobile beacon path acquisition program to realize SDN node topology location based on ant colony algorithm. The experimental results show that under the background of node communication radius of 2.0 and 5.0, the node topology positioning errors of this method are small, and the minimum errors are 9.10% and 5.15% respectively. It is fully proved that this method has good node topology positioning effect.

关键词： ant colony algorithm SDN social network node topology positioning method

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Analysis of Accurate Investment Strategy of Distribution Network Based on ant colony algorithm

Analysis of Accurate Investment Strategy of Distribution Net...

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2023 IEEE Global Conference on Information Technologies and Communications, GCITC 2023

作者： Wu, Baoxiu Zhu, Shaoyu Lin, Yixi Yan, Lei State Grid Zhangzhou Electrice Power Supply Company 363000 China

ISBN: (纸本)9798350308167

Nowadays, with the development of society, people need more and more energy for life, so all walks of life are also improving facilities and equipment, one of the most indispensable energy sources is electricity. Power supply companies have also been continuously improving the construction of the main network in recent years, and in the development of the future power grid, the construction of the distribution network is also a part that cannot be ignored. Therefore, the precise investment in the distribution network should be paid attention to. Traditional investment strategies cannot solve the problem of whether precise investment in distribution networks is feasible and reasonable. Therefore, this paper proposes an ant colony algorithm to analyze the accurate investment of distribution network. First, the computer is used to analyze and evaluate the investment strategy, and the indicators are divided according to the precise investment requirements of the distribution network to reduce it Interference factors in precise investment in distribution networks. Then, the computer evaluates the precise investment strategy of the distribution network, forms the precise investment plan of the distribution network, and conducts the precise investment results of the distribution network Comprehensive analysis. MATLAB simulation shows the rationality of the ant colony algorithm for accurate investment in distribution network under certain evaluation criteria The feasibility of precise investment in distribution network is better than that of traditional investment strategies. © 2023 IEEE.

关键词： ant colony algorithm computer distribution network Precise investment in distribution networks

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A Control Method for Regulating Power Supply Based on the Combination of ant colony algorithm and Genetic algorithm 1

A Control Method for Regulating Power Supply Based on the Co...

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1st IEEE International Conference on Ambient Intelligence, Knowledge Informatics and Industrial Electronics, AIKIIE 2023

作者： Liu, Yichi Wu, Fangquan Ji, Yuan Hu, Junhan Guizhou Power Grid Co. Guizhou China

ISBN: (纸本)9798350316469

Currently, the power system planning software developed domestically and internationally mainly focuses on the current power structure of fossil energy generation, based on traditional power generation optimization and scheduling models. Existing planning software platforms are difficult to adapt to the flexible regulation of coal electricity and new energy collaborative planning needs, and lack the construction of carbon emission assessment modules. This article designs a platform architecture for collaborative planning and carbon emission assessment of multiple types of regulated power sources and new energy, establishes a basic database for grid transmission network planning, develops functional modules for collaborative planning and carbon emission assessment of multiple types of regulated power sources and new energy, integrates key technologies for collaborative planning of multiple types of regulated power sources and new energy. The results indicate that this algorithm overcomes the shortcomings of genetic algorithm which can obtain the local optimal solution. It also shortens the task scheduling time of cloud computing system and achieves better task scheduling effect. The average cost of the tasks completed by the algorithm is obviously lower than that of the other two algorithms and the solution is better. © 2023 IEEE.

关键词： ant colony algorithm genetic algorithm multi type regulation power control transmission network

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Exploration of the Precise Management Mode of College Student Service Based on ant colony algorithm 1

Exploration of the Precise Management Mode of College Studen...

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1st IEEE International Conference on Ambient Intelligence, Knowledge Informatics and Industrial Electronics, AIKIIE 2023

作者： Yang, Yi Shandong Institute of Commerce and Technology Shandong Province Jinan250103 China

ISBN: (纸本)9798350316469

This article addresses the issue of unsatisfactory management effectiveness. Therefore, this article proposes an ant colony algorithm for service-oriented precision management analysis. Firstly, use positive feedback from information to evaluate the management model, and divide indicators according to the requirements of service-oriented precision management to reduce interference factors in service-oriented precision management. Then, feedback the information to service-oriented college students for precise management, forming a service-oriented precise management plan, and conducting a comprehensive analysis of the results of service-oriented precise management. MATLAB simulation shows that under certain evaluation criteria, ant colony algorithm is accurate in service-oriented and precise management of college student management. © 2023 IEEE.

关键词： ant colony algorithm positive feedback of information Precise management University Student Management

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UAV 3D Path Planning based on ant colony algorithm

UAV 3D Path Planning based on Ant Colony Algorithm

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2023 IEEE Global Conference on Information Technologies and Communications, GCITC 2023

作者： Du, Xikang Shenyang Aerospace University College of Mechanical and Electrical Engineering Liaoning Shenyang23456 China

ISBN: (纸本)9798350308167

Path planning technology is the core part of UAV field, the purpose of path planning is to provide a feasible and safe optimal path for UAV flight, to meet the feasibility of UAV operation, and improve the path optimization ability of UAV in complex and multi-obstacle environment. Traditional path planning algorithms have low computational efficiency and are prone to local extremes. In this paper, it is proposed that the three-dimensional path planning of UAV based on ant colony algorithm can improve the effectiveness of UAV dynamic constraint processing and enhance the path optimization ability in multi-obstacle environment. The advantages of this algorithm are fast convergence speed, simple calculation process, and few parameters, etc., and it has become the first choice for UAV planning three-dimensional path. At the same time, a multi-obstacle model is constructed in a three-dimensional environment, and the fitness function is constructed on the obstacle threat, path length and navigation height integration. After dynamic 3D environment simulation experiments, the results show that the ant colony algorithm can significantly improve the UAV path optimization ability and ensure the stability of 3D path planning. © 2023 IEEE.

关键词： 3D paths ant colony algorithm Path planning UAVs

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Optimization Model of Housing Construction Project Scheduling Based on Optimized ant colony algorithm 2

Optimization Model of Housing Construction Project Schedulin...

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2nd International Conference on Smart Technologies for Smart Nation, SmartTechCon 2023

作者： Srinivasa, Gowda G.K. Krishna, G.R. Sanjay Rex, J. Kumar, K. Sambath Kumar, Madhan Mohan Manikandan, N. Department of Computer Science and Engineering ACS College of Engineering Tamilnadu Bangalore India Department: Mechanical Engineering Koneru Lakshmaiah Education foundation Green fields Andhra Pradesh Vaddeswaram India Department of Civil Engineering Malla Reddy Engineering College Tamilnadu Hyderabad India Department of Electronics and Communication Engineering Vel Tech Rangarajan Dr.Sagunthala R&D Institute of Science and Technology Chennai India Department of Robotics and Automation Easwari Engineering College Bharathi salai Ramapuram Tamilnadu Chennai India Dept of Mechanical Engineering School of Engineering Mohan Babu University Andhra Pradesh Tirupati India

ISBN: (纸本)9798350305418

Construction management is a standardized means of project management. The construction project takes a long time and has many links, and the construction workers involved are complicated. Poor quality buildings will not only affect the construction enterprises’ brand, but also threaten the safety of people's lives and property. In this paper, an optimization model of housing construction project scheduling based on ant colony algorithm (ACA) is put forward. By studying the relationship among various sub-projects in the construction system of building projects, the management of building projects can be better realized. The results show that compared with the other two algorithms, the optimized ACA has certain advantages in recall and accuracy. There are many contents involved in the building construction process, and there are many uncontrollable factors in the building process, which greatly impact the project's construction quality. The construction industry can use this technology to strengthen the building construction management, solve the problems existing in the construction management, and improve the construction quality. © 2023 IEEE.

关键词： ant colony algorithm Building engineering Construction supervision Optimization Model Project scheduling

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Research on path planning of electric tractor based on improved ant colony algorithm 25

Research on path planning of electric tractor based on impro...

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25th International Conference on Electrical Machines and Systems (ICEMS)

作者： Liang Chuandong Lu Min Shihezi Univ Coll Mech & Elect Engn Shihezi Peoples R China

ISBN: (纸本)9781665493024

The emergence of electric tractors and related control technologies has accelerated the development of modern agriculture, but the path planning problem of electric tractors affects their operating range to a certain extent. In this paper, an improved ant colony algorithm is proposed to address the problems that the basic ant colony algorithm in the path planning of electric tractors is prone to local optimal solutions and slow convergence speed. Based on the idea of "Newton's cooling law", the pheromone volatility factor and state transfer probability function are improved to enhance the ability of global search in the early iteration of the algorithm and accelerate the convergence speed in the middle and late iteration;the early termination strategy of the algorithm iteration is introduced to reduce the iteration redundancy and shorten the running time of the algorithm;based on the kinematic model of the electric tractor, a mathematical model of energy loss is established to shorten the running time of the algorithm. Based on the kinematic model of electric tractor, the mathematical model of energy loss is established, and the evaluation index of the optimal path is established. The simulation results show that compared with the literature algorithm and the basic ant colony algorithm, the energy loss of the electric tractor is reduced by 18.31% and 28.96%, the optimal path length is shortened by 0.81% and 0.97%, and the running time is reduced by 20.13% and 18.43%, respectively. The comprehensive performance of the improved algorithm in this paper is excellent, which verifies the optimization effect.

关键词： Path planning Electric tractors ant colony algorithm Pheromone volatility factor State transfer probability function

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Routing networking technology based on improved ant colony algorithm in space-air-ground integrated network

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EURASIP JOURNAL ON ADVANCES IN SIGNAL PROCESSING 2024年第1期2024卷 34页

作者： Nie, Wuzhou Chen, Yong Wang, Yuhao Wang, Peizheng Li, Meng Ning, Lei Shenzhen Technol Univ Coll Big Data & Internet Shenzhen Peoples R China

Space-air-ground integrated networks comprise a multi-level heterogeneous integrated network that combines satellite-based, aerial, and terrestrial networks. With the increasing human exploration of space and growing demands for internet applications, space-air-ground integrated networks have gradually emerged as the direction for communication network development. These networks face various challenges such as extensive coverage, diverse communication node types, low-quality communication links, and simultaneous operation of multiple network protocols. However, the rapid development and widespread application of artificial intelligence and machine learning technologies in recent years have offered new perspectives and solutions for the communication architecture and routing algorithm research within space-air-ground integrated networks. In these networks, not all nodes can typically communicate directly with satellites;instead, a specific set of specialized communication nodes facilitates data communication between aerial and satellite networks due to their superior communication capabilities. Consequently, in contrast to traditional communication architectures, space-air-ground integrated networks, particularly in the terrestrial layer, often need to address challenges related to the diversity of communication node types and low-quality communication links. A well-designed routing approach becomes crucial in addressing these issues. Therefore, this paper proposes an AODV routing network protocol based on an improved ant colony algorithm (AC-AODV), specifically designed for the terrestrial layer within the space-air-ground integrated networks. By integrating information such as the type, energy, and location of communication nodes, this protocol aims to facilitate network communication. The objective is to guide information flow through nodes that are more suitable for communication, either by relaying communication or by connecting with satellites through speciali

关键词： Space-air-ground integration Terrestrial layer network ant colony algorithm Routing networking protocol

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Path Planning for Mobile Robots Based on Improved ant colony algorithm 6th

Path Planning for Mobile Robots Based on Improved Ant Colony...

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6th International Conference on Cognitive Computing (ICCC) Held as Part of the Services Conference Federation (SCF)

作者： Zhang, Jie Pan, Xiuqin Minzu Univ China Sch Informat Engn Beijing 100081 Peoples R China

ISBN: (纸本)9783031235849;9783031235856

In a two-dimensional environment, the traditional ant colony algorithm path planning is prone to problems, such as many turning points, easily falling into a local minimum, and the path is not smooth. To address these problems, a new improved ant colony algorithm is proposed to improve the path optimization performance. First, according to the position of the current grid relative to the start point and the end point, a non-uniform initial pheromone strategy is proposed, so that the closer the dominant grid is, the higher the pheromone concentration is, avoiding blind search by ants and reducing invalid search, and then the introduction of an angular guidance factor to increase the guidance to the end point and to avoid the probability of path zigzagging due to small differences in adjacent grid pheromones, next the pheromone update strategy with a reward and punishment mechanism, the enhancement and decay factors are introduced to adjust the pheromone values adaptively to improve the convergence of the algorithm, final the improved ant colony algorithm and genetic algorithm are fused, and the path is smoothed using the piecewise B-spline curve strategy. The experimental results show that the improved algorithm has greatly improved both the optimization finding ability and the convergence ability.

关键词： Path planning ant colony algorithm Non-uniform pheromone Angular guidance factor Reward and punishment mechanism Enhancement factors Decay factors Genetic algorithm Piecewise B-spline curve

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Monte Carlo calculation of the photon beam quality correction factor kQ, Q0 for ionization chambers of very small volume: Use of variance reduction techniques driven with an ant colony algorithm

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RADIATION PHYSICS AND CHEMISTRY 2024年 225卷

作者： Garvi, A. M. Zamora, L. I. Anguiano, M. Lallena, A. M. Garcia-Pareja, S. Univ Granada Dept Fis Atom Mol & Nucl E-18071 Granada Spain Hosp Reg Univ Virgen Nieves Serv Fis & Protecc Radiol E-18014 Granada Spain Univ Granada Complejo Hosp Univ Granada Inst Invest Biosanit Ibs GRANADA E-18016 Granada Spain Hosp Univ Reg Malaga UGC Radiofis Hosp Avda Carlos Haya S-N E-29010 Malaga Spain

Purpose : To evaluate the effectiveness of an ant colony algorithm in implementing variance reduction techniques in the Monte Carlo computation of the photon beam quality correction factor kQ , Q 0 for ionization chambers characterized with very small active volumes. Methods: The Monte Carlo code PENELOPE has been utilized to compute the photon beam quality correction factor kQ , Q 0 for the Semiflex 3D 31021 ionization chamber, which has an active volume of 0.071 . 071 cm3. 3 . Various clinical photon beams generated with nominal potentials from 4 to 25 MV have been considered, with a 60 Co beam serving as the reference. The calculation involved determining the absorbed dose to both water and the sensitive volume of the ionization chamber. This information was used to derive the f c,Q , Q factors for the photon beams and the f c,Q0 , Q 0 factor for the 60 Co beam, whose ratio provides the k Q , Q 0 factors. Results: The algorithm has been initially validated by comparing with analog simulations where no variance reduction techniques are applied. The results have demonstrated an efficiency improvement ranging from a factor of 7 to 44. By incorporating the ant colony algorithm along with the variance reduction techniques, the determination of TPR 20 10 values for various studied photon beams has been achieved. The calculated k Q , Q 0 factors agree with previously published values. Two distinct protocols outlined in the TRS-398 have been taken into account and the results obtained for these protocols were compared to explore any differences between them. Conclusions: The ant colony algorithm facilitates the automatic application of variance reduction techniques, such as splitting and Russian roulette, without the need to delve into the geometric intricacies of the simulation. This automated approach results in increased efficiency, enabling simulations to be conducted within reasonable times while maintaining uncertainties at levels that ensure reliability.

关键词： ant colony algorithm Splitting Russian roulette Monte Carlo PENELOPE Ionization chamber Beam quality correction factor

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