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Data Fusion for Wireless Sensor Networks Based on Hybrid ant Colony algorithm 2019

Data Fusion for Wireless Sensor Networks Based on Hybrid Ant...

2nd International Conference on Geoinformatics and Data Analysis (ICGDA) / 2nd International Conference on Software and Services Engineering (ICSSE)

作者： Wang, Lihong Han, Xue Heihe Univ Heihe Heilongjiang Peoples R China

ISBN: (纸本)9781450362450

A hybrid ant algorithm is proposed for wireless sensor networks data fusion, which to improve the efficiency of data integration and rextend the network lifetime. Not only the energy consumption is considered, but also the data transmission delay is considered. First, Making use of the advantages of ant algorithm in searching for the shortest path, the algorithm construct the shortest path. To overcome the disadvantages of prematurity and slow the rate of convergence in ant algorithm, At the same time, a variable neighborhood search mutation operator is applied to optimize search results. when iterrations number is achieved. Experiment results show that the algorithm which reduce energy consumption and network delay, is more stable and has better perfoming.

关键词： Wireless Sensor Network Data Fusion ant algorithm

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Enumerating Knight's Tours using an ant colony algorithm

Enumerating Knight's Tours using an ant colony algorithm

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IEEE Congress on Evolutionary Computation

作者： Hingston, P Kendall, G Edith Cowan Univ Mt Lawley WA 6050 Australia

ISBN: (纸本)0780393635

In this paper we show how an ant colony optimisation algorithm may be. used to enumerate knight's tours for variously sized chessboards. We have used the algorithm to enumerate all tours on 5x5 and 6x6 boards, and, while the number of tours on an 8x8 board is too large for a full enumeration, our experiments suggest that the algorithm is able to uniformly sample tours at a constant, fast rate for as long as is desired.

关键词： game theory optimisation ant colony optimisation chessboard knight tours ant algorithm ant colony optimization Optimization algorithms algorithms

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Application of Collaborative ant Colony algorithm for Railway Optimal Stowage Problem with Category Restriction

Application of Collaborative Ant Colony Algorithm for Railwa...

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2nd International Asia Conference on Informatics in Control, Automation and Robotics (CAR)

作者： Wang Hai-xing Li Zhen-jiang Beijing Jiaotong Univ Beijing 100044 Peoples R China

ISBN: (纸本)9781424451944

Collaborative ant colony algorithm (ACA) was presented for Railway Optimal Stowage Problem with Category Restriction (ROSPCR). Having distinguished the differences of specific volume between the used loading capacity and the remained, a new ACA is devised. Then improvement concerning the rules of route construction and pheromone updating is adopted on the basis of former algorithm to optimize the loading capacity and volume of vehicles, besides the least number of vehicles needed in various conditions, thus making the algorithm a more practical one. Finally an example is put forward and analyzed, proving that the ACA designed in this paper is feasible and efficient in determining the optimal loading plan with ROSPCR.

关键词： ant algorithm loading capacity STOWAGE vehicle specific volume railways

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Combination of genetic algorithm and ant algorithm and its application to QoS multicast routing

Wuhan Ligong Daxue Xuebao (Jiaotong Kexue Yu Gongcheng Ban)/...

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Wuhan Ligong Daxue Xuebao (Jiaotong Kexue Yu Gongcheng Ban)/Journal of Wuhan University of Technology (Transportation Science and Engineering) 2005年第6期29卷 932-935页

作者： Qu, Jianwei Li, Layuan Department of Computer Science Wuhan University of Technology Wuhan 430063 China

The multicast routing problem with QoS constraints such as delay, delay jitter, bandwidth and packet loss metrics is discussed. A network model that is suitable to study such routing problems is described. A combination of genetic algorithm and ant algorithm (GAAA) is given for multiple constrained QoS multicast routing. It adopts genetic algorithm to solve and to give information pheromone, to distribute and make use of its ability of quickness and randomness on a globally searching. At the same time, it gives a well solution making use of the characteristics of ant algorithm, converges on optimization pass information pheromone quickly. Simulation results show that the algorithm is valid and effective.

关键词： ant algorithm GAAA algorithm Genetic algorithm Multicast routing QoS routing

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Multiple ant colonies algorithm based on colony level interactions

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IEICE TRANSACTIONS ON FUNDAMENTALS OF ELECTRONICS COMMUNICATIONS AND COMPUTER SCIENCES 2000年第2期E83A卷 371-379页

作者： Kawamura, H Yamamoto, M Suzuki, K Ohuchi, A Hokkaido Univ Grad Sch Engn Sapporo Hokkaido 0608628 Japan

Recently, researchers in various fields have shown interest in the behavior of creatures from the viewpoint of adaptiveness and flexibility. ants, known as social insects, exhibit collective behavior in performing tasks that can not be carried out by an individual ant. In ant colonies. chemical substances, called pheromones, are used as a way to communicate important information on global behavior. For example. ants looking for food lay the way back to their nest with a specific type of pheromone. Other ants can follow the pheromone trail and find their way to baits efficiently. In 1991, Colorni et al. proposed the ant algorithm for Traveling Salesman Problems (TSPs) by using the analogy of such foraging behavior and pheromone communication. In the ant algorithm, there is a colony consisting of many simple ant agents that continuously visit TSP cities with opinions to prefer subtours connecting near cities and they lay strong pheromones. The ants completing their tours lay pheromones of various intensities with passed subtours according to distances. Namely, subtours in TSP tourns that have the possibility of being better tend to have strong pheromones, so the ant agents specify good regions in the search space by using this positive feedback mechanism. In this paper, we propose a multiple ant colonies algorithm that has been extended from the ant algorithm. This algorithm as several ant colonies for solving a TSP, while the original has only a single ant colony. Moreover, two kinds of pheromone effects, positive and negative pheromone effects, are introduced as the colony-level interactions. As a result of colony-level interactions, the colonies can exchange good schemata for solving a problem and can maintain their own variation in the search process. The proposed algorithm shows better performance than the original algorithm with almost the same agent strategy used in both algorithms except for the introduction of colony-level interactions.

关键词： multi-agent system ant algorithm traveling salesman problems combinatorial optimization problems

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Shortest-Path Routing Based on ant-algorithm

Shortest-Path Routing Based on Ant-Algorithm

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2004 International Symposium on Distributed Computing and Applications to Business, Engineering and Science

作者： Min LianYing,Yang JinYong School of Computer Science and Technology,Wuhan University of Technology Wuhan,Hubei,430063,China

In this paper we first analyze the theory of ant algorithm and its math model,then we put forward a novel approach to solve the shortest-path-routing problem that uses the ant *** we set up an experiment to testify th... 详细信息

关键词： ant algorithm The Shortest-Path Routing

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Adaptive Learning Model Based on ant Colony algorithm

INTERNATIONAL JOURNAL OF EMERGING TECHNOLOGIES IN LEARNING

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INTERNATIONAL JOURNAL OF EMERGING TECHNOLOGIES IN LEARNING 2019年第1期14卷 49-57页

作者： Li, Rongxia Chongqing Technol & Business Univ Modern Int Acad Design Art Chongqing 401120 Peoples R China

To better respond to people's demands for multimedia learning, appropriate learning paths should be offered based on their actual learning demands and different knowledge levels. Adaptive online learning model integrates and improves existing learning frameworks to offer a set of knowledge paths that can cater to differ7ent preferences, tastes, and knowledge levels of learners, no need for them to be aware of this. Based on the improved ant colony algorithm, an adaptive learning system model that can satisfy learners' demands is built herein with reference to the foraging approach of ants to traverse the paths, thereby to find the best learning path, while the classification method for some learning objects can determine the search parameters. This innovative approach proposed hereof can help improve learners' academic performance and learning efficiency.

关键词： ant algorithm adaptive learning learning path learning style

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A time synchronization scheme for sensor networks based on ant colony algorithm

A time synchronization scheme for sensor networks based on a...

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11th International Conference on Wireless Communications, Networking and Mobile Computing (WiCOM 2015)

作者： Nuo Wei Ming Lei Shu Ming Yang Chang Fang Chen Shandong Provincial Key Laboratory of Computer Networks Jinan China

ISBN: (纸本)9781510821279

Time synchronization has received a great attention as its crucial parts in wireless sensor networks. To minimize the number of transmission packets and achieve energy efficiency, a time synchronization scheme based on ant colony algorithm (TSAC) is presented in this paper. By exploiting the principle of ant colony algorithm adjusting the pheromone dynamically and automatically, an optimum pair selection theme is designed to select the nodes synchronized by performing the pairwise synchronization, and all the other nodes could be synchronized by listening. The simulation results show that TSAC needs less message exchanges and provides more accuracy than other time synchronization algorithms.

关键词： ant Colony algorithm Time Synchronization Wireless Sensor Networks ant algorithm clock recovery Wireless sensor networks

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Data Fusion for Wireless Sensor Networks Based on Hybrid ant Colony algorithm

Data Fusion for Wireless Sensor Networks Based on Hybrid Ant...

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作者： Lihong WANG Xue HAN Heihe University

A hybrid ant algorithm is proposed for wireless sensor networks data fusion, which to improve the efficiency of data integration and rextend the network lifetime. Not only the energy consumption is considered,but also the data transmission delay is considered. First, Making use of the advantages of ant algorithm in searching for the shortest path, the algorithm construct the shortest *** overcome the disadvantages of prematurity and slow the rate of convergence in ant algorithm, At the same time, a variable neighborhood search mutation operator is applied to optimize search *** iterrations number is achieved. Experiment results show that the algorithm which reduce energy consumption and network delay,is more stable and has better perfoming.

关键词： Wireless Sensor Network Data Fusion ant algorithm

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Missile Trajectory Optimization Using a Modified ant Colony algorithm

Missile Trajectory Optimization Using a Modified Ant Colony ...

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IEEE Aerospace Conference

作者： Zachary J. Kiyak Roy J. Hartfield Timothy W. Ledlow Department of Aerospace Engineering Auburn University

ISBN: (纸本)9781479916191

A modified ant colony optimization (ACO) algorithm is applied to a single-stage solid missile design problem involving six degrees of freeedom (6-DOF) flight trajectory modeling. A local search procedure is also integrated with the algorithm, adding a search intensification ability that compliments the ability of ACO to thoroughly explore a solution space. The goal of this work is to evaluate the effectiveness of the ant colony optimization scheme by comparing its solution output quality with those of other, well-known optimization methods. Performance is based on solution "fitness", or how closely each solution matches a specific set of performance objectives, as well as the number of calls to the objective function that are required in order to reach that solution. Additionally, an important performance criterion is to determine each algorithm's capabilities of finding, not only a single quality solution to a design problem, but also a diverse set of additional, near-optimal solutions. The results of this study demonstrate that the modified ACO algorithm is a viable candidate as a high-performance optimization method, while the added local search method may or may not be a worthwile addition for the attempted optimization problem.

关键词： ant algorithm ADMINISTRATIVE CONSENT ORDER trajectory optimization missile trajectories design problems Solutions PERFORMANCE OBJECTIVES optimization method Performance metrics Solution space Search methods ant colony optimization Solution

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