检索结果-内蒙古大学图书馆

8th International Conference on Intelligent systems Design and Applications (ISDA 2008)

作者： Djamarus, Djasli Ku-Mahamud, Ku Ruhana Trisakti Univ Dept Informat Jakarta 11440 Indonesia Univ Utara Malaysia Coll Arts & Sci Kedah Malaysia

ISBN: (纸本)9780769533827

This paper presents a proposed ant system algorithm that incorporates negative pheromone to solve the course scheduling problem. The performance of the proposed algorithm is tested with a case study data on course scheduling. Comparisons of results were performed with ant system algorithm that does not incorporate the negative pheromone.

关键词： ant system algorithm Course Scheduling Problem Meta-heuristic Negative Pheromone

来源：评论

学校读者我要写书评

暂无评论

Deterministic Model for Analyzing the Dynamics of ant system algorithm and Performance Amelioration through a New Pheromone Deposition Approach

Deterministic Model for Analyzing the Dynamics of Ant System...

引用

4th International Conference on Information and Automation for Sustainability

作者： Acharya, Ayan Maiti, Deepyaman Konar, Amit Ramadoss, Janarthanan Jadavpur Univ Dept Elect & Telecommun Engn Kolkata 700032 India Jaya Engn Coll Dept Informat Technol Madras 600017 Tamil Nadu India

ISBN: (纸本)9781424428991

ant Colony Optimization (ACO) is a metaheuristic for solving difficult discrete optimization problems. This paper presents a deterministic model based on differential equation to analyze the dynamics of basic ant system algorithm. Traditionally, in all ant system algorithms developed so far, the deposition of pheromone on different parts of the tour of a particular ant is always kept unvarying. This implies that the pheromone concentration remains uniform throughout the entire path of an ant. This article introduces an exponentially increasing pheromone deposition approach by artificial ants to improve the performance of basic ant system algorithm. The idea here is to introduce an additional attracting force to guide the ants towards destination more easily by constructing an artificial potential field identified by increasing pheromone concentration towards the goal. Apart from carrying out analysis of ant system dynamics with both traditional and the newly proposed deposition rules, the paper presents an exhaustive set of experiments performed to find out suitable parameter ranges for best performance of ant system with the proposed deposition approach. Simulations with this empirically obtained parameter set reveal that the proposed deposition rule outperforms the traditional one by a large extent both in terms of solution quality and algorithm convergence. Thus, the contributions of the article can be presented as follows: i) it introduces differential equation and explores a novel method of analyzing the dynamics of ant system algorithms, ii) it initiates an exponentially increasing pheromone deposition approach by artificial ants to improve the performance of algorithm in terms of solution quality and convergence time, iii) exhaustive experimentation performed facilitates the discovery of an algebraic relationship between the parameter set of the algorithm and feature of the problem environment.

关键词： ant system algorithm Stability Analysis of ant system dynamics Uniform deposition rule Non-uniform pheromone deposition approach Solution Quality Convergence Speed

来源：评论

学校读者我要写书评

暂无评论

Satellite Constellation Design with Adaptively Continuous ant system algorithm

引用

Chinese Journal of Aeronautics 2007年第4期20卷 297-303页

作者： He Quan Han Chao School of Astronautics Beijing University of Aeronautics and Astronautics Beijing 100083 China

The ant system algorithm （ASA） has proved to be a novel meta-heuristic algorithm to solve many multivariable problems. In this paper, the earth coverage of satellite constellation is analyzed and a n ＋ 1^ -fold coverage rate is put forward to evaluate the coverage performance of a satellite constellation. An optimization model of constellation parameters is established on the basis of the coverage performance. As a newly developed method, ASA can be applied to optimize the constellation parameters. In order to improve the ASA, a rule for adaptive number of ants is proposed, by which the search range is obviously enlarged and the convergence speed increased. Simulation results have shown that the ASA is more quick and efficient than other methodV211.71s.

关键词： ant system algorithm satellite constellation optimization design coverage performance adaptive adjusting

来源：评论

学校读者我要写书评

暂无评论

A Continuous ant Colony (C-ant) algorithm solving the Economic Load Dispatch (ELD) Problem

引用

JOURNAL OF INFORMATION & OPTIMIZATION SCIENCES 2011年第1期32卷 1-13页

作者： Vlachos, Aristidis Petikas, Isidoros Kyriakides, Simos Univ Piraeus Dept Informat 80Karaoli & Dimitriou St Piraeus 18534 Greece

Classic algorithms that are based on the ant system theory have been designed to face problems with discrete solutions. When dealing with non discrete problems, in order to apply ant Colony Optimization (AGO) algorithms they should be transformed to discrete problems. The arbitrary limitation of the number of possible solutions for each space is the result of the transformation of the solutions of the problems from the continuous to the discrete workspace. Hence, the choice of the width of the solutions spaces essentially defines the possible best solutions of the problem. In order to deal with this disadvantage, we present a new algorithm: the Continuous ant Colony (C-ant). This algorithm encourages local searching around the best solution found in each iteration. The proposed (C-ant) is applied to a simple ELD problem composed of 4 generators. Comparison to conventional Particle Swarm Optimization (PSO) algorithms is presented.

关键词： Economic Load Dispatch (ELD) ant Colony Optimization (AGO) ant system algorithm combinatorial optimization oower system.

来源：评论

学校读者我要写书评

暂无评论

Adaptive Artificial ant Colonies for Edge Detection in Digital Images

Adaptive Artificial Ant Colonies for Edge Detection in Digit...

引用

36th Annual Conference of the IEEE Industrial-Electronics-Society (IECON)/4th IEEE International Conference on E-Learning in Industrial Electronics/IES Industry Forum

作者： Jevtic, Aleksandar Andina, Diego Tech Univ Madrid Grp Automat Signal & Commun Madrid Spain

ISBN: (纸本)9781424452262

ant Colony Optimization (ACO) is a group of algorithms inspired by the foraging behavior of ant colonies in nature. Like their biological counterparts, a colony of artificial ants is able to adapt to the changes in their environment, such as exhaustion of a food source and discovery of a new one. In this paper, one of the basic ACO algorithms, the ant system algorithm, was applied for edge detection where the edge pixels represent food for the ants. A set of grayscale images obtained by a nonlinear contrast enhancement technique called Multiscale Adaptive Gain is used to create a variable environment. As the images change, the ant colony adapts to those changes leaving pheromone trails where the new edges appear while the pheromone trails that are not reinforced evaporate over time. Although the images were used to create an environmental setup in which the ants move, the colony's adaptive behavior could be demonstrated on any type of digital habitat.

关键词： adaptive artificial ant colonies adaptive systems ant system algorithm digital images edge detection edge detection edge pixels grayscale images image colour analysis image enhancement multiscale adaptive gain nonlinear contrast enhancement optimisation

来源：评论

学校读者我要写书评

暂无评论

Global optimal path planning for mobile robot based onimproved Dijkstra algorithm and ant system algorithm

引用

Journal of Central South University of Technology 2006年第1期13卷 80-86页

作者：谭冠政贺欢 Aaron Sloman School of Information Science and Engineering Central South University Changsha 410083 China School of Computer Science The University of Birmingham Birmingham B15 2TT UK School of Information Science and Engineering Central South University Changsha 410083 China School of Computer Science The University of Birmingham Birmingham B15 2TT UK

A novel method of global optimal path planning for mobile robot was proposed based on the improved Dijkstra algorithm and ant system algorithm. This method includes three steps: the first step is adopting the MAKLINK graph theory to establish the free space model of the mobile robot, the second step is adopting the improved Dijkstra algorithm to find out a sub-optimal collision-free path, and the third step is using the ant system algorithm to adjust and optimize the location of the sub-optimal path so as to generate the global optimal path for the mobile robot. The computer simulation experiment was carried out and the results show that this method is correct and effective. The comparison of the results confirms that the proposed method is better than the hybrid genetic algorithm in the global optimal path planning.

关键词： mobile robot global optimal path planning improved Dijkstra algorithm ant system algorithm MAKLINK graph free MAKLINK line

来源：评论

学校读者我要写书评

暂无评论

Hybrid adaptive ant system algorithm and its application research

Hybrid adaptive ant system algorithm and its application res...

引用

Asia Simulation Conference/6th International Conference on system Simulation and Scientific Computing

作者： Zhang, HY Yang, R Xian Univ Technol Dept Informat & Control Xian 710048 Peoples R China

ISBN: (纸本)7506278413

In order to solve the problem of pheromone shortage and slow convergent speed of existing ant system algorithm (AS) in its application to complex optimal searching, this paper presents a new hybrid adaptive ant system algorithm with pheromone weight multiplier and pheromone balance operator, which can adaptively adjust select probabilities and pheromone strength. The simulation results -- the global optimum value searching of multi-extremum continuous functions and nonlinear continuous function, solving complex TSP problem and neural network parameter learning with ant system algorithm -- present a good characteristic with lesser probability at local optimization, more strong global optimization capability and some good characteristics on reducing CPU time, and demonstrate the effectiveness of algorithm in improving optimization speed and adding result diversity.

关键词： ant system algorithm hybrid adaptive weight multiplier balance operator neural network

来源：评论

学校读者我要写书评

暂无评论

Hybrid Adaptive ant system algorithm and Its Application Research

Hybrid Adaptive Ant System Algorithm and Its Application Res...

引用

Asian Simulation Conference/The 6th International conference on system Simulation and Scientific Computing

作者： ZHANG Haiying, YANG Rui (Departent of information and Control, Xi'an University of Technology, Xi'an P.R.China 710048 Waterborne Transportation Institute , The Ministry of Communications P.R.China, Beijing 100088)

In order to solve the problem of pheromone shortage and slow convergent speed of existing ant system algorithm (AS) in its application to complex optimal searching, this paper presents a new hybrid adaptive ant system algorithm with pheromone weight multiplier and pheromone balance operator, which can adaptively adjust select probabilities and pheromone strength. The simulation results - the global optimum value searching of multi-extremum continuous functions and nonlinear continuous function , solving complex TSP problem and neural network parameter learning with ant system algorithm -- present a good characteristic with lesser probability at local optimization, more strong global optimization capability and some good characteristics on reducing CPU time, and demonstrate the effectiveness of algorithm in improving optimization speed and adding result diversity.

关键词： ant system algorithm hybrid adaptive weight multiplier balance operator neural network

来源：评论

学校读者我要写书评

暂无评论

Intelligent PID controller based on ant system algorithm and fuzzy inference and its application to bionic artificial leg

引用

Journal of Central South University of Technology 2004年第3期11卷 316-322页

作者：谭冠政曾庆冬李文斌 School of Information Science and Engineering Central South University Changsha 410083 China

A designing method of intelligent proportional-integral-derivative(PID) controllers was proposed based on the ant system algorithm and fuzzy inference. This kind of controller is called Fuzzy-ant system PID controller. It consists of an off-line part and an on-line part. In the off-line part, for a given control system with a PID controller,by taking the overshoot, setting time and steady-state error of the system unit step response as the performance indexes and by using the ant system algorithm, a group of optimal PID parameters K*p , Ti* and T*d can be obtained, which are used as the initial values for the on-line tuning of PID parameters. In the on-line part, based on Kp* , Ti*and Td* and according to the current system error e and its time derivative, a specific program is written, which is used to optimize and adjust the PID parameters on-line through a fuzzy inference mechanism to ensure that the system response has optimal transient and steady-state performance. This kind of intelligent PID controller can be used to control the motor of the intelligent bionic artificial leg designed by the authors. The result of computer simulation experiment shows that the controller has less overshoot and shorter setting time.

关键词： ant system algorithm fuzzy inference PID controller Fuzzy-ant system PID controller intelligent bionic artificial leg

来源：评论

学校读者我要写书评

暂无评论

Design of PID controller with incomplete derivation based on ant system algorithm

引用

控制理论与应用（英文版） 2004年第3期2卷 246-252页

作者： Guanzheng TAN Qingdong ZENG Wenbin LI School of Information Science and Engineering Central South UniversityChangsha Hunan 410083China

A new and intelligent design method for PID controller with incomplete derivation is proposed based on the ant system algorithm ( ASA) . For a given control system with this kind of PID controller, a group of optimal PID controller parameters K p * , T i * , and T d * can be obtained by taking the overshoot, settling time, and steady-state error of the system's unit step response as the performance indexes and by use of our improved ant system algorithm. K p * , T i * , and T d * can be used in real-time control. This kind of controller is called the ASA-PID controller with incomplete derivation. To verify the performance of the ASA-PID controller, three different typical transfer functions were tested, and three existing typical tuning methods of PID controller parameters, including the Ziegler-Nichols method (ZN),the genetic algorithm (GA),and the simulated annealing (SA), were adopted for comparison. The simulation results showed that the ASA-PID controller can be used to control different objects and has better performance compared with the ZN-PID and GA-PID controllers, and comparable performance compared with the SA-PID controller.

关键词： PID controller Incomplete derivation Parameter tuning ant system algorithm Genetic algorithm Simulated annealing

来源：评论

学校读者我要写书评

暂无评论

建议与咨询留下您的常用邮箱和电话号码，以便我们向您反馈解决方案和替代方法

时间限定

文献类型

馆藏选择

核心期刊

语言

文献类型

帮助

文字说明：

检索规则说明：

检索范例：

分类表

所选分类

限定检索结果

文献类型

馆藏范围

日期分布

学科分类号

主题

机构

作者

语言

请选择保存的检索档案：

请选择收藏分类：

通借通还

建议与咨询 留下您的常用邮箱和电话号码，以便我们向您反馈解决方案和替代方法

时间限定

文献类型

馆藏选择

核心期刊

语言

文献类型

帮助

文字说明：

检索规则说明：

检索范例：

分类表

所选分类

限定检索结果

文献类型

馆藏范围

日期分布

学科分类号

主题

机构

作者

语言

请选择保存的检索档案： 新增检索档案 确定 取消

请选择收藏分类： 新增自定义分类 确定 取消

通借通还

建议与咨询留下您的常用邮箱和电话号码，以便我们向您反馈解决方案和替代方法

请选择保存的检索档案：

请选择收藏分类：