Results 211 to 220 of about 61,825 (273)
Application of optimal power point tracking technology in distributed grid-connected photovoltaic systems. [PDF]
PLoS OneYang P, Weng H, Zhong Y.
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2020
Ant colony optimization (ACO) algorithm, models the real-life behavior of ants to solve optimization problems. Information provided in this chapter include: path navigation of ants, foraging pattern of ants by depositing pheromones during exploration and ACO model development.
Modestus O. Okwu, Lagouge K. Tartibu
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Ant colony optimization (ACO) algorithm, models the real-life behavior of ants to solve optimization problems. Information provided in this chapter include: path navigation of ants, foraging pattern of ants by depositing pheromones during exploration and ACO model development.
Modestus O. Okwu, Lagouge K. Tartibu
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Parallel Ant Colony Optimization Algorithm
2006 6th World Congress on Intelligent Control and Automation, 2006Ant colony optimization algorithm is a good way to solve complex multi-stage decision problems. But the construction graph and computation steps for an ant to construct a solution in the construction graph will be exponentially increased, if the stage number and decision variable dimension of complex multi-stage decision problem are increasing. It will
null Hong Liu, null Ping Li, null Yu Wen
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An Ant Colony Verification Algorithm
Seventh International Conference on Intelligent Systems Design and Applications (ISDA 2007), 2007Buchi automata are widely used as a modeling formalism in formal verification. The emptiness check procedure is used to carry on the model checking of a model M. of a system, against an LTL formula Phi, that expresses the desidered properties the system should satisfy.
R.achid Rebiha, Giovanni L. Ciampaglia
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Intelligent Learning Ant Colony Algorithm
Applied Mechanics and Materials, 2011Ant colony algorithm is effective algorithm for NP-hard problems, but it also tends to mature early as other evolutionary algorithms. One improvement method of ant colony algorithm is studied in this paper. Intelligent learning ant colony algorithm with the pheromone difference and positive-negative learning mechanism is brought forward to solve TSP ...
Jian Hua Ma, Fa Zhong Tian
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Adaptive ant colony optimization algorithm
2014 International Conference on Mechatronics and Control (ICMC), 2014An adaptive ant colony algorithm is proposed to overcome the premature convergence problem in the conventional ant colony algorithm. The adaptive ant colony is composed of three groups of ants: ordinary ants, abnormal ants and random ants. Each ordinary ant searches the path with the high concentration pheromone at the high probability, each abnormal ...
Gu Ping +4 more
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Application of Ant Colony Algorithm
Applied Mechanics and Materials, 2014This paper mainly considers the application of the ant colony in our life. The principle of ant colony optimization, improves the performance of ant colony algorithm, and the global searching ability of the algorithm. We introduce a new adaptive factor in order to avoid falling into local optimal solution.
Rui Wang, Zai Tang Wang
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Continuous Ant Colony Algorithm
Advanced Materials Research, 2011Ant Colony Algorithm is a new bionics optimization algorithm from mimic the swarm intelligence of ant colony behavior. And it is a very good combination optimization method. To extend the ant colony algorithm, and to improve the searching performance, from the connections of continuous optimization and searching process of ant colony algorithm, one new
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An Improved Ant Colony Algorithm
2008 International Conference on MultiMedia and Information Technology, 2008Artificial ant colony algorithm is new in the evolution computing. The primary study shows it is a better algorithm with robust based population, but it has some shortcomings such as its slow computing speed, and it is easy to fall in local peak in large scale problem. To overcome these deficiencies, an improved ant colony algorithm is designed through
Xin Zhang, Yu-zhong Zhou, Ping Fang
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MC-ANT: A Multi-Colony Ant Algorithm
2010In this paper we propose an ant colony optimization variant where several independent colonies try to simultaneously solve the same problem. The approach includes a migration mechanism that ensures the exchange of information between colonies and a mutation operator that aims to adjust the parameter settings during the optimization.
Leonor Melo +2 more
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