This paper proposes an algorithm for data mining named Pheromone-Miner (ant-colony-based data miner). The algorithm is inspired by both researches on the behavior of real ant colonies and data mining concepts as well ...
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ISBN:
(纸本)9781424427932
This paper proposes an algorithm for data mining named Pheromone-Miner (ant-colony-based data miner). The algorithm is inspired by both researches on the behavior of real ant colonies and data mining concepts as well as principles. The goal of Pheromone-Miner is to extract more exact knowledge from a database. Pheromone-based mining breaks through limitations of other mining approaches. We compare the performance of pheromone-miner with a general semantic miner. The accident causes discovered by ant-miner are considerably more accurate than those discovered by a general semantic miner. In a word, this evolutionary algorithm is suitable for improving the accuracy of data miners.
Ship detection is an important section of Synthetic Aperture Radar's marine applications. Through analyzing the distribution characteristics of ship targets and speckle, a novel ship detection method based on NSCT...
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ISBN:
(纸本)9781424441303
Ship detection is an important section of Synthetic Aperture Radar's marine applications. Through analyzing the distribution characteristics of ship targets and speckle, a novel ship detection method based on NSCT and ACO is proposed for SAR image processing. First, apply NSCT adaptive threshold method to de-noise the SAR images, then detect the edges by ACO, last ship targets can be precisely detected. Simulating results indicate that this method can not only pick-up contour information of ship objects in complex speckle efficiently, but also keep ships structure well, show ideal anti-jamming competence, guarantee the detection accuracy.
Urban off-road park facilities layout planning is an important component of the parking system planning and an integrated system engineering issue with multi-index and multi-constraint. This paper includes the study o...
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ISBN:
(纸本)9780769538761
Urban off-road park facilities layout planning is an important component of the parking system planning and an integrated system engineering issue with multi-index and multi-constraint. This paper includes the study of the organizational mechanisms of parking facilities layout form and analysis of all factors that impact the public parking facilities layout. In this paper, the author established the simplified model of multi-objective optimization of the parking facilities site considering the highest social benefit of their layout. The Intelligent ant colony optimization algorithm is introduced to solve the model.
The ant colony optimization algorithm (ACOA) is a new class of stochastic search algorithm proposed for the solution of combinatorial optimisation problems. Different versions of ACOA are developed and used with varyi...
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The ant colony optimization algorithm (ACOA) is a new class of stochastic search algorithm proposed for the solution of combinatorial optimisation problems. Different versions of ACOA are developed and used with varying degrees of success. The Max-Min ant System (MMAS) is recently proposed as a remedy for the premature convergence problem often encountered with ACOAs using elitist strategies. The basic concept behind MMAS is to provide a logical balance between exploitation and exploration. The method, however, introduces some additional parameters to the original algorithm, which should be tuned for the best performance of the method adding to the computational requirement of the algorithm. An alternative method to MMAS is proposed in this paper and applied to pipe network optimization problem. The method uses a simple but effective mechanism, namely Pheromone Trail Replacement (PTR), to make sure that the global best solution path has always the maximum trail intensity. This mechanism introduces enough exploitation into the method and more importantly enables one to exactly predict the number of global best solutions at each iteration of the algorithm without requiring calculation of the cost of the solutions created. The sub-colony of repeated global best solutions of the iterations is then mutated, such that a predefined number of solutions survive the mutation process. Two different mutation mechanisms, namely deterministic and stochastic mutation processes, are introduced and used. The first one uses a one bit mutation with a probability of one on some members of the sub-colony, while the second one uses a uniform mutation on the whole sub-colony. The probability of mutation in the second mutation process is adjusted at each iteration, so that the required number of global-best solutions survives the mutation. The method is shown to produce results comparable to the MMAS algorithm, while requiring less free parameter tuning. The application of the method to a
In this paper, a novel ant colony optimization algorithm with random perturbation behavior (RPACO) based on combination of general antcolonyoptimization and stochastic mechanism is developed for the solution of opti...
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In this paper, a novel ant colony optimization algorithm with random perturbation behavior (RPACO) based on combination of general antcolonyoptimization and stochastic mechanism is developed for the solution of optimal unit commitment (UC) with probabilistic spinning reserve determination. In general, the purpose of UC is to enhance the economical efficiency as could as possible while simultaneously satisfying physical and operation constraints of individual unit. Consider the possibility of generating unit failure, the requirement, the sufficient spinning reserve capacity to ensure adequate reliability levels, must be satisfied by the commitment schedule. The security function approach is applied to evaluate the desired level of system security, and the proposed method in this paper, RPACO, is adopted to solve the UC problems. The effectiveness of the proposed method has been demonstrated on the corresponding numerical results. Further, the sensitivity of the desired security level to the optima during optimization is investigated in this paper. (C) 2003 Elsevier B.V. All rights reserved.
Application of an ant colony optimization algorithm (ACOA) for simultaneous layout and size optimization of tree-like pipe networks is described in this paper using two different formulations. In the first formulation...
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Application of an ant colony optimization algorithm (ACOA) for simultaneous layout and size optimization of tree-like pipe networks is described in this paper using two different formulations. In the first formulation, each link of the base graph is considered as the decision point of the problem. Each decision point is considered in turn and the ants are then required to choose any of the available options at the current decision point. The list of available pipe diameters with the null option included for each link constitutes the available options in this formulation. In the second approach, the network nodes are considered as the decision points of the problem. The available options in this formulation are represented by the list of allowable pipe diameters for all plausible links such that the resulting network is a tree network. The plausible links at each decision point are provided by a tree-growing algorithm. This formulation leads to a very small search space compared with the first algorithm, as each ant is now forced to create a feasible solution regarding the layout geometry of the network. This approach fully exploits the sequential nature of the ACOA in building solutions, which is believed to be one of the main advantages of these algorithms compared with other general metaheuristics. The proposed methods are applied to find the optimal layout of two benchmark examples in the published literature and the results are presented and compared with the existing results.
In order to improve the speed of convergence of antcolonyoptimization, a parallel algorithm based on coarse-grained model is proposed in the paper, search tasks are assigned to q ant subgroups, and parallel searchin...
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In order to improve the speed of convergence of antcolonyoptimization, a parallel algorithm based on coarse-grained model is proposed in the paper, search tasks are assigned to q ant subgroups, and parallel searching are finished by q subgroups. Results of experiment show that the algorithm described in this paper makes the searching speed hundreds of times faster than the latest improved algorithm.
It is shown that partner selection in agile supply chain network can be represented as a directed graph model. This paper considers multi-stages in this process instead of one. The natures of the proposed model enable...
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ISBN:
(纸本)9781424441983
It is shown that partner selection in agile supply chain network can be represented as a directed graph model. This paper considers multi-stages in this process instead of one. The natures of the proposed model enable us to design a meta-heuristic algorithm -- GACA which combined the pros part of ACOA and GA for solving the good path search problem. Computational results show the efficiency of our algorithm in compare to the other techniques.
It is shown that partner selection in agile supply chain network can be represented as a directed graph model. This paper considers multi-stages in this process instead of one. The natures of the proposed model enable...
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It is shown that partner selection in agile supply chain network can be represented as a directed graph model. This paper considers multi-stages in this process instead of one. The natures of the proposed model enable us to design a meta-heuristic algorithm - GACA which combined the pros part of ACOA and GA for solving the good path search problem. Computational results show the efficiency of our algorithm in compare to the other techniques.
ant colony optimization algorithm is a heuristic ap- proach for the solution of combinatorial optimization *** order to solve continuous optimization models,a new ant colony optimization algorithm is de- *** Benchmark...
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ant colony optimization algorithm is a heuristic ap- proach for the solution of combinatorial optimization *** order to solve continuous optimization models,a new ant colony optimization algorithm is de- *** Benchmark problems are employed to il- lustrate the effectiveness of the algorithm.
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