Semantic-based image retrieval bridges the gap between visual features and human understanding of image in the field of image retrieval. Image annotation is one important technology of image retrieval based on the sem...
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Based on the property of Human vision system (HVS) that human eye's sensitivity to an image varies with different information regions of the image, Pulse-coupled neural network (PCNN) model is modified for image s...
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Based on the property of Human vision system (HVS) that human eye's sensitivity to an image varies with different information regions of the image, Pulse-coupled neural network (PCNN) model is modified for image segmentation. The modified PCNN stimulated by an input image has pulse output with multiple pulse values rather than only two in the conventional PCNN, according to the local information rate of the input image. This results in image segmentation according to local information rate delivered from the image by the modified PCNN. Experiments with the modified PCNN on image segmentation and image compression on the segmented images with the principle that the lower information rate is, the higher compression rate is applied, show much better performance in compression rate compared with that on the segmented images with the conventional PCNN.
Ant colony optimization (ACO for short) has been proved a successful meta-heuristic by a huge of empirical studies. This paper discusses the termination criteria of ACO and therefore provides research ideas to other m...
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Ant colony optimization (ACO for short) has been proved a successful meta-heuristic by a huge of empirical studies. This paper discusses the termination criteria of ACO and therefore provides research ideas to other meta-heuristics. A general discussion about four types of termination criteria has been firstly discussed in this article. Then some measures of convergence based on pheromone have been introduced. And a new termination criterion based on Bayesian approach is presented. Finally a new convergence proof for a class of ACO algorithms is presented.
The traveling salesman problem (TSP) is among the most important combinatorial problems. Ant colony optimization (ACO) algorithm is a recently developed algorithm which has been successfully applied to several NP-hard...
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The traveling salesman problem (TSP) is among the most important combinatorial problems. Ant colony optimization (ACO) algorithm is a recently developed algorithm which has been successfully applied to several NP-hard problems, such as traveling salesman problem, quadratic assignment problem and job-shop problem. Association rule (AR) is the key in knowledge in data mining for finding the best data sequence. A new algorithm which integrates ACO and AR is proposed to solve TSP problems. Compare with the simulated annealing algorithm, the standard genetic algorithm and the standard ant colony algorithm, the new algorithm is better than ACO.
Structure alignment could help to find shape similarities between proteins and guide structure classification and fold recognition. Common substructure detection and extraction are especially important, for which coul...
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ISBN:
(纸本)9781424415786
Structure alignment could help to find shape similarities between proteins and guide structure classification and fold recognition. Common substructure detection and extraction are especially important, for which could guide the biologist to discover binding site or active site. We represent each segment of alpha-carbon backbone by using dihedral angles and curve moment invariants. Then, local and global structure alignment could be performed by iterative closest point algorithm. Maximum common substructures between a pair of proteins or within a protein could be found. Active sites also could be detected by the proposed algorithm.
By use of the properties of ant colony algorithm and genetic algorithm, a hybrid algorithm is proposed to solve the traveling salesman problems. First, it adopts genetic algorithm to give information pheromone to dist...
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ISBN:
(纸本)7900719229
By use of the properties of ant colony algorithm and genetic algorithm, a hybrid algorithm is proposed to solve the traveling salesman problems. First, it adopts genetic algorithm to give information pheromone to distribute. Second, it makes use of the ant colony algorithm to get several solutions through information pheromone accumulation and renewal. Finally, by using across and mutation operation of genetic algorithm, the effective solutions are obtained. Compare with the simulated annealing algorithm, the standard genetic algorithm, the standard ant colony algorithm, and statistics initial ant colony algorithm, all the 16 hybrid algorithms are proved effective. Especially the hybrid algorithm with across strategy B and mutation strategy B is a simple and effective better algorithm than others.
Superimpose one protein tertiary structure to another can help to find similarity between them and further identify functional and evolutionary relationships. We first extract invariant features under rigid body trans...
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Due to the existence of a large amount of legacy information systems, how to obtain the information and integrate the legacy systems is becoming more and more concerned. This paper introduces the integration pattern b...
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Currently, there are many researches focusing on grid scheduling and more and more scheduling algorithms were proposed. However, those algorithms are not satisfied with the requirement of the grid for ignoring its cha...
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ISBN:
(纸本)9781595937575
Currently, there are many researches focusing on grid scheduling and more and more scheduling algorithms were proposed. However, those algorithms are not satisfied with the requirement of the grid for ignoring its characteristics of dynamics, autonomy, distributing, etc. Therefore, this paper proposes an adaptable dynamic job scheduling approach based on historical information (ADJSA). This approach adjusts the predicting model automatically by using the recent jobs execution historical information and then selects the appropriate resource to execute the job considering dynamic and real-time factors of the Grid.
An optimization mathematical model of clustering problem is given in this paper. The new hybrid particle swarm optimization (PSO) algorithms are put forward to solve clustering problem. The basic particle swarm optimi...
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An optimization mathematical model of clustering problem is given in this paper. The new hybrid particle swarm optimization (PSO) algorithms are put forward to solve clustering problem. The basic particle swarm optimization algorithm is then extended to use K-means clustering to seed the initial swarm and the particle is position is adjusted according to the new cluster center vectors. The algorithms are evaluated on Iris plants database. Results show that all the 3 hybrid particle swarm optimization algorithms are proved effective and especially the third modified particle swarm optimization algorithm is proved more effective. It also shows that the PSO clustering techniques have much potential.
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