For the optimization problem about triangulation of Bayesian networks, a novel genetic algorithm, DHGA, is proposed in this paper. DHGA employs a heuristic-based mutation operation. Moreover, it uses population divers...
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(纸本)9788988678251
For the optimization problem about triangulation of Bayesian networks, a novel genetic algorithm, DHGA, is proposed in this paper. DHGA employs a heuristic-based mutation operation. Moreover, it uses population diversity to identify stagnation and convergence as well as to guide the search procedure. Experiments on representative benchmarks show that DHGA posses better performance and robustness than other swarm intelligence methods.
Classical genetic algorithm suffers heavy pressure of fitness evaluation for time-consuming optimization problems, e.g., aerodynamic design optimization, qualitative model learning in bioinformatics. To address this p...
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A large number of techniques have been implemented mostly based on abundance of data statistics and they usually do not harness the semantic relationships between attributes. This paper proposes a novel ontology-based...
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Automatic image segmentation remains a challenging problem in the fields of computer vision, image analysis and understanding. A lot of algorithms and technologies have been proposed and developed for image segmentati...
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Classification and prediction of different cancers based on gene expression profiles are important for cancer diagnosis, cancer treatment and medication discovery. The k nearest neighbor algorithm (k-NN) is one easy a...
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To find an optimal elimination ordering for Bayesian networks, a multi-heuristic-based ant colony system named MHC-HS-ACS is proposed. MHC-HS-ACS uses a set of heuristics to guide the ants to search solutions. The heu...
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Most of the existing methods for community discovery only deal with social network with a fixed structure, so they can not effectively deal with dynamic social network. This paper proposes a Multi-agent system method ...
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Chip Multi-Processor (CMP) could support more than two threads to execute simultaneously, and some executing units are owned by each core. Because threads share various resources of CMP, such as L2-Cache, among many t...
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Chip Multi-Processor (CMP) could support more than two threads to execute simultaneously, and some executing units are owned by each core. Because threads share various resources of CMP, such as L2-Cache, among many threads, CMP system is inherently different from multiprocessors system and, CMP is also different from simultaneously multithreading (SMT). In this paper a novel and complete approach on how to parallelism for relational database multithreaded query execution that strives for maximum resource utilization for both CPU and disk activities. The focus of this approach is on how to use the multithreaded parallel technique to optimize and process queries based on multi-core architecture. A set of algorithms for implementing and optimizing the best query plan, such as the algorithms for scheduling and parallel executing the query plan, the algorithms for allocating thread to sub-query and memory to the buffers between operations in pipelining execution, are proposed in this method. Additionally this paper analysis and optimize the implementation of parallel buffers and multithread. In the experiments, this paper evaluates performance of the parallel buffers and tests the coordination of the multithread.
In this paper, a hybrid algorithm named DPSO-SA is proposed to find near-to-optimal elimination orderings in Bayesian networks. DPSO-SA is a discrete particle swarm optimization method enhanced by simulated annealing....
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According to the characteristics of the optimal elimination ordering problem in Bayesian networks, a heuristic-based genetic algorithm, a cooperative coevolutionary genetic framework and five grouping schemes are prop...
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