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Titlebook: Knowledge Science, Engineering and Management; 11th International C Weiru Liu,Fausto Giunchiglia,Bo Yang Conference proceedings 2018 Spring

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樓主: ARSON
51#
發(fā)表于 2025-3-30 09:25:43 | 只看該作者
52#
發(fā)表于 2025-3-30 16:04:01 | 只看該作者
53#
發(fā)表于 2025-3-30 18:56:40 | 只看該作者
A Multi-objective Optimization Algorithm Based on Preference Three-Way Decompositionated set of the three sub-problems, a set of external preservation sets are formed so as to get the optimal set that the DM is interested in. Experimental results show that the proposed method can reduce the workload of the DM and obtain more accurately converge to the optimal frontiers of the optimization problems.
54#
發(fā)表于 2025-3-30 21:55:02 | 只看該作者
A Community-Division Based Algorithm for Finding Relations Among Linear Constraintslations among constraints in the same community through search. Experimental results show that the algorithm can effectively process large set of constraints, reduce time cost and find relations with higher quality.
55#
發(fā)表于 2025-3-31 03:52:57 | 只看該作者
A Parthenogenetic Algorithm for Deploying the Roadside Units in Vehicle NetworksPGA is proposed to solve the deployment problem. Compared with algorithms Delta-r and Delta-GA, in many .-Deployments, the Delta-uc and UCPGA algorithms respectively required fewer RSUs, which were proved by the experiments on the realistic mobility trace of Cologne, Germany.
56#
發(fā)表于 2025-3-31 05:39:27 | 只看該作者
57#
發(fā)表于 2025-3-31 09:52:55 | 只看該作者
ROSIE: Runtime Optimization of SPARQL Queries over RDF Using Incremental Evaluationn, as well as a mechanism to detect cardinality estimation error at runtime, ROSIE relieves the problem of biased cardinality propagation in an efficient way. Extensive experiments on real and benchmark data have shown that, compared to the state-of-the-arts, ROSIE consistently outperformed on complex queries by orders of magnitude.
58#
發(fā)表于 2025-3-31 14:41:32 | 只看該作者
59#
發(fā)表于 2025-3-31 18:26:04 | 只看該作者
60#
發(fā)表于 2025-3-31 23:43:26 | 只看該作者
The New Adaptive ETLBO Algorithms with K-Armed Bandit Model-KAB algorithm is effective and brings dramatic improvement compared with TLBO and ETLBO. Furthermore, a new perturbation strategy—discussion group strategy is proposed. And the experimental results indicate that the efficiency of AETLBO-KAB with discussion group algorithm exceeds AETLBO-KAB algorithm.
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