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The paper proposed an online analysis for motion captured motion data. Traditional manifold-based motion analysis can only perform in offline mode, which limits the applications and developments of the data-driven computer animation. By reserving the eigenspace and reconstructing the space using only the new instance, online motion analysis can be achieved. Numerical new training instances can be...
To solve a typical NP-hard combinatorial optimization problem-traveling salesman problem, ant colony optimization based on minimum spanning tree(MST-ACO), is presented and the performance is reported. The mechanism of MST-ACO is described from three aspects: adopting dual nearest insertion procedure to initialize the pheromone, integrating reinforcement learning through computing lowbound by 1-minimum...
The traveling salesman problem (TSP) in operations research is a classical problem in discrete or combinatorial optimization. It is a prominent illustration of a class of problems in computational complexity theory which are classified as NP-hard. Ant colony optimization inspired by co-operative food retrieval have been widely applied unexpectedly successful in the combinatorial optimization. This...
In this paper, a grid computational model and algorithm based on mind evolutional computation is constructed and implemented, which supports the dynamically resource allocation under grid environment. We investigate the grid enabled parallel computational model performance metrics, and proposed the Mind Evolutionary Computation based space decomposition parallel evolutionary algorithm , which simulates...
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