Titlebook: Computational Intelligence and Intelligent Systems; 4th International Sy Zhihua Cai,Zhenhua Li,Yong Liu Conference proceedings 2009 Springe

上流社会

Registrierte Seniorenkriminalität, yields better structures in fewer iterations than initializing with random structures. Hence, the proposed two-stage optimization outperforms a local search procedure based on simulated annealing alone.

ACRID

Omnidirectional Motion Control for the Humanoid Soccer Robota Nao model. This has greatly increased the complexity and difficulty of motion controller for Nao. Based on the analysis of Nao’s structure, our team G-Star has worked out the quantitative relation of joint angle in motion control and developed a toolkit to calculate the angle of joints accurately.

蛤肉

Routing Algorithm Based on Gnutella Modelto result in the network congestion and instability. In order to solve this problem, this paper improved the current routing algorithm based on the Ant algorithm. For achieving the optimal routing, the algorithm amended the routing gradually. In the routing search, it also avoided the randomization

鼓掌

Sliding-Window Recursive PLS Based Soft Sensing Model and Its Application to the Quality Control of h complex nonlinearity and time-variance, an adaptive soft sensing model based on sliding-widow recursive PLS (RPLS) is presented to build a prediction model for the Mooney-viscosity of rubber mixture. The improved RPLS model can adaptively adjust the structures and parameters of PLS model according

scrape

The Research of Method Based on Complex Multi-task Parallel Scheduling Problemhot research spots for domestic and foreign experts or scholars. This paper mainly proposes an optimization method of network planning project by using an improved genetic algorithm for solving complex parallel multi-task scheduling problems. It used a method that gradually increases the number of p

珊瑚

fatty-acids

A Cluster-Based Orthogonal Multi-Objective Genetic Algorithmnce the convergence and diversity of a multi-objective genetic algorithm. This paper introduces a new algorithm, with both good convergence and diversity based on clustering method and multi-parent crossover operator. Meanwhile, an initial population is generated by orthogonal design to enhance the

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Living-Will

An Multi-objective Evolutionary Algorithm with Lower-Dimensional Crossover and Dense Controlhm that can have a good control of both. The algorithm not only adopts the Lowerdimensional Crossover algorithm to accelerate the convergence but also proposes two good methods to keep the wide population distribution for global search. Also a new method is put forward as an algorithm of repulsing m