Notice of Retraction: A customer identification method based on genetic algorithm and customer value model: Theoretical model and empirical application

2010 ◽  
Author(s):  
Yinghong Wan ◽  
Cao Xiaopeng ◽  
Jiang Liquan
Keyword(s):  
Genetic Algorithm ◽  
Theoretical Model ◽  
Customer Value ◽  
Empirical Application ◽  
Identification Method ◽  
Customer Identification ◽  
Value Model

Design of Docking Probe Based on Dynamics Model of Flexible Beam Impact

2011 ◽  
Vol 120 ◽  
pp. 371-374
Author(s):  
Xiang Zhang ◽  
Yi Yong Huang ◽  
Wei Han ◽  
Xiao Qian Chen
Keyword(s):  
Genetic Algorithm ◽  
Theoretical Model ◽  
Impact Dynamics ◽  
Flexible Beam ◽  
Analytical Mechanics ◽  
Space Probe ◽  
Dynamics Model ◽  
Docking Mechanism

The issue considered in this paper is a flexible beam based on space probe-cone docking mechanism, which aims to buffer impact effects replacing buffering mechanism. The theoretical model of docking impact dynamics based on flexible beam is built according to the Lagrange Analytical Mechanics theory. The shape of docking probe is optimized by using genetic algorithm.

The DNA Genetic Algorithm Applied for Solving Optimal Placement of Sensors

2012 ◽  
Vol 160 ◽  
pp. 103-108
Author(s):  
Xin Liu ◽  
Zhong Ren Feng ◽  
Xiong Jian Wang ◽  
Bao Fu Wang
Keyword(s):  
Genetic Algorithm ◽  
Integer Programming ◽  
Expected Value ◽  
Optimal Placement ◽  
Stochastic Integer Programming ◽  
Objective Functions ◽  
Stochastic Variable ◽  
Expected Value Model ◽  
Complex Knowledge ◽  
Value Model

In order to solve optimal placement of bridge sensors based on the modal information, a multi-objective integer programming expected value model is established and the number of modal is considered as a stochastic variable in this paper, and here Fisher and MAC matrix are combined as the objective functions . Since DNA Genetic algorithm has the merits of plentiful coding, and decoding, conveying complex knowledge flexibly, these merits and the technique of stochastic simulation are also combined, which for estimating stochastic integer programming expected value models problem. And finally the feasibility of the algorithm is showed by XuGe Bridge as an example.

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