Maximum Sampling Sequence Design in Teaching Management Application Based on Genetic Algorithm

Abstract:

The spatial design of experiment and information subset had been studied by correlated random sequence sampling. The problems in many applied region had been found, such as statistical geology, sampling sequence, and environmental statistics. In all applications, maximum sampling sequence can be selected and different location and times. In maximum sampling sequence design, the feasible design program would be taken when the design domain and time are discrete from the design goal and expected result. The main problem is how to solve the maximum sampling sequence design idea. This is the algorithm GA sequence theory problem. In order to apply the GA design in computer experiments, in many cases, the design space is not possible to calculate accurately. In order to improve the efficient experiment of sampling sequence, the GA algorithm is developed to take advantage of business power of sequence algorithm. The results show that design idea and construction are very efficient for solving the mistake.

• Periodical: Applied Mechanics and Materials (Volumes 321-324)
• Pages: 2089-2092
• DOI: https://doi.org/10.4028/www.scientific.net/AMM.321-324.2089
• Online since: June 2013
• Authors: Xiao Xu Zhu
• Keywords: Design, Genetic Algorithm (GA), Maximum Sampling, Teaching Management

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