Title :
Optimal management of educational resources design based on genetic algorithm
Author_Institution :
Coll. of Adult & Continuing Educ., Beihua Univ., Jilin, China
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 Robustness power of sequence algorithm. The test results show that design idea and construction are very efficient for solving the mistake.
Keywords :
continuing education; genetic algorithms; resource allocation; sampling methods; GA sequence theory; adult education; continuing education; correlated random sequence sampling; educational resource design; genetic algorithm; information subset; maximum sampling sequence; optimal management; robustness power; Algorithm design and analysis; Biological system modeling; Computational modeling; Computers; Genetic algorithms; Nickel; Safety; GA; computer exeriments; maximum sampling; spatial design;
Conference_Titel :
IT in Medicine and Education (ITME), 2011 International Symposium on
Conference_Location :
Cuangzhou
Print_ISBN :
978-1-61284-701-6
DOI :
10.1109/ITiME.2011.6132156