The Application of Adaptive Genetic Reduction Algorithm in Radar Faults Diagnosis
An improved adaptive genetic reduction algorithm based on knowledge dependability is presented in this paper when rough set theory and genetic algorithm are researched. There are four characters of the algorithm, which the initial population of binary code is restricted by attribute core of decision table, the fitness function in the algorithm is define through the dependability that decision attribute for condition attribute, the adaptive crossover probability and adaptive mutation probability are improved, and the new generation individuals are added correction operator. Using the algorithm radar faults is diagnosed and the simple rules can be obtained automatically. The diagnosis rules have the characteristic that fault premonitions and fault reasons parallelism can be correlated one by one. The defects of worse system veracity and lower efficiency can be avoided about expert fault diagnosis based on traditional fault tree.
adaptive genetic algorithm rough set radar faults diagnosis knowledge dependability reduction
Pan Wei Xu Jiahe Li Lei
Electric Detection Department, Shenyang Artillery Academy, Shenyang 110867, China Department of Research Institute of Wood Industry Chinese Academy of Forestry, Beijing 100091, China
国际会议
2011 China Control and Decision Conference(2011中国控制与决策会议 CCDC)
四川绵阳
英文
1703-1707
2011-05-23（万方平台首次上网日期，不代表论文的发表时间）