CAJ | 학술논문

对Web故障监测异常数据的自适应重写可以实现对Web数据库的极值扰动盲分离，提高Web故障监测数据库的访问能力，进而提高对Web网络故障的诊断性能。提出基于极值扰动的Web异常数据自适应重写算法，引入自适应经验函数，优化粒子群进化搜索能力。选择一定的基函数与故障监测信号进行匹配，为了使粒子群摆脱局部极值，增加了极值扰动算子，进行经验约束函数调控，提高对Web网络故障的诊断性能。仿真实验表明，该算法能有效实现对Web网络故障数据的自适应重写，信号恢复和跟踪效果较好，提高了对Web数据库的访问精度，在Web网络数据库故障检测和数据调度访问等领域具有较好的应用价值。
대Web고장감측이상수거적자괄응중사가이실현대Web수거고적겁치우동맹분리，제고Web고장감측수거고적방문능력，진이제고대Web망락고장적진단성능。제출기우겁치우동적Web이상수거자괄응중사산법，인입자괄응경험함수，우화입자군진화수색능력。선택일정적기함수여고장감측신호진행필배，위료사입자군파탈국부겁치，증가료겁치우동산자，진행경험약속함수조공，제고대Web망락고장적진단성능。방진실험표명，해산법능유효실현대Web망락고장수거적자괄응중사，신호회복화근종효과교호，제고료대Web수거고적방문정도，재Web망락수거고고장검측화수거조도방문등영역구유교호적응용개치。
Adaptive rewriting algorithm of Web fault monitoring data can realize extremum disturbed blind separation, and improve the ability of Web fault monitoring database, and then improve the performance of Web network fault diagnosis. The Web abnormal data rewriting algorithm is proposed based on adaptive extreme disturbance, the adaptive function is de?fined, and the particle swarm optimization evolutionary search ability is obtained. Certain basis function is selected for matching the fault monitoring signals, in order to make the particle swarm to escape from local minimum, maximum pertur?bation operator is enhanced. The experience constraint function regulation is proposed to improve the performance of Web network fault diagnosis. Simulation results show that, the algorithm can effectively realize adaptive rewriting of the failure data of Web network, signal recovery and tracking effect is good, the Web database access accuracy is improved, so it has good application value in network fault detection and data scheduling access, etc.