摘要
大数据时代背景下,发掘生产现场的历史数据中有用的信息和知识,利用智能算法来模型辨识多变量系统,已经成为了主流的研究方向。论文经过多个实验探究分析历史大数据和智能算法相融合的多变量系统辨识中具有的问题,并且把输入变量对输出的影响进行了量化,同时把这种方案使用在热力发电厂的多变量协调控制系统的相关建模实验里,相应的辨识结果证明了这个方案的实效性。
In the era of large data, it is a mainstream research direction to discover useful information and knowledge in historical data, and to use intelligent algorithm to model multivariable system. In this paper, several experiments are carried out to analyze the problems of multivariable system identification with the integration of historical data and intelligent algorithms, and the influence of input variables on output is quantified, and this scheme is used in the multivariable Coordinated controt system in the relevant modeling experiments, the corresponding identification results prove the effectiveness of this program.
出处
《网络空间安全》
2016年第11期44-46,58,共4页
Cyberspace Security
关键词
大数据
双量子粒子
多变量系统
large data
double quantum particle
multivariable system
