供热负荷时间序列混沌特性识别及区间预报研究
Identification of chaos in heating load time series and interval prediction
摘要：
对供热负荷时间序列进行了混沌特性分析，计算得到了吸引子维数和最大Lyapunov指数。在最大Lyapunov指数点预报法的基础上，提出了最大Lyapunov指数区间预报法，并给出了最大预报时间尺度。仿真结果表明，该方法可取得较高的预报精度和较高可靠度的预报区间。
关键词：供热负荷,时间序列,混沌,区间预报,相空间重构,最大Lyapunov指数
Abstract：
Analyses the chaotic properties of heating load time series, and obtains the correlation dimension of attractor and the largest Lyapunov exponent. Based on the largest Lyapunov exponent point prediction algorithm, presents a novel algorithm—largest Lyapunov exponent interval prediction algorithm, and provides the largest predicting time scale. Simulation results show that this method is with higher accuracy and more reliable prediction interval.
Keywords:heatingload,timeseries,chaos,intervalprediction,phasespacereconstruction,largestLyapunovexponent