CAJ | 학술논문

提出一种面向决策树目标路径编码的相空间嵌入维计算优化算法。构建云平台环境下的数据交互节点拓扑模型，通过部分链路失效多路径加密方法使得数据聚集具有很高的容错功能，然后采用决策树目标路径编码方案，在给定带宽约束和量化阈值的情况下，对决策树目标路径编码的相空间嵌入维数据进行自适应的量化分解，以实现对决策树目标路径编码的相空间嵌入维的准确估计，降低误码率。仿真结果表明，该算法能准确估计相空间嵌入维，提高估计精度，能有效降低误码率，提高数据动态交互通信的准确性，信号保真度较高。展示了其优越性和较好的应用价值。
제출일충면향결책수목표로경편마적상공간감입유계산우화산법。구건운평태배경하적수거교호절점탁복모형，통과부분련로실효다로경가밀방법사득수거취집구유흔고적용착공능，연후채용결책수목표로경편마방안，재급정대관약속화양화역치적정황하，대결책수목표로경편마적상공간감입유수거진행자괄응적양화분해，이실현대결책수목표로경편마적상공간감입유적준학고계，강저오마솔。방진결과표명，해산법능준학고계상공간감입유，제고고계정도，능유효강저오마솔，제고수거동태교호통신적준학성，신호보진도교고。전시료기우월성화교호적응용개치。
This paper presents an decision tree target path coding phase space embedding dimension calculation optimiza?tion algorithm. The construction of data interaction topology model of cloud platform environment, through encryption meth?ods part link failure multi path allows data aggregation has the functions of fault tolerance is high, then the decision tree tar?get path coding scheme in a given bandwidth constraints and quantization threshold, decomposition of quantization on deci?sion tree target path coding phase space embedding dimension data adaptive, accurate estimation of the decision tree to achieve the target path coding phase space embedding dimension, reducing the error rate. Simulation results show that the algorithm can accurately estimate the phase space embedding dimension, improve the estimation accuracy, can effectively reduce the error rate, improve the accuracy of dynamic interactive data communication, signal has a higher fidelity. It has demonstrated its superiority and good application value.