%0 Journal Article
%T 基于机器学习方法的无线信道特征的识别与区域划分<br>Identification and Region Division of Wireless Channel Characteristics Based on Machine Learning Method
%A 吴仍康
%J Journal of Antennas
%P 1-7
%@ 2325-2243
%D 2016
%I Hans Publishing
%R 10.12677/JA.2016.51001
%X 本文运用机器学习方法，对无线信道的特征建立了相应的决策树分类模型。并且对所建立的决策树模型运用真实信道数据进行了测试检验，发现分类效果较好。因此，该机器学习模型对无线信道特征的识别具有较高的准确性。进而可以运用该模型对无线信道数据进行有效的区域划分，并且该模型还具备了一定的统计学意义。<br />
In this paper, using the machine learning method establishes the corresponding decision tree classification model for the characteristics of wireless channel. Using the real channel data tests the decision tree model and finds the classification results are better. Therefore, this machine learning method recognition model has high accuracy for wireless channel characteristics. Then we can use the model to divide the wireless channel data into region effectively, and the model also has statistical significance.
%K 机器学习，无线信道，决策树模型，区域划分<br>Machine Learning
%K Wireless Channel
%K Decision Tree Model
%K Region Division
%U http://www.hanspub.org/journal/PaperInformation.aspx?PaperID=18126