Prediction of Output Response Probability of Sound Environment System Using Simplified Model with Stochastic Regression and Fuzzy Inference
Prediction of Output Response Probability of Sound Environment System Using Simplified Model with Stochastic Regression and Fuzzy Inference
复制标题
利用随机回归和模糊推理简化模型预测声环境系统输出响应概率
DOI：
10.1007/s12543-013-0142-4
复制
发表时间：
2013
影响因子：
1.2
通讯作者：
N. H. Siddique and H. Orimoto
中科院分区：
文献类型：
--
作者：
A. Ikuta;N. H. Siddique and H. Orimoto
The traditional standard stochastic system models, such as the autoregressive (AR), moving average (MA) and autoregressive moving average (ARMA) models, usually assume the Gaussian property for the fluctuation distribution, and the well-known least squares method is applied on the basis of only the linear correlation data. In the actual sound environment system, the stochastic process exhibits various non-Gaussian distributions, and there exist potentially various nonlinear correlations in addition to the linear correlation between input and output time series. Consequently, the system input and output relationship in the actual phenomenon cannot be represented by a simple model. In this study, a prediction method of output response probability for sound environment systems is derived by introducing a correction method based on the stochastic regression and fuzzy inference for simplified standard system models. The proposed method is applied to the actual data in a sound environment system, and the practical usefulness is verified.
