NDLI: Prediction of output response probability for sound environment system by introducing stochastic regression and fuzzy inference for simplified standard system model

Content Provider	IEEE Xplore Digital Library
Author	Ikuta, A. Orimoto, H.
Copyright Year	2010
Description	Author affiliation: Department of Management Information Systems, Prefectural University of Hiroshima, Hiroshima, 734-8558 Japan (Ikuta, A.; Orimoto, H.)
Abstract	The traditional standard stochastic system models, such as the AR (Autoregressive), MA (Moving average) and ARMA (Autoregressive moving average) models, usually assume the Gaussian property for the fluctuation distribution. These models assume also the linear regression function for the time series of system input and output, and the well-known least squares method is applied based only on the linear correlation data. In the actual sound environment system, however, the stochastic process exhibits various non-Gaussian distributions, and there potentially exist various nonlinear correlations in addition to the linear correlation between input and output time series. Consequently, often the system input and output relationship in the actual phenomenon cannot be represented by a simple model such as the AR, MA and ARMA models. In this study, a prediction method of output response probability for sound environment system is derived by introducing a correction method for simplified standard system models. More precisely, a parameter-linear regression model is adopted as a simplified standard system model for the input and output relationship. Furthermore, a correction method for the simplified standard system model is proposed by introducing the stochastic regression and fuzzy inference. The proposed method is applied to the actual data in a sound environmnet system, and the practical usefulness is verified.
Starting Page	1
Ending Page	6
File Size	578991
Page Count	6
File Format	PDF
ISBN	9781424490233
e-ISBN	9781424490240
DOI	10.1109/UKRICIS.2010.5898144
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2010-09-01
Publisher Place	United Kingdom
Access Restriction	Subscribed
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	Correlation Roads Noise Probability density function Predictive models Probability distribution Autoregressive processes
Content Type	Text
Resource Type	Article

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2	Indian Institute of Technology Kharagpur	Host Institute of the Project: The host institute of the project is responsible for providing infrastructure support and hosting the project	https://www.iitkgp.ac.in
3	National Digital Library of India Office, Indian Institute of Technology Kharagpur	The administrative and infrastructural headquarters of the project	Dr. B. Sutradhar bsutra@ndl.gov.in
4	Project PI / Joint PI	Principal Investigator and Joint Principal Investigators of the project	Dr. B. Sutradhar bsutra@ndl.gov.in Prof. Saswat Chakrabarti will be added soon
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