Modelling long-term vibration monitoring data with Gaussian Process time-series models

نویسندگان
چکیده

برای دانلود باید عضویت طلایی داشته باشید

برای دانلود متن کامل این مقاله و بیش از 32 میلیون مقاله دیگر ابتدا ثبت نام کنید

اگر عضو سایت هستید لطفا وارد حساب کاربری خود شوید

منابع مشابه

Gaussian process modelling of multiple short time series

We present techniques for effective Gaussian process (GP) modelling of multiple short time series. These problems are common when applying GP models independently to each gene in a gene expression time series data set. Such sets typically contain very few time points. Naive application of common GP modelling techniques can lead to severe over-fitting or under-fitting in a significant fraction o...

متن کامل

Gaussian Mixture Models for Time Series Modelling, Forecasting, and Interpolation

Gaussian mixture models provide an appealing tool for time series modelling. By embedding the time series to a higher-dimensional space, the density of the points can be estimated by a mixture model. The model can directly be used for short-to-medium term forecasting and missing value imputation. The modelling setup introduces some restrictions on the mixture model, which when appropriately tak...

متن کامل

Mixture Gaussian Time Series Modeling of Long-term Market Returns

Stochastic modeling of investment returns is an important topic for actuaries who deal with variable annuity and segregated fund investment guarantees. The traditional lognormal stock return model is simple, but it is generally less appealing for longer-term problems. In recent years, the use of regime-switching lognormal (RSLN) processes for modeling maturity guarantees has been gaining popula...

متن کامل

Gaussian Process Time-Series Models for Structures under Operational Variability

A wide range of vibrating structures are characterized by variable structural dynamics resulting from changes in environmental and operational conditions, posing challenges in their identification and associated condition assessment. To tackle this issue, the present contribution introduces a stochastic modelingmethodology viaGaussian Process (GP) time-series models. In the presently introduced...

متن کامل

Gaussian process prediction for time series of structured data

Time series prediction constitutes a classic topic in machine learning with wide-ranging applications, but mostly restricted to the domain of vectorial sequence entries. In recent years, time series of structured data (such as sequences, trees or graph structures) have become more and more important, for example in social network analysis or intelligent tutoring systems. In this contribution, w...

متن کامل

ذخیره در منابع من


  با ذخیره ی این منبع در منابع من، دسترسی به آن را برای استفاده های بعدی آسان تر کنید

ژورنال

عنوان ژورنال: IFAC-PapersOnLine

سال: 2019

ISSN: 2405-8963

DOI: 10.1016/j.ifacol.2019.12.343