Wavelet SVM Regression Algorithm and Its Application in Chaotic Time Series Prediction
نویسندگان
چکیده
منابع مشابه
Chaotic Time Series Prediction Using Wavelet Decomposition
A novel approach to chaotic time series prediction is proposed. It is based on the use of the Discrete Wavelet Transform for obtaining a proper decomposition of the original sequence and standard multilayer neural networks for performing the prediction of the individual components. Simulation results for the case of chaotic signals obtained by integrating the Lorenz equations are presented, and...
متن کاملchaotic time series prediction by auto fuzzy regression model
since the pioneering work of zadeh, fuzzy set theory has been applied to amyriad of areas. song and chissom introduced the concept of fuzzy time series andapplied some methods to the enrolments of the university of alabama. thereafter weapply fuzzy techniques for system identification and apply statistical techniques tomodelling system. an automatic methodology framework that combines fuzzytech...
متن کاملShort Term Chaotic Time Series Prediction using Symmetric LS-SVM Regression
In this article, we illustrate the effect of imposing symmetry as prior knowledge into the modelling stage, within the context of chaotic time series predictions. It is illustrated that using Least-Squares Support Vector Machines with symmetry constraints improves the simulation performance, for the cases of time series generated from the Lorenz attractor, and multi-scroll attractors. Not only ...
متن کاملDIPLOMARBEIT Support Vector Machines for Regression Estimation and their Application to Chaotic Time Series Prediction
Support vector machines (SVMs) are a quite recent supervised learning approach towards function estimation. They combine several results from statistical learning theory, optimisation theory, and machine learning, and employ kernels as one of their most important ingredients. The present work covers the theory of SVMs with emphasis on SVMs for regression estimation, and the problem of chaotic t...
متن کاملA Novel Evolving Clustering Algorithm with Polynomial Regression for Chaotic Time-Series Prediction
Time-series prediction has been a very well researched topic in recent studies. Some popular approaches to this problem are the traditional statistical methods e.g. multiple linear regression and moving average, and neural network with the Multi Layer Perceptron which has shown its supremacy in time-series prediction. In this study, we used a different approach based on evolving clustering algo...
متن کاملذخیره 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: Energy Procedia
سال: 2011
ISSN: 1876-6102
DOI: 10.1016/j.egypro.2011.10.951