The Svm Approach for Box–jenkins Models
نویسندگان
چکیده
• Support Vector Machine (SVM) is known in classification and regression modeling. It has been receiving attention in the application of nonlinear functions. The aim is to motivate the use of the SVM approach to analyze the time series models. This is an effort to assess the performance of SVM in comparison with ARMA model. The applicability of this approach for a unit root situation is also considered. Key-Words: • Support Vector Machine; time series analysis; unit root. AMS Subject Classification: • 49A05, 78B26. 24 Saeid Amiri, Dietrich von Rosen and Silvelyn Zwanzig The SVM Approach for Box–Jenkins Models 25
منابع مشابه
Forecasting Milled Rice Production in Ghana Using Box-Jenkins Approach
The increasing demand for rice in Ghana has been a major concern to the government and other stakeholders. Recent concerns by the coalition for African Rice Development (CARD) to double rice production within ten years in Sub-Saharan countries have triggered the to implement strategies to boost rice production in the government. To fulfill this requirement, there is a need to monitor and foreca...
متن کاملCarbon Monoxide Prediction in the Atmosphere of Tehran Using Developed Support Vector Machine
Air quality prediction is highly important in view of the health impacts caused by exposure to air pollutants in urban air. This work has presented a model based on support vector machine (SVM) technique to predict daily average carbon monoxide (CO) concentrations in the atmosphere of Tehran. Two types of SVM regression models, i.e. -SVM and -SVM techniques, were used to predict average daily C...
متن کاملCarbon Monoxide Prediction in the Atmosphere of Tehran Using Developed Support Vector Machine
Air quality prediction is highly important in view of the health impacts caused by exposure to air pollutants in urban air. This work has presented a model based on support vector machine (SVM) technique to predict daily average carbon monoxide (CO) concentrations in the atmosphere of Tehran. Two types of SVM regression models, i.e. -SVM and -SVM techniques, were used to predict average daily C...
متن کاملSoft Rbf Neural Network Models and an Svm Model for Wages Time Series Modeling and Forecasting
The wages time series are in fact stochastic in which successive observations are dependent and can be represented by a linear combination of independent random variables , , 1 − t t ε ε ... . If the successive observations are highly dependent, we should use in model past values of the time series variable and (or) current and past values of the error terms { t ε }. There are available techniq...
متن کاملPrediction of Stock Price using Particle Swarm Optimization Algorithm and Box-Jenkins Time Series
The purpose of this research is predicting the stock prices using the Particle Swarm Optimization Algorithm and Box-Jenkins method. In this way, the information of 165 corporations is collected from 2001 to 2016. Then, this research considers price to earnings per share and earnings per share as main variables. The relevant regression equation was created using two variables of earnings per sha...
متن کامل