Combine holts winter and support vector machines in forecasting time series

This study proposes on a combine methodology that exploits the Holts- Winter (HW) model and the Support Vector Machines (SVM) model in forecasting time series. Problems of forecasting using time series data have been and still being addressed at every sphere of research using different approaches. T...

وصف كامل

التفاصيل البيبلوغرافية
المؤلف الرئيسي:	Salisu, Alfa Mohammed
التنسيق:	أطروحة
اللغة:	الإنجليزية
منشور في:	2013
الموضوعات:	QA Mathematics
الوصول للمادة أونلاين:	http://eprints.utm.my/47917/25/AlfaMohammedSalisuMFS2013.pdf

مواد مشابهة

Combine holts winter and support vector machines in forecasting time serie
حسب: Alfa, Mohammed Salisu
منشور في: (2013)

Combined forecast model involving wavelet-group methods of data handling for drought forecasting
حسب: Mohammed Salisu, Alfa
منشور في: (2021)

Genetic algorithm approach in improving winter's method of forecasting
حسب: Mohmad Kahar, Mohd. Nizam
منشور في: (2002)

Forecasting revenue passenger enplanements using wavelet-support vector machine
حسب: Zainuddin, Mohamad Aiman
منشور في: (2015)

Parameters estimation of holt-winter smoothing method using genetic algorithm
حسب: Mohd. Azmi, Nur Intan Liyana
منشور في: (2013)

Improved models in fuzzy time series for forecasting
حسب: Sadaei, Hossein Javedani
منشور في: (2013)

Empirical mode decomposition with least square support vector machine model for river flow forecasting
حسب: Ismail, Shuhaida
منشور في: (2016)

Error magnitude and directional accuracy for time series forecasting evaluation
حسب: Nor, Maria Elena
منشور في: (2014)

SWGARCH : an enhanced GARCH model for time series forecasting
حسب: Shbier, Mohammed Z. D
منشور في: (2017)

Developing defuzzifying method of fuzzy time-variant series for forecasting product demand
حسب: Saeed, Akbarnatajbisheh
منشور في: (2013)

Time series forecasting of airline passenger no-shows using fir neural network
حسب: Muhammad Hussein, Muhammad Zaly Shah
منشور في: (2002)

A hybrid of bekk garch with neural network for modeling and forecasting time series
حسب: Pung, Yean Ping
منشور في: (2021)

An enhanced support vector regression -African Buffalo optimisation algorithm for electricity time series forecasting
حسب: Maijama'a, Inusa Sani
منشور في: (2023)

Enhanced artificial bee colony-least squares support vector machines algorithm for time series prediction
حسب: Zuriani, Mustaffa
منشور في: (2014)

Time arrival in series forecasting model for tourist National Park Kuala Tahan, Pahang
حسب: Megat Muhammad Afif, Megat Muainuddin
منشور في: (2021)

An application of predicting student performance using kernel k-means and smooth support vector machine
حسب: Sajadin, Sembiring
منشور في: (2012)

Self organizing map and least square support vector machine method for river flow modelling
حسب: Ismail, Shuhaida
منشور في: (2011)

Incorporating optimized local protein structures and granular support vector machines for structural class prediction
حسب: Hassan, Rohayanti
منشور في: (2011)

Combining group method of data handling models using artificial bee colony algorithm for time series forecasting
حسب: Yahya, Nurhaziyatul Adawiyah
منشور في: (2019)

The comparative forecast performance of univariate and multivariate model: an application to time series forecasting
حسب: Sallehuddin, Roselina, وآخرون
منشور في: (2009)

Time series support vector regression models with missing data treatments for water level prediction
حسب: Ibrahim, Noraini
منشور في: (2014)

Hybridization of nonlinear and linear models for time series forecasting
حسب: Salleh@Sallehuddin, Roselina
منشور في: (2010)

Improved mutual information method in combination model selection for forecasting tourist arrival
حسب: Md. Maarof, Mohd. Zulariffin
منشور في: (2019)

New bio-inspired barnacle optimizers based least-square support vector machine for time-series prediction of pandemic outbreaks
حسب: Marzia, Ahmed
منشور في: (2024)

Combined empirical mode decomposition and dynamic regression model for forecasting electricity load demand
حسب: Akrom, Nuramirah
منشور في: (2015)

Email categorization using support vector machine
حسب: Mohd. Daud, Mariah
منشور في: (2004)

A similarity of multivariate time series in stocks network analysis
حسب: Gan, Siew Lee
منشور في: (2016)

The enhanced group method of data handling models for time series forecasting
حسب: Samsudin, Ruhaidah
منشور في: (2012)

Preprocessing And Clustering Short Time-Series Microarray
حسب: Loh, Wei Ping
منشور في: (2008)

Time series support vector regression models with missing data treatments for water lavel prediction
حسب: Ibrahim, Noraini
منشور في: (2014)

Time series modeling and designing of artifical neural network (ANN) for revenue forecasting
حسب: Mohd. Yusof, Norfadzlia
منشور في: (2005)

Detecting Structural Break In Commodity Time Series Data
حسب: Jatarona , Nurul Najwa
منشور في: (2010)

Modeling Malaysian Road Accidents: The Structural Time Series Approach
حسب: Junus, Noor Wahida Binti Md
منشور في: (2018)

Anomaly behavior detection using flexible packet filtering and support vector machine algorithms
حسب: Abdul Wahid, Mohammed N.
منشور في: (2016)

Interminable Long Memory Model And Its Hybrid For Time Series Modeling
حسب: Alhaji, Jibrin Sanusi
منشور في: (2019)

A new classifier based on combination of genetic programming and support vector machine in solving imbalanced classification problem
حسب: Mohd Pozi, Muhammad Syafiq
منشور في: (2016)

The forecast of some Malayan Economic time series / Hapisah Imam Lipat
حسب: Hapisah, Imam Lipat
منشور في: (1970)

A public transport travel time prediction using least squares support vector machine
حسب: Sadat Zadeh, Seyed Mojtaba Tafaghod
منشور في: (2013)

Parameter-driven count time series models / Nawwal Ahmad Bukhari
حسب: Nawwal , Ahmad Bukhari
منشور في: (2018)

Time series modeling and designing and artificial neural network (ANN) for revenue forecasting
حسب: Mohd Yusof, Norfadzlia
منشور في: (2006)