Time series forecasting using least square support vector machine for Canadian Lynx data by Shabri, Ani, Ismail, Shuhaida

“…This paper discusses the application of Least Square Support Vector Machine (LSSVM) models for Canadian Lynx forecasting. The objective of this paper is to examine the flexibility of LSSVM in time series forecasting by comparing it with other models in previous research such as Artificial Neural Networks (ANN), Auto-Regressive Integrated Moving Average (ARIMA), Feed-Forward Neural Networks (FNN), Self-Exciting Threshold Auto-Regression (SETAR), Zhang’s model, Aladang’s hybrid model and Support Vector Regression (SVR) model. …”

Improvement of time forecasting models using a novel hybridization of bootstrap and double bootstrap artificial neural networks by Zainuddin, Nurul Hila, Lola, Muhamad Safiih, Djauhari, Maman Abdurachman, Yusof, Fadhilah, Ramlee, Mohd. Noor Afiq, Deraman, Aziz, Ibrahim, Yahaya, Abdullah, Mohd. Tajuddin

“…Our investigation is based on three well-known real datasets, i.e., Wolf's sunspot data, Canadian lynx data and, Malaysia ringgit/United States dollar exchange rate data. …”