Xây dựng một mô hình lai đa đầu ra để dự báo chuỗi thời gian có giá trị trong khoảng thời gian

Tóm tắt

Time series analysis and forecasting is an attractive research area over the last few years, especialy in interval-valued time series. Financial market is an example; a useful model may be of great interest to home brokers who do not possess sufficient knowledge to invest in such companies. In this paper, multi-input multi-output least square support vector regression (MIMO-LSSVR) is an improved algorithm based on support vector machine (SVM), with the combination of the sliding-window algorithm is proposed for interval-valued time series forecasting, a new branch in time series analysis field. The experiment shows MIMO-S-LSSVR positive outcomes than previous results. A retest using twotime series data sets in three years demonstrates that the proposed model is a promising alternative for interval-valued time series forecasting.