학술논문

Estimating time series future optima using a steepest descent methodology as a backtracker
Document Type
Conference
Source
2008 International Multiconference on Computer Science and Information Technology Computer Science and Information Technology, 2008. IMCSIT 2008. International Multiconference on. :893-898 Oct, 2008
Subject
Computing and Processing
History
Equations
Yttrium
Computer science
Information technology
Optimization methods
Finance
Meteorology
Temperature
Agriculture
Language
Abstract
Recently it was produced a backtrack technique for the efficient approximation of a time series’ future optima. Such an estimation is succeeded based on a selection of sequenced points produced from the repetitive process of the continuous optima finding. Additionally, it is shown that if any time series is treated as an objective function subject to the factors affecting its future values, the use of any optimization technique finally points local optimum and therefore enables accurate prediction making. In this paper the backtrack technique is compiled with a steepest descent methodology towards optimization.