Paper Info
Title
Trend Detection in Gold Worth Using Regression.
Abstract
A mapping chase autoregression shape is applied to predict gold worth here. Previous works centered on prediction of the instability of gold worth to reveal the characteristics of gold market. By the way, due to the fact that the data of gold worth have high dimensionality, MCAF is suitable and able to predict gold worth more accurately rather than other mechanisms. In this paper, the MCAF is used to the everyday worth of gold. The experimental results indicate MCAF outperforms BPNN technique, especially on stability, which reveals the advantage of MCAF technique in dealing with huge amounts of data.
Year
DOI
Venue
2016
10.1007/978-3-319-62434-1_24
ADVANCES IN COMPUTATIONAL INTELLIGENCE, MICAI 2016, PT I
Keywords
Field
DocType
Gold worth,Mapping chase autoregression,Predict shape
Autoregressive model,Regression,Computer science,Trend detection,Curse of dimensionality,Artificial intelligence,Machine learning,Gold as an investment
Conference
Volume
ISSN
Citations 
10061
0302-9743
0
PageRank 
References 
Authors
0.34
0
3
Name
Order
Citations
PageRank
Seyedeh Foroozan Rashidi100.34
Hamid Parvin226341.94
Samad Nejatian3226.14