@article{MAKHILLJEAS2019141017851,
    title = {Using Particle Swarm Optimization Algorithm to Address the
Multicollinearity Problem},
    journal = {Journal of Engineering and Applied Sciences},
    volume = {14},
    number = {10},
    pages = {3345-3353},
    year = {2019},
    issn = {1816-949x},
    doi = {jeasci.2019.3345.3353},
    url = {https://makhillpublications.co/view-article.php?issn=1816-949x&doi=jeasci.2019.3345.3353},
    author = {Sabah Manfi,Adila and},
    keywords = {The multicollinearity problem,particle swarm optimization algorithm,multicollinearity,MATLAB,important problems,relationship},
    abstract = {The problem of the multicollinearity problem is one of the important problems that occur in the data
which address the existence of the linear relationship between the independent variables. The aim of this study
is to address the problem of the multicollinearity problem using particle swarm optimization algorithm
or so-called intelligence of the squadron. The variables were generated with different sample sizes for small and
large samples (10, 30, 100 and 200) as well as the correlation coefficients between the independent variables
(0.85, 0.90 and 0.99) a program was written in MATLAB R 2013 a Version, 8.1, Na had reached the superiority
of particle swarm optimization algorithm in all sizes and samples of all correlation coefficients, the comparison
has been using the average error boxes (Mean Square Error (MSE)).}
    }