shahab M, A., H.A. AL Z., T., Sedeek Kareem, N. (2020). De-noise data by using Multivariate Wavelets in the Path analysis with application. Alustath, 10(1), 268-294.
Awaz shahab M; Taha H.A. AL Z.; Nazeera Sedeek Kareem. "De-noise data by using Multivariate Wavelets in the Path analysis with application". Alustath, 10, 1, 2020, 268-294.
shahab M, A., H.A. AL Z., T., Sedeek Kareem, N. (2020). 'De-noise data by using Multivariate Wavelets in the Path analysis with application', Alustath, 10(1), pp. 268-294.
shahab M, A., H.A. AL Z., T., Sedeek Kareem, N. De-noise data by using Multivariate Wavelets in the Path analysis with application. Alustath, 2020; 10(1): 268-294.

De-noise data by using Multivariate Wavelets in the Path analysis with application

journal of kirkuk University For Administrative and Economic Sciences
Volume 10, Issue 1, June 2020, Pages 268-294    PDF (2.13 M)
Authors
Awaz shahab M; Taha H.A. AL Z.; Nazeera Sedeek Kareem
University of Kirkuk Journal For Administrative and Economic Science
Abstract
In this research dealing with pollution in multivariate data used in the analysis path through the purification by an algorithm proposed based on multivariate wavelets (Daubechies, bior and rbio) and soft thresholding and estimate of level in a way (Minimax) and then compare them with the results path analysis before dealing with pollution through the practical application of analyzing the causes of a problem water pollution in the Kurdistan region, concluded research on the proposed algorithm is efficient compared with the classical method depending on the MATLAB language and program (SPSS) with (Amos).

 
Keywords
De-noise; multivariate Wavelets; Path analysis; thresholding
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