المصدر: | زانكو - الإنسانيات |
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الناشر: | جامعة صلاح الدين |
المؤلف الرئيسي: | Abdullah, Shiraz Abdulkhaliq (Author) |
مؤلفين آخرين: | Omer, Paree khan Aabdulla (Co-Author) |
المجلد/العدد: | مج22, ع1 |
محكمة: | نعم |
الدولة: |
العراق |
التاريخ الميلادي: |
2018
|
الصفحات: | 288 - 296 |
ISSN: |
2218-0222 |
رقم MD: | 882001 |
نوع المحتوى: | بحوث ومقالات |
اللغة: | الإنجليزية |
قواعد المعلومات: | HumanIndex |
مواضيع: | |
كلمات المؤلف المفتاحية: |
Environmental | Principal Component Analysis | Orthogonal | Eigenvalue-Eigenvector | Kaiser Measurement
|
رابط المحتوى: |
الناشر لهذه المادة لم يسمح بإتاحتها. |
المستخلص: |
Principal component analysis (PCA) is a powerful tool for analyzing data. The other main advantage of PCA is that once you have found these patterns in the data, and you compress the data by reducing the number of dimensions, without much loss of information. It has been called one of the most valuable results from applied linear algebra. It is used abundantly in all forms of analysis - from neuroscience to computer graphics - because it is a simple, non-parametric method of extracting relevant information from confusing data. In fact, pollution the environment in our society is a huge problem which needs to solve and determine the reasons, here taking two different samples from Salahaddin University (students, lecturers) of all colleges, this research takes the negative points or gathers the ideas which helps to build a healthy environment in which you can live in without any hesitation, used the stratified sample in this research by questionnaire form for collecting information. Later PCA has been applied as a tool to analyzing the data and this application has been found to be a successful in this area because we reached to the most important result, the first component of the two levels has (7) common variables and it is usually explained the largest part of the variance in the analyzing, it shows us the convergence of intellectual awareness on campus the university against environmental pollution in the region. |
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ISSN: |
2218-0222 |