تطوير خوارزمية ذكية للتنقيب عن التدفق المستمر للبيانات: دراسة حالة تقييم تلوث الهواء في مدينة حلب

الموضوعات

علوم تطبيقية وتكنولوجية

روابط وملفات

التعريف والنوع

رقم الوثيقة

01fce46a-302f-4f5c-8ab7-cf4ffb4a14ed

رقم العقد

0

نوع الوسائط

Crawler

نوع المحتوى

الرسائل العلمية

صيغة المصدر

رسائل ماجيستير

نوع الملف

pdf text

أسماء الملفات

1958492_1.pdf

بيانات النشر

ترجمة العنوان

Developing Intelligent Algorithm for Data Stream: Mining Case Study Evaluating the Air Pollution in Aleppo

ألقاب المؤلفين

[{"name_ar":"إياد هلالي","title_ar":"اعداد","title_en":"Preparation"},{"name_ar":"حازم عيسى","title_ar":"اشراف","title_en":"Supervision"},{"name_ar":"عبد القادر جوخدار","title_ar":"اشراف","title_en":"Supervision"}]

اللغة

Arabic

المصدر والدورية

اسم المصدر

تطوير خوارزمية ذكية للتنقيب عن التدفق المستمر للبيانات: دراسة حالة تقييم تلوث الهواء في مدينة حلب

المحتوى والصفحات

عدد الصفحات

180

ترجمة الملخص

The Air is considered one of the most significant major elements needed for life continuation on our planet. Natural or intended air pollution results in huge dangers, which affect human being and other beings as well as establishments. Most of the developed countries paid important attention on air pollution and dedicated large debits for doing research in this domain. Accordingly, there are stations for air pollution parameters sensing; the main goal of this thesis is to establish some mechanisms, which help in decision making by leaders so that they can keep at accepted globally rate or even zero pollution air. Aleppo is the second largest Syrian city, and it is the industrial capital of the Syrian Arab Republic, is prone to significant air pollution measures due to its industries and intensive populations live in this city. Due to the aforementioned reasons, there are five stations for air pollution parameters sensing distributed around Aleppo. This PhD thesis focuses on the data acquisitioned from those stations,it also processes the problems of missing data. The thesis has contributed the following key points:Proposing and implementing a novel mechanism for air pollution parameters consisted of four steps; including: available data receiving; initial data processing; AI-Based predictor/classifier design. The proposed classifier must enable decision makers to take an action upon the classifier results.Newly developing Bees Algorithm to find the optimum solution for missing data in air pollution.Developing three methods for processing missing data of air pollution and providing comparison among them to be used for compensating the values of missing data in which accurate values are obtained. Implementation of feature selection (Linear Correlation Filtering) for air pollution parameters selection with strong correlation to be used in a classifier building up and canceling those parameters with weak correlation, this may lead to less processing time and simpler analysis.AI-Based classifier building up.Web-Based design, which enables ease access to air pollution data and future prediction for few coming days.

كلمات الباحثين

Air Pollution, Bees Algorithm, Data Stream Mining, Feature Selection, Missing Values, Multi-Layer Perceptron, اختيار الخصائص, التنقيب عن تدفق البيانات, الشبكات العصبونية الصنعية, القيم المفقودة, تلوث الهواء, خوارزمية النحل, مدينة حلب

إشراف وإعداد

الإشراف

حازم عيسى, عبد القادر جوخدار

الإعداد

إياد هلالي

الاقتباسات الببليوغرافية