Fault diagnosis in pv systems using optimized deep learning techniques / (Record no. 173292)

MARC details
000 -LEADER
fixed length control field 04427namaa22004211i 4500
003 - CONTROL NUMBER IDENTIFIER
control field OSt
005 - أخر تعامل مع التسجيلة
control field 20250831132045.0
008 - FIXED-LENGTH DATA ELEMENTS--GENERAL INFORMATION
fixed length control field 250803s2024 ua a|||frm||| 000 0 eng d
040 ## - CATALOGING SOURCE
Original cataloguing agency EG-GICUC
Language of cataloging eng
Transcribing agency EG-GICUC
Modifying agency EG-GICUC
Description conventions rda
041 0# - LANGUAGE CODE
Language code of text/sound track or separate title eng
Language code of summary or abstract eng
-- ara
049 ## - Acquisition Source
Acquisition Source Deposit
082 04 - DEWEY DECIMAL CLASSIFICATION NUMBER
Classification number 623.043
092 ## - LOCALLY ASSIGNED DEWEY CALL NUMBER (OCLC)
Classification number 623.043
Edition number 21
097 ## - Degree
Degree Ph.D
099 ## - LOCAL FREE-TEXT CALL NUMBER (OCLC)
Local Call Number Cai01.13.08.Ph.D.2024.Gh.F
100 0# - MAIN ENTRY--PERSONAL NAME
Authority record control number or standard number Ghada Shaban Mohamed Ahmed,
Preparation preparation.
245 10 - TITLE STATEMENT
Title Fault diagnosis in pv systems using optimized deep learning techniques /
Statement of responsibility, etc. by Ghada Shaban Mohamed Ahmed ; Supervisors Prof. Dr. Hanan Kamal, Dr. Mohamed A. Moustafa Hassan.
246 15 - VARYING FORM OF TITLE
Title proper/short title تشخيص الأعطال في أنظمة الطاقة الشمسية الضوئية باستخدام تقنيات التعلم العميق المحسنة
264 #0 - PRODUCTION, PUBLICATION, DISTRIBUTION, MANUFACTURE, AND COPYRIGHT NOTICE
Date of production, publication, distribution, manufacture, or copyright notice 2024.
300 ## - PHYSICAL DESCRIPTION
Extent 99 pages :
Other physical details illustrations ;
Dimensions 30 cm. +
Accompanying material CD.
336 ## - CONTENT TYPE
Content type term text
Source rda content
337 ## - MEDIA TYPE
Media type term Unmediated
Source rdamedia
338 ## - CARRIER TYPE
Carrier type term volume
Source rdacarrier
502 ## - DISSERTATION NOTE
Dissertation note Thesis (Ph.D)-Cairo University, 2024.
504 ## - BIBLIOGRAPHY, ETC. NOTE
Bibliography, etc. note Bibliography: pages 92-99.
520 #3 - SUMMARY, ETC.
Summary, etc. The fast expansion of the solar photovoltaic (PV) sector over the past decade has contributed significantly to the significance of solar PV systems. Solar PV systems can be made more reliable, efficient, and safe by regularly monitoring the system and quickly identifying any faults. As a result, determining the kind of defect that happens in a solar PV system and its location are imperative. Once a fault has been identified and located, it must be fixed using the proper diagnosis technique. In this work, novel fault diagnosis and detection techniques were proposed. Deep Learning techniques were applied for correctly diagnosing the fault type achieving high accuracy of prediction. Specifically, supervised machine learning techniques such as KNN, LR, NB, and DT were applied. Back Propagation Neural Network (BPNN) was also applied for fault diagnosis. BPNN-PSO was introduced and applied for fault diagnosis showing high accuracy of prediction. Correction techniques for faults and maintenance of PV panels were presented to correct the diagnosed faults practically.
520 #3 - SUMMARY, ETC.
Summary, etc. لقد ساهم التوسع السريع لقطاع الطاقة الشمسية الضوئية (PV) على مدار العقد الماضي بشكل كبير في أهمية أنظمة الطاقة الشمسية الضوئية. يمكن زيادة موثوقية وكفاءة وسلامة أنظمة الطاقة الشمسية الضوئية من خلال مراقبة النظام بانتظام وتحديد أي أعطال بسرعة. نتيجة لذلك، فإن تحديد نوع العطل الذي يحدث في نظام الطاقة الشمسية الضوئية وموقعه أمر بالغ الأهمية. بمجرد تحديد وتحديد العطل، يجب إصلاحه باستخدام تقنية التشخيص المناسبة. في هذا العمل، تم اقتراح تقنيات جديدة لتشخيص وتحديد الأعطال. تم تطبيق تقنيات التعلم العميق لتشخيص نوع العطل بشكل صحيح وتحقيق دقة عالية في التنبؤ. على وجه التحديد، تم تطبيق تقنيات التعلم الآلي الخاضعة للإشراف مثل KNN و LR و NB و DT. كما تم تطبيق شبكة عصبية ذات انتشار خلفي (BPNN) لتشخيص الأعطال. تم تقديم وتطبيق BPNN-PSO لتشخيص الأعطال مع إظهار دقة عالية في التنبؤ. تم تقديم تقنيات تصحيح الأعطال وصيانة الألواح الشمسية لتصحيح الأعطال التي تم تشخيصها عمليًا.
530 ## - ADDITIONAL PHYSICAL FORM AVAILABLE NOTE
Issues CD Issues also as CD.
546 ## - LANGUAGE NOTE
Text Language Text in English and abstract in Arabic & English.
650 #0 - SUBJECT ADDED ENTRY--TOPICAL TERM
Topical term or geographic name entry element Electronics engineering
653 #1 - INDEX TERM--UNCONTROLLED
Uncontrolled term Deep Learning
-- PSO
-- Naïve Bayes
-- Back Propagation Neural Network
-- Decision Tree
700 0# - ADDED ENTRY--PERSONAL NAME
Personal name Hanan Kamal
Relator term thesis advisor.
700 0# - ADDED ENTRY--PERSONAL NAME
Personal name Mohamed A. Moustafa Hassan
Relator term thesis advisor.
900 ## - Thesis Information
Grant date 01-01-2024
Supervisory body Hanan Kamal
-- Mohamed A. Moustafa Hassan
Discussion body Essam El-Din M.Aboul Zahab
-- Ahmad Mohamed Elgarhy
Universities Cairo University
Faculties Faculty of Engineering
Department Department of Electronics and Communications Engineering
905 ## - Cataloger and Reviser Names
Cataloger Name Shimaa
Reviser Names Eman Ghareb
942 ## - ADDED ENTRY ELEMENTS (KOHA)
Source of classification or shelving scheme Dewey Decimal Classification
Koha item type Thesis
Edition 21
Suppress in OPAC No
Holdings
Source of classification or shelving scheme Home library Current library Date acquired Inventory number Full call number Barcode Date last seen Effective from Koha item type
Dewey Decimal Classification المكتبة المركزبة الجديدة - جامعة القاهرة قاعة الرسائل الجامعية - الدور الاول 03.08.2025 91847 Cai01.13.08.Ph.D.2024.Gh.F 01010110091847000 03.08.2025 03.08.2025 Thesis
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