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Selecting Real Seismic Records and Scaling it to Fit the Syrian Design Spectra using Genetic Algorithm

اختيار السجلات الزلزالية الحقيقية و تقييسها لملائمة طيف الاستجابة التصميمي السوري باستخدام الخوارزمية الجينية

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 Publication date 2015
and research's language is العربية
 Created by Shamra Editor




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In this study, basic methodologies of the GA and the scaling procedures are summarized, the scaling criteria of real time history records to satisfy the Syrian design code are discussed. The traditional time domain scaling procedures and the scaling procedures using GA are utilized to scale a number of the available real records to match the Syrian design spectra. The resulting time histories of the procedures are investigated and compared in terms of meeting criteria.


Artificial intelligence review:
Research summary
تتناول هذه الدراسة اختيار السجلات الزلزالية الحقيقية وتقييسها لمطابقة طيف الاستجابة التصميمي السوري باستخدام الخوارزمية الجينية. بعد اختيار السجلات الحقيقية، يجب تقييسها لمطابقة شدة الزلزال المحتملة في الموقع. عادةً ما يتم ذلك باستخدام التقييس الموحد في مجال الزمن، حيث يتم تكبير أو تصغير السجلات الزمنية بشكل موحد لتتم مطابقتها مع طيف الاستجابة الهدف. ومع ذلك، فإن إيجاد معاملات التقييس الأمثل هو مهمة معقدة، لذلك استخدم الباحثون الخوارزمية الجينية، وهي إحدى طرائق البحث التطورية الصناعية التي تعتمد على الاختيار الطبيعي وآليات الوراثة. تم تلخيص المنهجيات الخاصة بالخوارزمية الجينية وعمليات التقييس، وناقشت الدراسة معايير تقييس السجلات الزمنية الحقيقية. ثم تم تطبيق إجراءات التقييس التقليدية في مجال الزمن وإجراءات التقييس باستخدام الخوارزمية الجينية على عدد من السجلات الحقيقية المتوفرة لمطابقة الطيف التصميمي السوري. وأخيرًا، تم فحص السجلات الزمنية الناتجة ومقارنتها لمعرفة مدى مطابقتها لمتطلبات الكود السوري. أظهرت النتائج أن استخدام الخوارزمية الجينية أكثر فعالية في تحقيق المطابقة المثلى مع الطيف الهدف مقارنة بالطريقة التقليدية، حيث أظهرت قيم معاملات التقييس الناتجة عن استخدام الخوارزمية الجينية أنها تحافظ على السجلات بشكل أفضل وتقلل من الضرر الناتج عن التقييس.
Critical review
دراسة نقدية: تعتبر هذه الدراسة إضافة قيمة لمجال تقييس السجلات الزلزالية، حيث تقدم منهجية جديدة باستخدام الخوارزمية الجينية لتحسين دقة المطابقة مع طيف الاستجابة التصميمي. ومع ذلك، يمكن توجيه بعض الانتقادات البناءة. أولاً، الدراسة تركز بشكل كبير على الجانب التقني دون تقديم تحليل شامل لتأثير هذه المنهجية على السلامة الهيكلية للمنشآت. ثانياً، لم يتم التطرق بشكل كافٍ إلى التحديات العملية التي قد تواجه المهندسين عند تطبيق هذه الخوارزمية في مشاريع حقيقية. ثالثاً، كان من الممكن تعزيز الدراسة بإجراء مقارنات مع منهجيات أخرى حديثة في نفس المجال لتقديم رؤية أوسع وشاملة. وأخيراً، قد يكون من المفيد تقديم توصيات أكثر تفصيلاً حول كيفية تحسين الخوارزمية الجينية لتكون أكثر فعالية في تطبيقات مختلفة.
Questions related to the research
  1. ما هي الخوارزمية الجينية وكيف تم استخدامها في هذه الدراسة؟

    الخوارزمية الجينية هي إحدى طرائق البحث التطورية الصناعية التي تعتمد على الاختيار الطبيعي وآليات الوراثة. في هذه الدراسة، تم استخدامها لإيجاد معاملات التقييس الأمثل للسجلات الزلزالية لمطابقتها مع طيف الاستجابة التصميمي السوري.

  2. ما هي الفائدة الرئيسية من استخدام الخوارزمية الجينية مقارنة بالتقييس الموحد في مجال الزمن؟

    الفائدة الرئيسية من استخدام الخوارزمية الجينية هي تحقيق مطابقة أفضل مع طيف الاستجابة الهدف وتقليل الضرر الناتج عن التقييس على السجلات الزلزالية، مما يجعلها أكثر فعالية من التقييس الموحد في مجال الزمن.

  3. ما هي التحديات التي قد تواجه المهندسين عند تطبيق الخوارزمية الجينية في مشاريع حقيقية؟

    من التحديات التي قد تواجه المهندسين هي التعقيد التقني للخوارزمية الجينية، الحاجة إلى خبرة متقدمة في البرمجة والتحليل الزلزالي، وكذلك التحديات المتعلقة بتكامل هذه الخوارزمية مع الأنظمة الهندسية الحالية.

  4. ما هي التوصيات التي قدمها الباحثون بناءً على نتائج الدراسة؟

    أوصى الباحثون باستخدام الخوارزمية الجينية في عملية تقييس السجلات الزلزالية بعد اختيار السجلات المناسبة، كونها تعطي المطابقة الأفضل مع الطيف الهدف. كما أوصوا بدراسة الفرق بين الطريقتين عند استخدام مجموعات مؤلفة من ثلاثة سجلات زلزالية فقط كما تسمح الكودات.


References used
American Society of Civil Engineers. (2007). ASCE/SEI 41- 06. Seismic rehabilitation of existing buildings, American Society of Civil Engineers, Reston, Va.2007
DEB, K. 2001. Multi-objective optimization using evolutionary algorithms, Wiley Interscience, Hoboken, U.S.A
Dubertret, L., Review of the structural geology of the Red Sea and Surounding areas, Royal Society of London philosophical transactions, Series A 267,1970, 9-20
FONSECA, C.M. & FLEMING, P.J. 1993. Genetic algorithms for multi objective optimization; optimization, formulation discussion and generalization. In: FORREST, S. Proceedings 5th International Conference on Genetic Algorithms, University of Illinois at Urbana- Champaign, U.S.A. pp416- 423
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