برآورد هزینه های ساختمان با روش های هوشمند داده مبنا و مشخص کردن عوامل تاثیرگذار بر هزینه‌های ساخت ( مطالعه موردی شرق استان تهران)

نوع مقاله : علمی - پژوهشی

نویسندگان

1 دانشجوی کارشناسی ارشد مهندسی و مدیریت ساخت موسسه آموزش عالی پردیسان فریدونکنار

2 استادیار موسسه آموزش عالی پردیسان، فریدونکنار، ایران

3 دپارتمان مهندسی عمران،موسسه آموزش عالی طبری بابل،بابل،ایران

4 استادیار گروه عمران دانشگاه صنعتی شاهرود

چکیده

امروزه اهمیت هزینه‌های ساخت در پروژه‌های عمرانی روز به روز افزایش می‌یابد و لازم می‌گردد تا به بررسی برآورد هزینه‌های ساخت و عوامل تاثیرگذار در هزینه‌ی ساخت و ساز مورد مطالعه قرار گیرد. این پژوهش با موضوع برآورد هزینه‌های ساختمان با روش‌های هوش مصنوعی، مشخص کردن عوامل تاثیرگذار بر هزینه و بهینه‌سازی هزینه‌ها در شرق استان تهران انجام گردیده است. برای برآورد هزینه‌های ساختمانهای مسکونی در این پژوهش از 46 ساختمان مسکونی که در سالهای 1393-1396 در منطقه‌ی شرق استان تهران اجرا شده‌اند، استفاده شده است و از روش‌های هوش مصنوعی جهت برآورد و مدل‌سازی‌ها که از روش‌های ANN، روش شبکه‌ی عصبی مصنوعی، GEP الگوریتم ژنتیک و SVM بردار پشتیبان استفاده شده است و همچنین برای تشخیص عوامل تاثیرگذار بر هزینه از پرسشنامه و روش آزمون فریدمن جهت اولویت‌بندی عوامل استفاده گردید تا با داشتن این دو فاکتور یعنی عوامل تاثیرگذار بر هزینه و برآورد هزینه‌های ساختمان بتوانیم هزینه‌ها را بهینه‌سازی کنیم. پس از بررسی‌ها و مطالعات نتایجی که بدست آمد، برآورد هزینه‌ها با روش‌های ANN,GEP,SVM انجام شد و با مقایسه‌های این روش‌ها، روش GEP به علت خطای کمتر و دقت پیش‌بینی بالاتر روشی برتر نسبت به دو روش دیگر بوده است. عوامل تاثیرگذار بر هزینه نیز با روش آزمون فریدمن تعیین شد که با بررسی این فاکتورها هزینه های ساخت بهینه‌سازی گردید.

کلیدواژه‌ها


عنوان مقاله [English]

Estimation of the building costs using intelligence data driven methods and determining the factors influencing on cost. (Case study: East of Tehran province)

نویسندگان [English]

  • reza lotfi kazemi 1
  • Mohammad Javad Taheri Amiri 2
  • Ali Ashrafian 3
  • Hossein Pahlavan 4
1 msc student in construction engineering and management, higher education institute of pardisan
2 Assistant professor, Pardisan University of Fereydonkenar, Fereydonkenar, Iran
3 Civil Engineering Department, Tabari University, Babol, Iran
4 Assistant Professor, Department of Civil Engineering, Shahrood University of Technology
چکیده [English]

Today, the importance of construction costs in construction projects is increasing day by day and it is necessary to study the estimation of construction costs and the factors affecting construction costs.This research has been done around the subject of estimate the construction costs by intelligence data driven methods named Artificial Neural Network (ANN), Support Vector Machine (SVM) and Gene Expression Programming (GEP) determine the effective factors on cost and cost optimization in east of Tehran. To estimate the costs of residential buildings, in this research it's used from 46 residential buildings which were implemented in west of Tehran and it's used from the artificial intelligence method to estimate the construction costs that is used from ANN, artificial neural network method, GEP, SVM and it was used from questionnaire and Friedman test method to diagnosis the effective factors on costs to prioritize factors that can optimize the costs by possessing these two factors, the effective factors on costs and construction costs estimation . After reviews and studies we resulted that costs estimation had been done by ANN, GEP, SVM methods and by comparing these methods, GEP cause of its less errors and more predictability, was the best method than others. The effective factors on costs were determined by Friedman test method that after reviews these factors, construction costs had been optimized.

کلیدواژه‌ها [English]

  • Artificial intelligence methods
  • Estimation
  • Effective factors on cost
  • optimization
  • ANN
  • SVM
  • GEP
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