ارائه مدل تحلیل ریسک‌ در پروژه‌‌های شهرسازی مبتنی بر تکنیک داده‌کاوی با مطالعه موردی

نوع مقاله : مقاله پژوهشی

نویسندگان

1 مربی، دانشگاه تربت حیدریه.

2 کارشناسی ارشد، دانشگاه صنعتی سجاد مشهد.

3 دانشیار، دانشگاه صنعتی شاهرود.

10.52547/jimp.10.2.137

چکیده

تحلیل واکنش درست به ریسک یکی از فرایندهای مهم مدیریت پروژه است. هدف از انجام این پژوهش، دسته‌بندی ریسک­‌های پروژه شهرسازی است. بدین‌منظور، پس از شناسایی ریسک‌­های پروژه شهرسازی، برای ارزیابی ریسک­‌ها مهم‌ترین شاخص‌های با تأیید خبرگان توسعه داده شده است که عبارت‌اند از: میزان تأثیر بر زمان؛ هزینه و کیفیت؛ احتمال وقوع؛ اثرات زیست‌محیطی؛ تأثیرات ایمنی؛ اهمیت ریسک؛ میزان مدیریت‌­پذیری ریسک و استراتژی پاسخ به ریسک؛ سپس ارزیابی ریسک‌ها با استفاده از شاخص‌های مدنظر انجام شد. تمامی مراحل تحلیل با استفاده از روش استاندارد داده‌کاوی کرسیپ اجرا و سطوح اهمیت ریسک، مدیریت‌پذیری ریسک و استراتژی پاسخ با استفاده از الگوریتم‌های داده‌کاوی پیشنهادی به تفکیک پیش‌بینی شدند. یافته‌‌های پژوهش نشان می‌دهند که الگوریتم‌های دسته‌بندی در مدیریت ریسک از عملکرد مطلوبی برخوردارند. الگوریتم دسته‌بندی لجستیک، میزان اهمیت و مدیریت‌پذیری ریسک را به‌­ترتیب با نرخ صحت 88/0 و 9/0 پیش‌بینی کرده ‌است؛ همچنین الگوریتم دسته‌بندی بیزی نیز در پیش‌بینی استراتژی پاسخ به ریسک توانسته است با نرخ صحت 84/0 عملکرد بهتری نسبت به سایر الگوریتم‌ها نشان دهد. برای بررسی بیشتر الگوریتم‌­های مورد­استفاده، نتایج با یکی از روش‌­های متداول، یعنی روش تاپسیس، مقایسه شد که  الگوریتم‌های داده‌کاوی در مقایسه با روش تاپسیس نتیجه بهتری ارایه دادند.

کلیدواژه‌ها

عنوان مقاله [English]

Presentation of Risks Analysis Model in Urban Projects Based on Data Mining Technique with Case Study

نویسندگان [English]

  • mohammad ghodoosi 1
  • Fatemeh Mirsaeedi 2
  • Aliakbar Hasani 3
1 Instructor, University of Torbat Heydarieh.
2 Master of Science, Sadjad University of Technology.
3 Associate Professor, Shahrood University of Technology.
چکیده [English]

Analysis of the right response to risk is one of the important processes in project management. The purpose of this research is to categorize the risks of the urban projects. To this end, after identifying the risks of the urban project, the most important indicators are developed in line with experts’ opinions to evaluate risks. These include impact on time, cost, quality, probability of occurrence, environmental impact, safety effects, importance of risk, risk manageability and risk response strategy. Then, the risk assessment is performed using the desired indicators. All steps are implemented according to CRISP-DM standard methodology and the importance of risk, risk manageability, and risk response strategy are predicted by data mining algorithms. The results show that classification algorithms performed in risk management successfully. Importance of risk and risk manageability are predicted by logistic regression whose accuracy rates are respectively equal 0.88 and 0.9. For risk response strategy, the Naïve Bayes algorithm performed better than other algorithms with an accuracy rate of 0.84. For further investigation of the used algorithms, the results are compared with one of the MCDM methods, the TOPSIS method. Data mining algorithms performed better than the TOPSIS method.

کلیدواژه‌ها [English]

  • Evaluation of Risk
  • Risk Manageablity
  • Risk Response Strategy
  • Optimum Algorithm
  • Data Mining

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