استفاده از تکنیک‌های داده‌کاوی در تامین دانش برای یک سیستم تصمیم یار (موردکاوی شرکت اتوبوسرانی تهران)

نوع مقاله : علمی - پژوهشی

نویسندگان

1 دانش آموخته کارشناسی ارشد، دانشکده مهندسی صنایع، دانشگاه آزاد اسلامی واحد تهران جنوب، تهران، ایران

2 استادیار، دانشکده مهندسی صنایع، دانشگاه علم و صنعت ایران، تهران، ایران

3 استاد، دانشکده مهندسی صنایع، دانشگاه علم و صنعت ایران، تهران، ایران

چکیده

در این مطالعه داده‌های تخلفات شرکت اتوبوسرانی تهران با استفاده ازتکنیک های داده‌کاوی مورد بررسی و به کشف دانش پنهان میان داده‌ها پرداخته شده است. در ابتدا داده‌های تخلفات شرکت‌های پیمانکار اتوبوسرانی تهران در حدفاصل سال‌های 1391 تا 1394 جمع‌آوری و جهت ورود به نرم‌افزار آماده‌سازی گردید. در مرحله بعد با بهره‌مندی از الگوریتم‌های قوانین انجمنی و درخت تصمیم جهت استخراج دانش استفاده شده است. تعیین شرکت‌های با میزان عملکرد پایین و تخلفات با فراوانی زیاد و ارتباط رخداد آن‌ها در فصول مختلف از جمله نتایج قابل توجهی است که بعنوان خروجی الگوریتم‌های مورد استفاده محسوب می‌گردد. مدیران عالی سازمان‌ها به منظور تصمیم‌گیری در شرایط عدم قطعیت نیاز دارند که از سیستم‌های تصمیم‌یار بهره‌مند شوند. نتایج خروجی تحقیق این مکان را فراهم می‌نماید که به منظور دستیابی یکی از اهداف عالی سازمان که رضایت شهروندی است، مدیران سازمان را در تامین دانش برای اتخاذ تصمیم  یاری نمایند. ریشه‌یابی علل رخداد تخلفات و تعیین فصول و ماه‌های پرتکرار از منظر تخلفات، می‌تواند باعث تدوین دستورالعمل‌ها و رویه‌های بهبود در شرکت اتوبوسرانی گردد که ضمن کنترل شرایط موجود، شرکت‌های پیمانکار را ملزم به اجرای دقیق قوانین و کاهش رخداد تخلفات می‌نماید. به هر حال این یک واقعیت است که بمنظور دستیابی به شرایط باثبات و پایدار برای تمامی واحدهای تولیدی، صنعتی و خدماتی همانند مطالعه موردی موردنظر، توجه به رضایت مشتری لازم و ضروری است. 

کلیدواژه‌ها

موضوعات

عنوان مقاله [English]

Using Data Mining Techniques in Providing Knowledge for Decision Support System (Case Study: Tehran Bus Transportation System)

نویسندگان [English]

  • Ardalan Badami 1
  • Rouzbeh Ghousi 2
  • Mohammad Saidi Mehrabad 3
1 MSc. Grad., Department of Industrial Engineering, Islamic Azad University, South Tehran Branch, Tehran, Iran
2 Professor, School of Industrial Engineering, Iran University of Science and Technology, Tehran, Iran
3 Professor, School of Industrial Engineering, Iran University of Science and Technology, Tehran, Iran
چکیده [English]

Using Data Mining techniques, the committed violations by Tehran Bus Company have been analyzed and consequently the hidden knowledge among data has been discovered in this research. First, the data from committed violations by Tehran Bus Company within 2012 to 2015 have been gathered and made ready for the program. The next stage is to extract knowledge through the algorithms of Association Rules and Decision Tree. Identifying the companies with poor performance and high rate of violations and considering the obvious correlation between them in different seasons are among the noteworthy results which are the outputs of the above-mentioned algorithms. The chief managers of organizations should use the Decision Support Systems (DSS) to make decisions in case of uncertainty. The results of the research help managers make decisions about achieving the ultimate organizational goal which is the satisfaction of people. Finding the root of the violations and determining the frequent seasons and months in which the violations are committed can be the cause of instructions and procedures which obligate contractors to precise implementation of regulations, decrease of committed violations and on the whole, improvement in Bus Company. It is a fact, attention to customer satisfaction as a significant and effective factor is essential for achieving stable and sustainable states in all production and industrial units and services firms such as research case study.

کلیدواژه‌ها [English]

  • Data mining
  • Decision Support systems
  • Association rules
  • Decision tree

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سابقه مقاله

  • تاریخ دریافت: 12 شهریور 1396
  • تاریخ بازنگری: 07 اسفند 1396
  • تاریخ پذیرش: 08 اسفند 1396

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