استخراج قوانین از توصیف و مدل‌سازی آنها با استفاده از شبکه‌های پتری فازی رنگی

چاوشی, مینا; بابامیر, سید مرتضی

doi:10.22052/scj.2022.246562.1078

استخراج قوانین از توصیف و مدل‌سازی آنها با استفاده از شبکه‌های پتری فازی رنگی

نوع مقاله : مقاله پژوهشی

نویسندگان

گروه مهندسی نرم افزار، دانشکده برق و کامپیوتر، دانشگاه کاشان، کاشان، ایران

10.22052/scj.2022.246562.1078

چکیده

در این مقاله، قوانین حاکم بر رفتار سیستم از توصیف آن استخراج و سپس با شبکه پتری مدل‌سازی می‌شود. مجموعه این قوانین، پایگاه دانش سیستم را تشکیل می‌دهد که قابلیت استنتاج از آن را فراهم می‌آورد. هر قانون از تعدادی شرط و یک نتیجه تشکیل شده است. زمانی که تعداد قوانین زیاد و شرط‌ها در قوانین مختلف همپوشانی داشته باشند، می‌توان با استفاده از ساختار سلسله مراتبی به وسیله موتور استنتاج از تکرار شرط‌ها جلوگیری کرد و در نتیجه تعداد بررسی لازم برای رسیدن به نتیجه را کاهش داد. وقتی این قوانین دارای متغیرهای زیاد و فازی باشند، شکل پیچیده‌ای به خود می‌گیرند و درک و استنتاج رفتار آنها مشکل می‌شود. برای درک بهتر این پیچیدگی، مناسب است که آن ‌را با استفاده از شبکه‌های پتری‌ فازی بصری‌سازی کنیم. تاکنون روش‌های مختلف و متعددی مبتنی بر شبکه‌های پتری فازی برای مدل کردن قوانین فازی ارائه شده است، اما این روش‌ها یا تعداد قوانین و متغیرهای زیاد در سیستم را پشتیبانی نمی‌کنند یا مواردی مانند نقش گزاره‌های شرطی در وقوع گزاره‌های نتیجه، احتمالی بودن گزاره‌های نتیجه، مقدار آستانه برای گزاره‌های شرطی و نتیجه، ضریب قطعیت برای قانون یا برای گزاره‌های نتیجه را در نظر نمی‌گیرند. در این مقاله، با توسعه کار قبلی خود، مدلی مبتنی بر شبکه پتری فازی ارائه می‌دهیم که دو مورد بیان شده در بالا را پوشش می‌دهد و کاستی‌هایی که در توصیف مدل در کار قبلی ما وجود داشت را جبران می‌کند. در انتها، مدل پیشنهادی را برای یک سیستم تصفیه آب ایمن و حملات آن به کار می‌بریم.

کلیدواژه‌ها

عنوان مقاله [English]

Extracting Rules from Specifications and Their Modeling using Colored Fuzzy Petri-Nets

نویسندگان [English]

Mina Chavoshi
Seyed Morteza Babamir

Department of Software Engineering, Faculty of Electrical and Computer, University of Kashan, Kashan, Iran

چکیده [English]

In this paper, the rules governing the behavior of the system are extracted from the system specifications and then they are modeled by Petri-nets. The set of these rules forms the knowledge base of the system, which provides the ability of making inferences. Each rule consists of several premises and a conclusion. When there are many rules and the premises in different rules overlap, it is possible to prevent the repetition of premises using a hierarchical structure by the inference engine and thus reduce the number of checks required to reach the conclusion. When these rules have many and fuzzy variables, they take a complex form, and it becomes difficult to understand and deduce their behavior. To better understand this complexity, it is appropriate to visualize it using fuzzy petri-nets. So far, many different methods based on fuzzy Petri nets have been presented to model fuzzy rules. But these methods either do not support a large number of rules and variables or do not consider matters like the role of conditional propositions in the occurrence of the conclusion propositions, the probability of the conclusion propositions, the threshold value for the conditional propositions and the conclusions, the certainty factor for the rule or for the conditional propositions. In this paper, by extending our previous work, we present a model based on fuzzy Petri nets that covers the two mentioned cases. Finally, we present the proposed model for a secure water refinement system and the attacks against it.

کلیدواژه‌ها [English]

State transition table
Fuzzy Petri net
Fuzzy inference
Knowledge-based system

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