(untitled) (International Journal of Engineering and Computer Science, 2017)
The development of highway at Kurdistan in Iraq, requirement of road users is increasing. The key problem is to design the asphalt pavement construction to ensure pavement performance. Evaluation of asphalt pavement performance is very important method it concerned with quantitative and uncertain information. Fuzzy Petri net (FPN), as one type of high level Petri net, has shown a lot of attention recently due to its sufficiency, for knowledge representation and logic reasoning. In this paper we present an intuitive approach of FPN model for asphalt pavement performance evaluation. The model is based on the theory of FPNs is used to describe a formal model of knowledge representation for vague information of asphalt pavement (i.e. rut depth).The proposed approach is to bring asphalt pavement performance evaluation within the powerful modeling method of FPN tools. The input values in our model the surface thickness (ST), traffic count (TC) and age (A) can be formulated as uncertain fuzzy tokens to determine the rut depth values at time instance (t+1). The FPN components and functions consist of some types of fuzzy operators AND operator (MIN) and OR operator (MAX) of If-parts and Then-parts in fuzzy rules.