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