In the structure of ANFIS, there are two different parameter groups: premise and
consequence. Training ANFIS means determination of these parameters using an …

Introduction Due to the menacing increase in the number of vehicles on a daily basis,
abating road congestion is becoming a key challenge these years. To cope-up with the …

Recently, the intelligent traffic control system and its uncertainty analysis are considered one
of the hot spots for utilizing the available techniques. It became more essential when the …

We consider an analytical signal control problem on a signalized network whose traffic flow
dynamic is described by the Lighthill–Whitham–Richards (LWR) model (Lighthill and …

This paper capitalizes on the increasingly high relevance gained by data-intensive
technologies in the development of intelligent transportation system, which calls for the …

Controlling traffic dynamically is a complex task which includes meeting the increasing traffic
demand and decreasing delays at the intersection. The current traffic controllers based on …

In this paper, a novel method for the design of flexible pavements is elaborated. The method
is based on fuzzy inference system with genetic algorithm (GA) aided optimized rule base …

In this investigation, differential evolution (DE) algorithm with the fuzzy inference system
(FIS) are combined and the DE algorithm is employed in FIS training process. Considered …

Increased traffic in metropolitan territories has led to significant concerns, such as road
blockage, transportation delays, pollution level, fuel consumption, etc. Traffic light signals at …

Reasonable setting of traffic signals can be very helpful in alleviating congestion in urban
traffic networks. Meta-heuristic optimization algorithms have proved themselves to be able to …