Objectives Machine learning (ML)–based emulators improve the calibration of decision-
analytical models, but their performance in complex microsimulation models is yet to be …

Metaheuristic algorithms are computational intelligence paradigms especially used for
solving different optimization issues. Metaheuristics examine a collection of solutions …

A DC motor widely uses for sensitive speed and position in industry. Stability and
productivity of a system are important for controlling of a DC motor speed. Stable of speed …

Calibration is an essential prerequisite to scenario evaluations using traffic micro-simulation
models (TMMs). In the context of mixed-traffic operations, where different fast and slow …

Examining driving behaviour is crucial for traffic operations because of its influence on driver
safety and the potential for increased risk of accidents, injuries, and fatalities. Approximately …

Left-turning vehicle movement at signalized intersections with permissive left-turn phases
creates safety concerns due to the higher chance of conflict with opposing-through vehicles …

We investigate differential evolution optimization to fit Rutherford backscattering data. The
algorithm helps to find, with very high precision, the sample composition profile that best fits …

When performing microscopic traffic simulations, a premise is to have appropriately
calibrated parameter values. This is often computationally expensive as it requires …

Unsignalized intersections in most of the developing countries do not have stringent traffic
regulations causing frequent priority rule violations. Moreover, roads in such countries carry …

Heterogeneous traffic conditions are characterized by a mix of vehicles with varying static
and dynamic characteristics. Modelling of such traffic conditions is a challenging task due to …