Inefficiencies in the management of earthmoving equipment greatly contribute to the
productivity gap of infrastructure projects. This paper develops and tests a Deep Neural …

Its significant influence on overall progress makes excavator productivity a major concern of
construction project managers, particularly during initial-stage earthwork activities. The …

A neural-network (NN) and observation-data-based approach to estimating construction
operation productivity is presented. The main reason for using neural networks for …

Many construction processes are carried out by machines working together and forming
technological systems, eg earthmoving machinery made up of excavators and haulers …

Heavy equipment represents a major cost element and a critical resource in large
infrastructure projects. Automating the measurement of its productivity is important to remove …

Estimating equipment production rates is both an art and a science. An accurate prediction
of the productivity of earthmoving equipment is critical for accurate construction planning …

The productivity estimation of construction machinery is a significant challenge faced by
many earthmoving contractors. Traditionally, contractors have used manufacturers' …

This paper aims to develop a quantitative model for predicting the productivity of excavators
using artificial neural networks (ANN), which is then compared with the multiple regression …

Many constructional processes are carried out by machines working together and forming
technological systems. An example here can be an earthmoving machinery set made up of …

Increased safety risks and the difficulties of training excavator operators, combined with
manpower shortages, have led to an increased demand for machine automation. This study …