This research study utilizes four machine learning techniques, ie, Multi Expression
programming (MEP), Artificial Neural Network (ANN), Adaptive Neuro-Fuzzy Inference …

Engineered cementitious composite (ECC) is a unique material, which can significantly
contribute to self-healing based on ongoing hydration. However, it is difficult to model and …

The incorporation of various modifiers such as rubber, plastic, fibers, and anti-stripping
agents has demonstrated favourable effects on the mechanical properties of bituminous …

Abstract Machine-learning (ML) methods often utilized in applications like computer vision,
recommendation systems, natural language processing (NLP), as well as user behavior …

This paper presents a study about a Machine Learning approach for modeling the stiffness
of different high-modulus asphalt concretes (HMAC) prepared in the laboratory with harder …

In this study a novel procedure is presented for an efficient development of predictive
models of road pavement asphalt concretes mechanical characteristics and volumetric …

Abstract Basalt Fiber Asphalt Concrete (BFAC) is an environmentally friendly and durable
material with potential road, bridge, and infrastructure construction applications. This study …

The conventional method for determining the Marshall Stability (MS) and Marshall Flow (MF)
of asphalt pavements entails laborious, time-consuming, and expensive laboratory …

This study addresses the challenge of designing hot-mix asphalt by evaluating the impact of
aggregate surface area (ASA) and the number of aggregates (NA) in machine learning (ML) …

This work aims to construct the physical-based machine learning (ML) approach for
estimating the hydrogen chloride (HCl) solubility in eleven different deep eutectic solvents …