Development of advanced artificial intelligence models for daily rainfall prediction

BT Pham, LM Le, TT Le, KTT Bui, VM Le, HB Ly… - Atmospheric …, 2020 - Elsevier
In this study, the main objective is to develop and compare several advanced Artificial
Intelligent (AI) models namely Adaptive Network based Fuzzy Inference System optimized …

A sensitivity and robustness analysis of GPR and ANN for high-performance concrete compressive strength prediction using a Monte Carlo simulation

DV Dao, H Adeli, HB Ly, LM Le, VM Le, TT Le… - Sustainability, 2020 - mdpi.com
This study aims to analyze the sensitivity and robustness of two Artificial Intelligence (AI)
techniques, namely Gaussian Process Regression (GPR) with five different kernels …

Predictive modelling of sustainable lightweight foamed concrete using machine learning novel approach

HS Ullah, RA Khushnood, J Ahmad, F Farooq - Journal of Building …, 2022 - Elsevier
Foamed concrete is a versatile material that can be used in different construction
applications and with proper mix designing, it can also be used as a structural member. The …

Optimization of artificial intelligence system by evolutionary algorithm for prediction of axial capacity of rectangular concrete filled steel tubes under compression

HQ Nguyen, HB Ly, VQ Tran, TA Nguyen, TT Le… - Materials, 2020 - mdpi.com
Concrete filled steel tubes (CFSTs) show advantageous applications in the field of
construction, especially for a high axial load capacity. The challenge in using such structure …

Prediction of pile axial bearing capacity using artificial neural network and random forest

TA Pham, HB Ly, VQ Tran, LV Giap, HLT Vu… - Applied Sciences, 2020 - mdpi.com
Axial bearing capacity of piles is the most important parameter in pile foundation design. In
this paper, artificial neural network (ANN) and random forest (RF) algorithms were utilized to …

[HTML][HTML] Field based index of flood vulnerability (IFV): A new validation technique for flood susceptible models

S Mahato, S Pal, S Talukdar, TK Saha, P Mandal - Geoscience Frontiers, 2021 - Elsevier
The flood hazard management is one of the major challenges in the floodplain regions
worldwide. With the rise in population growth and the spread of infrastructural development …

Development of an AI model to measure traffic air pollution from multisensor and weather data

HB Ly, LM Le, LV Phi, VH Phan, VQ Tran, BT Pham… - Sensors, 2019 - mdpi.com
Gas multisensor devices offer an effective approach to monitor air pollution, which has
become a pandemic in many cities, especially because of transport emissions. To be …

Investigation and optimization of the C-ANN structure in predicting the compressive strength of foamed concrete

DV Dao, HB Ly, HLT Vu, TT Le, BT Pham - Materials, 2020 - mdpi.com
Development of Foamed Concrete (FC) and incessant increases in fabrication technology
have paved the way for many promising civil engineering applications. Nevertheless, the …

Computational hybrid machine learning based prediction of shear capacity for steel fiber reinforced concrete beams

HB Ly, TT Le, HLT Vu, VQ Tran, LM Le, BT Pham - Sustainability, 2020 - mdpi.com
Understanding shear behavior is crucial for the design of reinforced concrete beams and
sustainability in construction and civil engineering. Although numerous studies have been …

Adaptive network based fuzzy inference system with meta-heuristic optimizations for international roughness index prediction

HL Nguyen, BT Pham, LH Son, NT Thang, HB Ly… - Applied Sciences, 2019 - mdpi.com
The International Roughness Index (IRI) is the one of the most important roughness indexes
to quantify road surface roughness. In this paper, we propose a new hybrid approach …