Analysis of input set characteristics and variances on k-fold cross validation for a Recurrent Neural Network model on waste disposal rate estimation

HL Vu, KTW Ng, A Richter, C An - Journal of environmental management, 2022 - Elsevier
The use of machine learning techniques in waste management studies is increasingly
popular. Recent literature suggests k-fold cross validation may reduce input dataset partition …

Machine learning and interactive GUI for concrete compressive strength prediction

MK Elshaarawy, MM Alsaadawi, AK Hamed - Scientific Reports, 2024 - nature.com
Concrete compressive strength (CS) is a crucial performance parameter in concrete
structure design. Reliable strength prediction reduces costs and time in design and prevents …

Novel wind speed forecasting model based on a deep learning combined strategy in urban energy systems

Y Hao, W Yang, K Yin - Expert Systems with Applications, 2023 - Elsevier
Effective wind speed forecasting has great significance for urban energy system operations
and the construction of low-carbon cities. However, most previous research has focused …

Toward improved prediction of recycled brick aggregate concrete compressive strength by designing ensemble machine learning models

MH Nguyen, SH Trinh, HB Ly - Construction and Building Materials, 2023 - Elsevier
The utilization of recycled brick aggregate concrete (RBC) is an area of active research, in
which further investigation is needed to develop accurate models for predicting the behavior …

The prediction analysis of compressive strength and electrical resistivity of environmentally friendly concrete incorporating natural zeolite using artificial neural network

AA Shahmansouri, M Yazdani, M Hosseini… - … and Building Materials, 2022 - Elsevier
To decrease the environmental and climatic effects of rising concrete consumption, more
environmentally friendly concretes are required. One approach to achieve this goal is using …

Earthquake effects on civil engineering structures and perspective mitigation solutions: a review

M Abbas, K Elbaz, SL Shen, J Chen - Arabian Journal of Geosciences, 2021 - Springer
Earthquakes are natural phenomena which cannot be controlled, but their effects can be
minimised. This study proposes a state-of-the-art review of the main effects of earthquakes …

[HTML][HTML] Reverse design for mixture proportions of recycled brick aggregate concrete using machine learning-based meta-heuristic algorithm: A multi-objective driven …

Y Wang, S Zhang, Z Zhang, Y Yu, J Xu - Journal of CO2 Utilization, 2024 - Elsevier
Abstract Construction and Demolition Wastes (CDW) have a significant impact on global
waste streams. Brick waste stands out as a prominent type of CDW, and numerous studies …

Mixed artificial intelligence models for compressive strength prediction and analysis of fly ash concrete

W Liang, W Yin, Y Zhong, Q Tao, K Li, Z Zhu… - … in Engineering Software, 2023 - Elsevier
The construction industry is facing challenges from the hazardous nature of Ordinary
Portland Cement (OPC) production as one of the main contributors to global warming and …

Metaheuristic‐based machine learning modeling of the compressive strength of concrete containing waste glass

MEA Ben Seghier, EM Golafshani… - Structural …, 2023 - Wiley Online Library
Waste glass (WG) can be used as fine aggregate and powder in concrete mixtures,
preventing pollution induced by this non‐biodegradable material. The properties of WG …

Prediction model and measurement of fracture parameters in eco-friendly coarse copper slag-SFRSCC based on semi-circular bending test

I Afshoon, M Miri, SR Mousavi - Construction and Building Materials, 2023 - Elsevier
This research has used 16 concrete mix designs containing 0.1, 0.3, and 0.5% steel fiber
(SF), and 20, 30, 40, 50, and 60% copper slag (CS) to examine their fresh and hardened …