Exploring the potential of bacterial concrete: A sustainable solution for remediation of crack and durability enhancement–A critical review

S Rajadesingu, KC Mendonce, N Palani… - … and Building Materials, 2024 - Elsevier
The investigation of durable and sustainable construction materials has encouraged
significant advancements in concrete technology, one such notable innovation is integration …

Daily scale air quality index forecasting using bidirectional recurrent neural networks: Case study of Delhi, India

CB Pande, NL Kushwaha, OA Alawi, SS Sammen… - Environmental …, 2024 - Elsevier
This research was established to accurately forecast daily scale air quality index (AQI) which
is an essential environmental index for decision-making. Researchers have projected …

Multi-objective optimization and performance assessment of response surface methodology (RSM), artificial neural network (ANN) and adaptive neuro-fuzzy …

R Jradi, C Marvillet, MR Jeday - Applied Thermal Engineering, 2024 - Elsevier
Fouling is a common occurrence in industrial heat exchangers, leading to a decrease of the
thermal efficiency. This research addresses the challenge of applying various machine …

[HTML][HTML] Computing models to predict the compressive strength of engineered cementitious composites (ECC) at various mix proportions

K Ghafor, HU Ahmed, RH Faraj, AS Mohammed… - Sustainability, 2022 - mdpi.com
Concrete has relatively high compressive strength (resists breaking when squeezed) but
significantly lower tensile strength (vulnerable to breaking when pulled apart). The …

Systematic literature review on the application of machine learning for the prediction of properties of different types of concrete

SI Hassan, SA Syed, SW Ali, H Zahid, S Tariq… - PeerJ Computer …, 2024 - peerj.com
Background Concrete, a fundamental construction material, stands as a significant
consumer of virgin resources, including sand, gravel, crushed stone, and fresh water. It …

Develo** an ensembled machine learning model for predicting water quality index in Johor River Basin

LM Sidek, HA Mohiyaden, M Marufuzzaman… - Environmental Sciences …, 2024 - Springer
Abstract Currently, the Water Quality Index (WQI) model becomes a widely used tool to
evaluate surface water quality for agriculture, domestic and industrial. WQI is one of the …

Rainfall modeling using two different neural networks improved by metaheuristic algorithms

SS Sammen, O Kisi, M Ehteram, A El-Shafie… - Environmental Sciences …, 2023 - Springer
Rainfall is crucial for the development and management of water resources. Six hybrid soft
computing models, including multilayer perceptron (MLP)–Henry gas solubility optimization …

Predictive modelling of nitrogen dioxide using soft computing techniques in the Agra, Uttar Pradesh, India

P Sihag, T Mehta, SS Sammen, CB Pande… - … of the Earth, Parts A/B/C, 2024 - Elsevier
Nitrogen dioxide (NO 2) is one of the air pollutants which aggravates the human health as
well as causes environmental issues. It is more causes respiratory problems due to acid …

Modeling the compressive strength of eco-friendly self-compacting concrete incorporating ground granulated blast furnace slag using soft computing techniques

RH Faraj, AA Mohammed, KM Omer - Environmental Science and …, 2022 - Springer
Concern regarding global climate change and its detrimental effects on society demands the
building sector, one of the major contributors to global warming. Reducing cement usage is …

[HTML][HTML] Comparative analysis of machine learning algorithms for water quality prediction

M Akhlaq, A Ellahi, R Niaz, M Khan… - Tellus A: Dynamic …, 2024 - a.tellusjournals.se
This study aims to identify the influential parameters and heavy metals in water and assess
the water quality classification at the Alpine glacial lakes and rivers in three districts of …