Integrating life cycle assessment and machine learning to enhance black soldier fly larvae-based composting of kitchen waste

MY Arshad, S Saeed, A Raza, AS Ahmad… - Sustainability, 2023 - mdpi.com
Around 40% to 60% of municipal solid waste originates from kitchens, offering a valuable
resource for compost production. Traditional composting methods such as windrow, vermi …

Implementation of deep neural networks and statistical methods to predict the resilient modulus of soils

R Polo-Mendoza, J Duque, D Mašín… - … Journal of Pavement …, 2023 - Taylor & Francis
ABSTRACT The Resilient Modulus (Mr) is perhaps the most relevant and widely used
parameter to characterise the soil behaviour under repetitive loading for pavement …

Robust and comprehensive predictive models for methane hydrate formation condition in the presence of brines using black-box and white-box intelligent techniques

MR Nezhad, MA Moradkhani, B Bayati… - International Journal of …, 2024 - Elsevier
Accurate estimation of gas hydrate formation condition is crucial for many reasons. In one
hand, the gas hydrate formation is a promising approach for gas separation, cold energy …

Exploring Machine Learning Techniques for Accurate Prediction of Methane Hydrate Formation Temperature in Brine: A Comparative Study

W Aleem, S Ahmad, S Qamar, M Hussain, O Ali… - Arabian Journal for …, 2024 - Springer
Accurate estimation of formation conditions plays a pivotal role in effectively managing
various processes related to hydrates, including flow assurance, deep-water drilling, and …

Prediction of Formation Conditions of Gas Hydrates Using Machine Learning and Genetic Programming

A Kumari, M Madhaw, VS Pendyala - Machine Learning for Societal …, 2022 - igi-global.com
The formation of gas hydrates in the pipelines of oil, gas, chemical, and other industries has
been a significant problem for many years because the formation of gas hydrates may block …