Experimental assessment and hybrid machine learning-based feature importance analysis with the optimization of compressive strength of waste glass powder-modified concrete

Materials Today Communications, Год журнала: 2025, Номер unknown, С. 112081 - 112081

Опубликована: Март 1, 2025

Язык: Английский

A survey and partial dependency analysis to assess residential solid waste recycling awareness in Saudi Arabia

Scientific Reports, Год журнала: 2025, Номер 15(1)

Опубликована: Март 7, 2025

Rapid industrialization, rise in population, and urbanization have led to severe environmental degradation health concerns for inhabitants due regular household waste (RHW). Implementing sustainable management practices, such as recycling, is an imminent need Saudi Arabia other nations. Yet, the analysis of awareness regarding RHW recycling its influencing elements Kingdom (KSA) has rarely been conducted. Efficient home currently a major concern, particularly economically developing countries, inappropriate disposal results financial losses detrimental effects on environment public health. The objective this study assess level among households RHW, issues associated with improper disposal, their readiness participate RHW. Therefore, we conducted two-stage analytic investigation that included total 909 from different areas Arabia. In addition questionnaire responses, partial dependency (PDP) was also using two supervised machine learning algorithms, Multi-Layer Perceptron (MLP) Decision Tree (DT), evaluate how sociodemographic factors influence awareness. Based results, most respondents are knowledgeable worried about adverse solid waste. Most motivated support large-scale program, provided enough facilities available. Also, PDP revealed age, gender, salary, marital status significantly impact recycling. Finally, considering rising amount produced by authorities must implement program address harmful promote development world.

Язык: Английский

AI-Driven greenhouse gas monitoring: enhancing accuracy, efficiency, and real-time emissions tracking

AIMS environmental science, Год журнала: 2025, Номер 12(3), С. 495 - 525

Опубликована: Янв. 1, 2025

Язык: Английский