Geographical perspectives on home-based enterprises in urban nigeria: economic growth and environmental impacts

GeoJournal, Год журнала: 2025, Номер 90(1)

Опубликована: Янв. 29, 2025

Язык: Английский

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Leak detection and localization in water distribution systems using advanced feature analysis and an Artificial Neural Network

Desalination and Water Treatment, Год журнала: 2024, Номер 320, С. 100685 - 100685

Опубликована: Авг. 3, 2024

This study capitalizes on a dataset, originally including 280 sensory measurements from laboratory-scale water distribution system, to advance the concept of leakage diagnosis and localization. The test rig are formulated in two configurations, namely looped branched layouts. paper processed time-domain data accelerometers dynamic pressure sensors into advanced statistical features of: Autocorrelation Coefficient (Au-C), Signal Energy (Sig-E), detect localize leakage. By Employment these features, research developed an expert system Artificial Neural Network (ANN) model designed with optimal parameters, neurons, hidden layers classify presence pinpoint location leaks within rig. effectiveness current approach is quantitatively evaluated using F1-scores accuracy metrics. A robust capability for both detecting localizing under varying conditions was established highest F1-score 86.5 % 86.2 %, respectively. findings underscore potential integrating Intelligence (AI) enhancing reliability dependability management systems. contributes broader application AI managing resources infrastructure resilience its support improve whereabouts.

Язык: Английский

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Optimizing water resources for sustainable desalination: The integration of expert systems and solar energy in experimental applications

Desalination and Water Treatment, Год журнала: 2024, Номер 320, С. 100683 - 100683

Опубликована: Авг. 3, 2024

The integration of renewable energy sources with multi-energy systems present challenges and opportunities to enhance sustainability. Among these, solar stills have emerged as a solution for water desalination. With the advent expert system technologies, avenues are opened improving operational efficiency distillers. This paper presents an innovative approach utilizing correlation analysis, ReliefF feature selection, k-Nearest Neighbor (kNN) algorithm forecasting cumulative distillate output double slope still. analysis is based on 6-cases-based dataset, which includes variations in relative different operational-environmental conditions. Key features that significantly impact overall performance were identified manage distiller productivity. findings reveal maximum was 1610 ML/m2.day due incorporating reflective materials phase change (PCM) enhancing distillation rates. kNN model evaluated its R2, RMSE, CVRMSE, best models achieving scores 0.995, 0.0033, 0.1666, respectively. These metrics underscore effectiveness proposed machine learning predicting output, thereby enabling informed management processes. Combining technologies computational intelligence holds significant promise sustainable environmental management, study presented.

Язык: Английский

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A Data Fusion Analysis and Random Forest Learning for Enhanced Control and Failure Diagnosis in Rotating Machinery

Journal of Failure Analysis and Prevention, Год журнала: 2024, Номер unknown

Опубликована: Ноя. 15, 2024

Язык: Английский

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Machine Learning-Based Medium-Term Power Forecasting of a Grid-Tied Photovoltaic Plant

Smart Grid and Renewable Energy, Год журнала: 2024, Номер 15(12), С. 289 - 306

Опубликована: Янв. 1, 2024

Язык: Английский

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Advancing sustainable renewable energy: XGBoost algorithm for the prediction of water yield in hemispherical solar stills

Discover Sustainability, Год журнала: 2024, Номер 5(1)

Опубликована: Дек. 21, 2024

Язык: Английский

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