Optimization of ultrasound-assisted extraction of bioactive compounds from Carthamus caeruleus L. rhizome: Integrating central composite design, Gaussian process regression, and multi-objective Grey Wolf optimization approaches

Process Biochemistry, Journal Year: 2024, Volume and Issue: 147, P. 476 - 488

Published: Oct. 23, 2024

Language: Английский

---

Harnessing Deep Learning for Real-Time Water Quality Assessment: A Sustainable Solution

Water, Journal Year: 2024, Volume and Issue: 16(23), P. 3380 - 3380

Published: Nov. 24, 2024

This study presents an innovative approach utilizing artificial intelligence (AI) for the prediction and classification of water quality parameters based on physico-chemical measurements. The primary objective was to enhance accuracy, speed, accessibility monitoring. Data collected from various samples in Algeria were analyzed determine key such as conductivity, turbidity, pH, total dissolved solids (TDS). These measurements integrated into deep neural networks (DNNs) predict indices sodium adsorption ratio (SAR), magnesium hazard (MH), percentage (SP), Kelley’s (KR), potential salinity (PS), exchangeable (ESP), well Water Quality Index (WQI) Irrigation (IWQI). DNNs model, optimized through selection activation functions hidden layers, demonstrated high precision, with a correlation coefficient (R) 0.9994 low root mean square error (RMSE) 0.0020. AI-driven methodology significantly reduces reliance traditional laboratory analyses, offering real-time assessments that are adaptable local conditions environmentally sustainable. provides practical solution resource managers, particularly resource-limited regions, efficiently monitor make informed decisions public health agricultural applications.

Language: Английский

---

Advanced green peel utilization for efficient methylene blue removal: Integrated analysis and predictive modeling

Journal of Molecular Liquids, Journal Year: 2024, Volume and Issue: 413, P. 125951 - 125951

Published: Sept. 12, 2024

Language: Английский

---

Preparation of activated carbon from Ziziphus jujuba stones by H3PO4-assisted thermo-chemical activation: application in the removal of anionic diazo dye from synthetic water

Biomass Conversion and Biorefinery, Journal Year: 2025, Volume and Issue: unknown

Published: March 13, 2025

Language: Английский

---

Simulating the Deterioration Behavior of Tunnel Elements Using Amalgamation of Regression Trees and State-of-the-Art Metaheuristics

Mathematics, Journal Year: 2025, Volume and Issue: 13(7), P. 1021 - 1021

Published: March 21, 2025

Tunnel infrastructures worldwide face escalating deterioration challenges due to aging materials, increasing load demands, and exposure harsh environmental conditions. Accurately predicting the onset progression of is paramount for ensuring structural safety, optimizing maintenance interventions, prolonging service life. However, complex interplay environmental, material, operational factors poses significant current predictive models. Additionally, they are constrained by small datasets a narrow range tunnel elements that limit their generalizability. This paper presents novel hybrid metaheuristic-based regression tree (REGT) model designed enhance accuracy robustness predictions. Leveraging metaheuristic algorithms’ strengths, developed method jointly optimizes critical hyperparameters identifies most relevant features prediction. A comprehensive dataset encompassing material properties, stressors, traffic loads, historical condition assessments was compiled development. Comparative analyses against conventional trees, artificial neural networks, support vector machines demonstrated consistently outperformed baseline techniques regarding While trees classic machine learning models, no single variant dominated all elements. Furthermore, optimization framework mitigated overfitting provided interpretable insights into primary driving deterioration. Finally, findings this research highlight potential models as powerful tools infrastructure management, offering actionable predictions enable proactive strategies resource optimization. study contributes advancing field modeling in civil engineering, with implications sustainable management infrastructure.

Language: Английский

---

Approximation of Oxygen Transfer Efficiency of Solid Jet Aerator Having Circular Opening with Kernel Function-Based Models and Random Forest Models

Iranian Journal of Science and Technology Transactions of Civil Engineering, Journal Year: 2025, Volume and Issue: unknown

Published: April 15, 2025

Language: Английский

---