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1441
Formative research to optimize pre-eclampsia risk-screening and prevention (PEARLS): study protocol
Published 2025-03-01“…By identifying factors that can influence implementation of pre-eclampsia prevention and care pathways, the findings will inform successful execution of the PEARLS trial, and post-research scale-up activities. This, in turn, can help reduce the prevalence of pre-eclampsia, and improve maternal and newborn outcomes in high-burden settings. …”
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1442
DDPG-Based UAV-RIS Framework for Optimizing Mobility in Future Wireless Communication Networks
Published 2025-06-01Get full text
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1443
An Intelligent Optimization System Using Neural Networks and Soft Computing for the FMM Etching Process
Published 2025-06-01“…Experimental results demonstrate a marked improvement in product yield and process stability while reducing manufacturing costs. …”
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1444
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1445
Underwater Acoustic Signal Prediction Based on MVMD and Optimized Kernel Extreme Learning Machine
Published 2020-01-01Get full text
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1446
Optimizing Q-Learning for Automated Cavity Filter Tuning: Leveraging PCA and Neural Networks
Published 2025-01-01“…Additionally, while intelligent algorithms can assist in tuning, they often require large volumes of simulated data, leading to high computational costs. …”
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1447
Multi-Objective Optimization of Machinability and Energy Consumption of Cast Iron Depending on Cooling Rate
Published 2025-01-01“…Energy efficiency has become a critical focus in sustainable production techniques and cost-effective machining processes. This variation directly influences machinability, with higher hardness generally improving surface quality. …”
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1448
Conditional distributionally robust dispatch for integrated transmission-distribution systems via distributed optimization
Published 2025-05-01“…Also, the distributed algorithm reduces solution time and scales well under various ITDSs.…”
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1449
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1450
A Comparative Analysis of Hyper-Parameter Optimization Methods for Predicting Heart Failure Outcomes
Published 2025-03-01“…We evaluated three optimization approaches—Grid Search (GS), Random Search (RS), and Bayesian Search (BS)—across three machine learning algorithms—Support Vector Machine (SVM), Random Forest (RF), and eXtreme Gradient Boosting (XGBoost). …”
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1451
Integrated Time Series Analysis, Clustering, and Forecasting for Energy Efficiency Optimization and Tariff Management
Published 2025-01-01“…The research demonstrated that energy costs for the analyzed public units could be reduced by approximately 2.7 million reais. …”
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1452
Design and optimization of distributed energy management system based on edge computing and machine learning
Published 2025-02-01“…Future research can further explore how to integrate multiple machine learning algorithms to optimize energy scheduling strategies and improve the system’s adaptability in complex environments.…”
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1453
Modeling and optimization of culture media for recombinant Helicobacter pylori vaccine antigen HpaA
Published 2024-12-01“…The H. pylori adhesin protein HpaA has demonstrated strong immunogenicity across various adjuvants and dosage forms, positioning it as a key candidate antigen for recombinant subunit vaccines against H. pylori. Optimizing fermentation culture conditions is an effective strategy to enhance product yield and lower production costs. …”
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1454
ADMET evaluation in drug discovery: 21. Application and industrial validation of machine learning algorithms for Caco-2 permeability prediction
Published 2025-01-01“…We believe that the model developed in this study could represent a reliable tool for assessing Caco-2 permeability during early-stage drug discovery and the chemical transformation rules derived here could provide insights for optimizing Caco-2 permeability. Scientific contribution A comprehensive validation of various machine learning algorithms combined with diverse molecular representations on a large dataset for predicting Caco-2 permeability was reported. …”
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1455
An intelligent stochastic optimization approach for air cargo order allocation under carbon emission constraints.
Published 2025-01-01“…The method finds the optimal solution through an improved adaptive large-scale neighborhood search algorithm and uses a scenario generation technique to generate the scenarios required for evaluating candidate solutions to the high-dimensional stochastic optimization problem. …”
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1456
Multi‐objective multi‐period optimal site and size of distributed generation along with network reconfiguration
Published 2024-12-01“…To address the pointed‐out challenge of multiperiod optimal DG allocation and reconfiguration while simultaneously decreasing the cost of energy supplied, the cost of energy lost, and the voltage deviation, a novel Multi‐objective Bidirectional co‐evolutionary algorithm (BiCo) is implemented. …”
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1457
Application of artificial intelligence and red-tailed hawk optimization for boosting biohydrogen production from microalgae
Published 2024-11-01“…Subsequently, the red-tailed hawk algorithm (RTH) is used to determine the optimal values for the process parameters, corresponding to maximum hydrogen yield. …”
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1458
A Clustering-Guided Integer Brain Storm Optimizer for Feature Selection in High-Dimensional Data
Published 2021-01-01“…Since the number of feature clusters is far smaller than the size of original features, IBSO-C can find an optimal feature subset fast. Compared with several existing algorithms on some real-world datasets, experimental results show that IBSO-C can find feature subset with high classification accuracy at less computation cost.…”
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1459
Dynamic Optimization of Bus Line Schedule in Commuter Corridor Based on Bus IC Card Data
Published 2022-01-01“…To solve the model, a dynamic departure interval optimization method based on improved Genetic Algorithm (GA) was designed under different decision preferences. …”
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1460
UV-Vis spectroscopy coupled with firefly algorithm-enhanced artificial neural networks for the determination of propranolol, rosuvastatin, and valsartan in ternary mixtures
Published 2025-03-01“…An experimental design of 25 samples was employed as a calibration set, and a central composite design of 20 samples was used as a validation set. The firefly algorithm (FA) was evaluated as a variable selection procedure to optimize the developed ANN models resulting in simpler models with improved predictive performance as evident by lower relative root mean square error of prediction (RRMSEP) values compared to the full spectrum ANN models. …”
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