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581
Optimizing Natural Image Quality Evaluators for Quality Measurement in CT Scan Denoising
Published 2025-01-01Get full text
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582
Improved energy efficiency using meta-heuristic approach for energy harvesting enabled IoT network
Published 2023-03-01“…In this article, we propose an optimization algorithm, based on meta-heuristic, to enhance the energy efficiency of amplify and forward relay IoT networks. …”
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583
K-Means Clustering Algorithm Measuring the Satisfaction Level of MNC TV Muslim I'murojaah Program Viewers
Published 2025-07-01“…Recommendations for program improvement include enhancing image and sound quality, ensuring that the equipment and technology used can produce optimal quality. …”
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584
What Influences Low-cost Sensor Data Calibration? - A Systematic Assessment of Algorithms, Duration, and Predictor Selection
Published 2022-06-01“…Many studies have employed field calibration to improve sensor agreement with co-located reference monitors. …”
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585
An experimental optimization environment for developing an intracycle pitch control in cross flow turbines
Published 2025-06-01“… Cross-flow tidal turbines have not reached the efficiency of horizontal-axis turbines. Among various improvement approaches found in the literature, the intracycle pitch control is one of the most promising ones. …”
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586
Fault Diagnosis System of Induction Motors Based on Neural Network and Genetic Algorithm Using Stator Current Signals
Published 2006-01-01“…GA is used to select the most significant features from the whole feature database and optimize the ANN structure parameter. …”
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587
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588
Reliability evaluation of dynamic face recognition systems based on improved Fuzzy Dynamic Bayesian Network
Published 2020-03-01“…In this article, we propose a novel evaluation method with True Positive Identification Rate in dynamic and M:N mode and create a novel evaluation model of system reliability with the improved Fuzzy Dynamic Bayesian Network. Subsequently, we infer to solve the fuzzy reliability state probabilities of the six systems with Netica and get two most important factors with the improved fuzzy C-means algorithm. …”
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589
Brown bear optimized random forest model for short term solar power forecasting
Published 2025-03-01“…The results obtained are compared with hyperparameter tuning using particle swarm optimization (PSO) and firefly algorithm (FA). MSE obtained using BBOA is improved by 2.7 % and 3.7 % when compared with PSO and FA respectively. …”
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590
Dual Strategy of Reconfiguration with Capacitor Placement for Improvement Reliability and Power Quality in Distribution System
Published 2023-01-01“…These scenarios were tested on typical 33 and 69 bus IEEE RDS using the binary salp swarm algorithm (BSSA) based on the multiobjective functions (MOFs), in order to identify the most effective scenario performance that achieved the highest power quality and system reliability. …”
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591
The Study of Roadside Visual Perception in Internet of Vehicles Based on Improved YOLOv5 and CombineSORT
Published 2025-01-01“…It indicates that most algorithms can achieve good detection results when the targets are sparse, and the lightweight models may have more advantages with considering the demand of computing resources. …”
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592
An optimal weighting-based hybrid classifier for Children's congenital heart diseases signal processing
Published 2025-09-01“…In this paper, a hybrid classifier incorporating Long Short-Term Memory (LSTM), Support Vector Machine (SVM), and Convolutional Neural Network (CNN) is proposed and applied to diagnose congenital heart disease in children. The most distinguishing feature of the proposed hybrid classifier compared to existing ones is its optimal weighting algorithm. …”
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593
Improvement of the Diagnostics of the Fetus Heart Anomalies During a Routine Screening Ultrasound Examination
Published 2014-09-01“…So, the study of fetal heart is one of the most important stages of screening ultrasound in the second trimester of pregnancy.…”
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594
ZZ-YOLOv11: A Lightweight Vehicle Detection Model Based on Improved YOLOv11
Published 2025-05-01“…Aiming at the problems of insufficient vehicle detection accuracy, high misdetection and omission rate, and heavy model computational burden caused by complex lighting conditions, target occlusion, and other factors in urban traffic scenarios, this paper proposes an improved lightweight detection network, ZZ-YOLO. Firstly, the current mainstream target detection algorithms lack components to improve the network’s focus on the edges of the objects, which can indirectly lead to unclear classification and localization. …”
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595
Enhancing Energy Efficiency in IoT-WSNs Through Optimized PSO Cluster Head Selection
Published 2025-01-01“…In IoT-based wireless sensor networks (WSNs), clustering is one of the most effective energy-saving approaches for optimizing the life cycle of networks. …”
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596
Prediction and dynamic optimization of drilling performance based on the combination of mineral composition and operational factors
Published 2025-06-01“…According to the training and testing results, the introduction of mineral composition can effectively improve the training speed and testing accuracy. Through the established prediction function, a dynamic optimization algorithm combined with DOE (Design of Experiments) theory was also developed. …”
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597
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598
Ensemble Learning-Based Wine Quality Prediction Using Optimized Feature Selection and XGBoost
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599
Conditional distributionally robust dispatch for integrated transmission-distribution systems via distributed optimization
Published 2025-05-01“…This paper closes this gap by proposing a conditional distributionally robust optimization (DRO) method for ITDSs. Specifically, a novel ambiguity set is built by exploiting the dependence of the wind power forecast error on its forecast value, which differs from most of the existing ones. …”
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600
Interpretable prediction model for hand-foot-and-mouth disease incidence based on improved LSTM and XGBoost
Published 2025-07-01“…In order to address the issues of low accuracy and poor interpretability in existing HFMD incidence prediction models, in this paper, we propose an interpretable prediction model, namely, ARIMA–LSTM–XGBoost, which integrates multiple meteorological factors with Autoregressive integrated moving average model (ARIMA), Long short-term memory (LSTM), Extreme gradient boosting (XGBoost), Grey wolf optimizer (GWO), Genetic algorithm (GA) and Shapley additive explanations (SHAP). …”
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