Explanation and Optimizing Multi‐Model Blending Algorithm Using Random Variables Theory by Yu Wang, Yong Cao, Yue Shen, Ruixia Zhao, Xiaoqing Zeng, Li Yao, Kan Dai

“…This improvement may be attributed to modeling the actual forecast error as a normally distributed unified parameter and applying a consistent correlation coefficient across the annual data set.…”
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Approximation Algorithms for Maximum Link Scheduling under SINR-Based Interference Model by Zi-Ao Zhou, Chang-Geng Li

“…To date, several approximation algorithms have been proposed to solve MLS under the SINR-based interference model. …”
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Research on an internal model control algorithm and parameter tuning for metro traction PMSMs by SI Junmin, YUE Xuelei, TIAN Di, XU Kelei

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Construction of prognostic scoring model for ovarian cancer based on deep learning algorithm by Xiaolin Zhong, Hongyang Xiao, Weihong Lu, Jiayuan Chen, Fan Chao, Ruiqin Tu

“…Accurate prognostic prediction and timely treatment are critical for improving patient outcomes. The aim of this study was to develop a prognostic prediction model for ovarian cancer based on pathological images. 158 In-house and 105 TCGA-OV pathological slides were processed with Macenko’s algorithm for stain normalization and patch extraction (256 × 256 pixels). …”
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Modeling and Optimization of Concrete Mixtures Using Machine Learning Estimators and Genetic Algorithms by Ana I. Oviedo, Jorge M. Londoño, John F. Vargas, Carolina Zuluaga, Ana Gómez

“…This study presents a methodology to optimize concrete mixtures by integrating machine learning (ML) and genetic algorithms. ML models are used to predict compressive strength, while genetic algorithms optimize the mixture cost under quality constraints. …”
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Fine-Pruning: A biologically inspired algorithm for personalization of machine learning models by Joseph Bingham, Saman Zonouz, Dvir Aran

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Carbon emission forecasting in Zhejiang Province based on LASSO algorithm and grey model by HONG Jingke, DU Wei, SHAO Jin*, LAO Huimin

“…In light of these findings, It is recommended that Zhejiang Province should focus on optimizing its industrial structure, improving energy efficiency, increasing investment in low-carbon research and development, and steadily advancing the goal of "carbon peaking" .…”
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Long tunnel group driving fatigue detection model based on XGBoost algorithm by Huazhi Yuan, Kun Zhao, Ying Yan, Li Wan, Zhending Tian, Xinqiang Chen

“…In addition, a significant correlation exists between the driving duration index and driving fatigue, which can provide a reference for improving the tunnel safety. Using the mean value of blink duration and driving duration as the characteristic indexes, the accuracy of the driving fatigue detection model based on the XGBoost algorithm reaches 98%. …”
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CKRT coagulation risk prediction and nursing feedback model based on intelligent algorithms by Xianrong Xu, Mou Chen, Lvjing Chen, Kaixing Huang, Shiqi Cao, Wenwen Gao, Kang Liu, Buyun Wu, Huijuan Mao

“…Conclusion The intelligent Continuous Kidney Replacement Therapy nursing feedback model improves prediction accuracy while reducing redundant information. …”
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Improving distributed systems failure prediction via multi-objective feature selection and deep forest by Zhidan Yuan, Yikai Zhang, Yingqi Yu, Taizhi Lv, Tao Huang

“…Compared to nine classical models, the Accuracy improvement ranges from 1.1% to 97.9%, while the Macro−F1 improvement ranges from 1.1% to 179.4%. …”
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Crop-Free-Ridge Navigation Line Recognition Based on the Lightweight Structure Improvement of YOLOv8 by Runyi Lv, Jianping Hu, Tengfei Zhang, Xinxin Chen, Wei Liu

“…The results showed that the average precision of the improved neural network model using this method was 90.4%, with a Params of 1.8 M, a FLOPs of 8.8 G, and an FPS of 49.5. …”
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Improving energy efficiency for intelligent reflecting surface assisted PD-NOMA in EH relaying network by Hong Nguyen-Thi, Thuc Kieu-Xuan, Thang Le-Nhat, Anh Le-Thi

“…To determine the efficiency of PSO, we consider two other techniques: Genetic Algorithm (GA) and Exhaustive Search (ES). Finally, we evaluate the proposed model's performance in different scenarios, such as the number of IRS elements and the number of relay nodes, the relaying selection strategies, and the transmit power at the BS. …”
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Improving air quality prediction using hybrid BPSO with BWAO for feature selection and hyperparameters optimization by Mohamed S. Sawah, Hela Elmannai, Alaa A. El-Bary, Kh. Lotfy, Osama E. Sheta

“…The study concludes that feature selection and hyperparameter optimization significantly improve model accuracy and computational efficiency, offering a robust framework for air quality forecasting.…”
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Theoretical Proposals for Improving the Noise Immunity of Receiving Multi-Position Signals in Channels with Variable Parameters by S. V. Dvornikov, A. V. Pshenichnikov, A. F. Kryachko, M. R. Bibarsov, G. S. Bibarsova

“…This, in turn, enables analysis of the effect of phase distortions in channels with variable parameters on the error probability of receiving QAM signal elements.Results. A transformed SS model with improved energy characteristics and an analytical relation for calculating the error probability of receiving QAM signal elements are proposed. …”
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Research on Stacking Distribution of Steel Plates Input Based on Improved Multi-objective Particle Swarm Optimization by ZHONG Chuanjie, CHENG Wenming, DU Run, GAO Xuchao, ZHANG Lin

“…Compared to the traditional stacking method used before optimization, the optimized stacking distribution scheme improved by 19.35%, 4.97%, and 62.23% under the three objectives, respectively, indicating a more significant optimization effect.ConclusionsBased on the actual demand of enterprises for optimizing automatic steel plate warehouse loading decisions, the PCDMOPSO algorithm has demonstrated good performance in the simulation test of solving the stack allocation model. …”
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Lightweight coal mine conveyor belt foreign object detection based on improved Yolov8n by Jierui Ling, Zhibo Fu, Xinpeng Yuan

“…Abstract To resolve the drawbacks of slow speed, excessive parameters, and high computational demands associated with deep learning-based conveyor belt foreign object detection methods, a lightweight algorithm for detecting foreign objects on conveyors based on an improved Yolov8n model is proposed. …”
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Real-Time Object Detection for the Running Train Based on the Improved YOLO V4 Neural Network by Yang Liu, Mengfei Gao, Humin Zong, Xinping Wang, Jinshuang Li

“…Lightweight convolutional neural network MobileNet and clustering ideas are combined to improve the object detection algorithm, and the MYOLO-lite model object detection algorithm is designed. …”
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Research on Sensitivity Improvement Methods for RTD Fluxgates Based on Feedback-Driven Stochastic Resonance with PSO by Rui Wang, Na Pang, Haibo Guo, Xu Hu, Guo Li, Fei Li

“…Simulink is used to construct the sensor model of odd polynomial feedback control, and the Particle Swarm Optimization (PSO) algorithm is used to optimize the coefficients of the feedback function so that the sensor reaches a resonance state, thus reducing the noise interference and improving the sensitivity of the sensor. …”
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Adversarial Reinforcement Learning-Based Converged Communication Efficiency Improvement Method for Power Distribution Network by Linyu PENG, Xu LIU, Wei TANG, Qing LIU, Hao FANG, Guanghui ZHANG

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Optimization of rotor-side controller parameters in doubly fed induction generators based on an improved NSGA-II. by Yanling Lv, Xiang Zhao, Zexin Mou

“…In particular, a multiobjective optimization framework based on an improved nondominated sorting genetic algorithm II (NSGA-II) is proposed by establishing a dynamic model of the rotor-side converter and investigating the operational dynamics of proportional-integral-derivative controllers under voltage transients. …”
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