Construction and validation of a predictive model for meningoencephalitis in pediatric scrub typhus based on machine learning algorithms by Yonghan Luo, Wenrui Ding, Xiaotao Yang, Houxi Bai, Feng Jiao, Yan Guo, Ting Zhang, Xiu Zou, Yanchun Wang

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Improved Dab-Deformable Model for Runway Foreign Object Debris Detection in Airport Optical Images by Yang Cao, Yuming Wang, Yilin Zhu, Rui Yang

“…First, this paper introduces a Lightweight Deep-Shallow Feature Fusion algorithm (LDSFF), which integrates a hotspot sensing network and a spatial mapping enhancer aimed at focusing the model on significant regions. …”
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Research on Lightweight Model of Multi-person Pose Estimation Based on Improved YOLOv8s-Pose by FU Yu, GAO Shuhui

“…To address the issues of high computational load and slow detection speed in existing human pose estimation models, this paper proposes a lightweight improved algorithm based on the YOLOv8s-Pose model. …”
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A Study of Corrosion-Grade Recognition on Metal Surfaces Based on Improved YOLOv8 Model by Hao Chen, Ying Cao, Shengxian Cao, Heng Piao

“…Finally, based on ablation experiments and comparison experiments, performance analyses of multiple algorithmic models are conducted for horizontal and vertical comparisons in order to verify the effectiveness of the improved method and the superiority of the models in this paper. …”
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Improving Offshore Wind Speed Forecasting with a CRGWAA-Enhanced Adaptive Neuro-Fuzzy Inference System by Yingjie Liu, Fahui Miao

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A Comprehensive Review and Benchmarking of Fairness-Aware Variants of Machine Learning Models by George Raftopoulos, Nikos Fazakis, Gregory Davrazos, Sotiris Kotsiantis

“…We analyze these adaptations in terms of their methodological adjustments, impact on algorithmic bias and ability to maintain predictive performance comparable to the original models.…”
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A population spatialization method based on the integration of feature selection and an improved random forest model. by Zhen Zhao, Hongmei Guo, Xueli Jiang, Ying Zhang, Changjiang Lu, Can Zhang, Zonghang He

“…Compared with MDA-RF, the prediction accuracy of the improved RF built on the same subset increased by 1.7%, indicating that improving the bootstrap sampling of random forest by using the K-means++ clustering algorithm can enhance model accuracy to some extent. …”
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Load Estimation Algorithm Based on Extended Kalman Filter for Freight Train by DENG Hao

“…In the simulation experiment of 2,000-ton load, the estimation error ranged from 3.5% to 4%, demonstrating the proposed algorithm could effectively improve the accuracy of the ATO system, with lower requirements on multi-particle motion models.…”
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Research on Traffic Marking Segmentation Detection Algorithm Based on Feature Fusion by Zhonghe He, Zizheng Gan, Pengfei Gong, Min Li, Kailong Li

“…In order to make the target detection task applicable to irregular objects or to detection tasks with higher accuracy requirements while reducing the waste of computational resources, this paper improves the accuracy of traffic marking segmentation detection by designing a multi-type traffic marking segmentation detection model based on image segmentation algorithms and designing a segmentation guidance matrix module based on a rank guidance matrix computation method. …”
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Courier Assignment and Routing Problem Algorithm in Online Food Delivery System with Multi-Customer Delivery Patterns by Prita Meilanitasari, Maulin Masyito Putri, Ilda Auly Sita Agustin, Muhammad Faisal Ibrahim, Dwi Sekar Arumjani

“…Various scenarios were tested to validate the model based on the chosen routes. The aim of this research is to develop a new model and algorithm that reduces delivery time and increases the number of orders that couriers can handle. …”
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An improved observer design approach for autonomous vehicles using error-based ultra-local model by Daniel Fenyes, Tamas Hegedus, Balazs Nemeth, Peter Gaspar

“…The design process combines two approaches: the Linear Parameter Varying framework and the error-based ultra-local model. The main goal of the error-based ultra-local model is to deal with the uncertainties and the nonlinearities of the model, whose effects cannot be taken into account during the modeling process. …”
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Developing an Optimization Model for Minimizing Solid Waste Collection Costs by Muciz Özcan, Semih Cengiz, Mehmet Şen

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Interpretable prediction model for hand-foot-and-mouth disease incidence based on improved LSTM and XGBoost by Xiao LI, Shuyu HE, Yan PENG, Rongxin YANG, Lu TAO, Tingqi LOU, Wenqi HE

“…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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Concrete Creep Prediction Based on Improved Machine Learning and Game Theory: Modeling and Analysis Methods by Wenchao Li, Houmin Li, Cai Liu, Kai Min

“…Therefore, in this study, three machine learning (ML) models, a Support Vector Machine (SVM), Random Forest (RF), and Extreme Gradient Boosting Machine (XGBoost), are constructed, and the Hybrid Snake Optimization Algorithm (HSOA) is proposed, which can reduce the risk of the ML model falling into the local optimum while improving its prediction performance. …”
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A model for shale gas well production prediction based on improved artificial neural network by LIN Hun, SUN Xinyi, SONG Xixiang, MENG Chun, XIONG Wenxin, HUANG Junhe, LIU Hongbo, LIU Cheng

“…Moreover, the model exhibits superior prediction accuracy and stability compared to the traditional BP（error backpropagation algorithm） neural network model. …”
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Identification method of canned food for production line sorting robot based on improved PSO-SVM by GAO Haiyan, GAO Jinyang, WANG Weicheng

“…By improving the particle swarm optimization algorithm to optimize support vector machine parameters, an optimized support vector machine classification model was obtained. …”
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Robust Adversarial Example Detection Algorithm Based on High-Level Feature Differences by Hua Mu, Chenggang Li, Anjie Peng, Yangyang Wang, Zhenyu Liang

“…To address these challenges, this paper introduces a novel adversarial example detection algorithm based on high-level feature differences (HFDs), which is specifically designed to improve robustness against both attacks and preprocessing operations. …”
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An Intrusion Detection Model Based on Feature Selection and Improved One-Dimensional Convolutional Neural Network by Qingfeng Li, Bo Li, Linzhi Wen

“…In this paper, an intrusion detection model based on feature selection and improved one-dimensional convolutional neural network was proposed. …”
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A Method for Bio-Sequence Analysis Algorithm Development Based on the PAR Platform by Haipeng Shi, Huan Chen, Qinghong Yang, Jun Wang, Haihe Shi

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Parameter Identification in Triple-Diode Photovoltaic Modules Using Hybrid Optimization Algorithms by Dhiaa Halboot Muhsen, Haider Tarish Haider, Yaarob Al-Nidawi

“…Seven different experimental data sets are used to improve the performance of the proposed differential evolution with an integrated mutation per iteration algorithm (DEIMA). …”
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