A novel model for malaria prediction based on ensemble algorithms. by Mengyang Wang, Hui Wang, Jiao Wang, Hongwei Liu, Rui Lu, Tongqing Duan, Xiaowen Gong, Siyuan Feng, Yuanyuan Liu, Zhuang Cui, Changping Li, Jun Ma

“…A single model cannot effectively capture all the properties of the data structure. However, a stacking architecture can solve this problem by combining distinct algorithms and models. …”
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Cloud drift optimization algorithm as a nature-inspired metaheuristic by Mohammad Alibabaei Shahraki

“…The CDO algorithm mimics the dynamic behavior of cloud particles influenced by atmospheric forces, striking a refined balance between exploration and exploitation. …”
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TAL-SRX: an intelligent typing evaluation method for KASP primers based on multi-model fusion by Xiaojing Chen, Xiaojing Chen, Jingchao Fan, Jingchao Fan, Shen Yan, Longyu Huang, Longyu Huang, Longyu Huang, Guomin Zhou, Guomin Zhou, Jianhua Zhang, Jianhua Zhang

“…To address the above problems, we proposed a typing evaluation method for KASP primers by integrating deep learning and traditional machine learning algorithms, called TAL-SRX. First, three algorithms are used to optimize the performance of each model in the Stacking framework respectively, and five-fold cross-validation is used to enhance stability. …”
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Ensemble and transfer learning of soil inorganic carbon with visible near-infrared spectra by Yu Wang, Keyang Yin, Bifeng Hu, Yongsheng Hong, Songchao Chen, Jing Liu, Lili Yang, Jie Peng, Zhou Shi

“…The stacking model consists of 10 base models (support vector machine (SVM), partial least squares algorithm (PLSR), multi-layer perceptron (MLP), etc.). …”
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Predicting the risk of acute kidney injury in patients with acute pancreatitis complicated by sepsis using a stacked ensemble machine learning model: a retrospective study based on... by Ying Zhou, Fuyuan Li, Zhan Wang, Zhanjin Wang, Ruiling Bian, Zhangtuo Xue, Junjie Cai

“…A new stacked ensemble model was developed using the Stacking ensemble method. …”
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A robot process automation based mobile application for early prediction of chronic kidney disease using machine learning by Md. Hasan Imam Bijoy, Md. Jueal Mia, Md. Mahbubur Rahman, Mohammad Shamsul Arefin, Pranab Kumar Dhar, Tetsuya Shimamura

“…The models’ performance was assessed using accuracy, precision, recall, F1-Score, error rate, AUC, and computational time. Among the tested algorithms, MKR Stacking achieved the highest accuracy of 99.50%, outperforming Random Forest (98.75%) and MKR Voting (98%). …”
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A Robust Framework for Bamboo Forest AGB Estimation by Integrating Geostatistical Prediction and Ensemble Learning by Lianjin Fu, Qingtai Shu, Cuifen Xia, Zeyu Li, Hailing He, Zhengying Li, Shaoyang Ma, Chaoguan Qin, Rong Wei, Qin Xiang, Xiao Zhang, Yiran Zhang, Huashi Cai

“…This study first employed Empirical Bayesian Kriging Regression Prediction (EBKRP) to spatialize sparse GEDI and ICESat-2 LiDAR metrics using Sentinel-2 and topographic covariates. Subsequently, a stacked ensemble model, integrating four machine learning algorithms, predicted AGB from the full suite of continuous variables. …”
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Ensemble Learning for Spatial Modeling of Icing Fields from Multi-Source Remote Sensing Data by Shaohui Zhou, Zhiqiu Gao, Bo Gong, Hourong Zhang, Haipeng Zhang, Jinqiang He, Xingya Xi

“…We applied five machine learning algorithms—Random Forest, XGBoost, LightGBM, Stacking, and Convolutional Neural Network Transformers (CNNT)—and evaluated their performance using six metrics: R, RMSE, CSI, MAR, FAR, and fbias, on both validation and testing sets. …”
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Genomic selection in pig breeding: comparative analysis of machine learning algorithms by Ruilin Su, Jingbo Lv, Yahui Xue, Sheng Jiang, Lei Zhou, Li Jiang, Junyan Tan, Zhencai Shen, Ping Zhong, Jianfeng Liu

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Lightweight remote sensing ship detection algorithm based on YOLOv5s by Haochen WANG, Yuelan XIN, Jiang GUO, Qingqing WANG

“…ObjectiveThis paper proposes a lightweight remote sensing ship target detection algorithm LR-YOLO based on improved YOLOv5s to meet the lightweight and fast inference requirements of ship target detection tasks involving remote sensing images. …”
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Comparative Study of Blockchain Hashing Algorithms with a Proposal for HashLEA by Abdullah Sevin, Abdu Ahmed Osman Mohammed

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PREDICTION OF SOFTWARE ANOMALIES METHODS BASED ON ENSEMBLE LEARNING METHODS by Raghda Azad Hasan, Ibrahim Ahmed Saleh

“…The model applies the basic algorithms (Random Forest (RF), Decision Tree (DT), Extra Tree) and the learning model ensemble (Adaboost, xgboost ,Stack, Voting, bagging) and metrics (accuracy, recall, F1 score, accuracy) to measure the prediction performance of the models and a comparison was made between the proposed model algorithms. …”
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Application of supervised machine learning and unsupervised data compression models for pore pressure prediction employing drilling, petrophysical, and well log data by Abu Bakker Siddique, Tanveer Alam Munshi, Nazmul Islam Rakin, Mahamudul Hashan, Sushmita Sarker Chnapa, Labiba Nusrat Jahan

“…A thorough comparison of all analyzed models indicates that the algorithms, ranked by performance metrics, are Stack_2, CatBoost, Stack_1, RF, PR, Stack_3, MLP, and MVR. …”
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Impact of PM_2.5 Pollution on Solar Photovoltaic Power Generation in Hebei Province, China by Ankun Hu, Zexia Duan, Yichi Zhang, Zifan Huang, Tianbo Ji, Xuanhua Yin

“…The inclusion of PM_2.5 as a predictor variable systematically enhanced model performance across all algorithms. To further optimize prediction accuracy, we implemented a stacking ensemble framework that integrates multiple base learners through meta-learning. …”
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An approach to improve grounding resistance characteristic in existing 115 KV transmission towers by Chaichan Pothisarn, Wiwat Kulwongwit, Praikanok Lertwanitrot, Sulee Bunjongjit, Atthapol Ngaopitakkul

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Algorithms for Simulation of Shunt Currents in a Vanadium Redox Flow Battery by Decebal Aitor Ispas-Gil, Ekaitz Zulueta, Javier Olarte, Jose Manuel Lopez-Guede

“…The formation patterns of the equivalent electrical circuit that models shunt currents in redox flow batteries are analyzed in such a way that the proposed algorithm is applicable for batteries with any number of cell stacks and any number of cells per stack. …”
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DNA-Inspired Lightweight Cryptographic Algorithm for Secure and Efficient Image Encryption by Mahmoud A. Abdelaal, Abdellatif I. Moustafa, H. Kasban, H. Saleh, Hanaa A. Abdallah, Mohamed Yasin I. Afifi

“…Very well-established encryption mechanisms such as AES, RC4, and XOR cannot strike a balance between speed, energy consumption, and robustness. …”
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Dam Crack Instance Segmentation Algorithm Based on Improved YOLOv8 by Shuaisen Ma, Mingyue Xu, Weiwu Feng

“…Dam cracks are typically morphologically complex and suffer from severe background interference. Current algorithms often struggle to strike a balance between detection accuracy and segmentation precision. …”
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An improved polar lights optimization algorithm for global optimization and engineering applications by Tianping Huang, Faguo Huang, Zhaohui Qin, Jiafang Pan

“…Abstract The study proposes an enhanced, high-caliber Population Evolution Polar Lights Optimization (IPLO) algorithm to address the shortcomings of the existing Polar Lights Optimization (PLO) method. …”
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Improved YOLOv8-Based Algorithm for Citrus Leaf Disease Detection by Zhengbing Zheng, Yibang Zhang, Luchao Sun

“…In view of the small difference between citrus leaf diseases which can lead to false inspection and missed inspection, an improved YOLOv8 citrus leaf disease detection algorithm is proposed. The proposed approach uses YOLOv8n as the base model and introduces adaptive convolution into the Backbone, allowing the model to dynamically prioritize different disease features. …”
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