Prediction of new candidate proteins and analysis of sub-modules and protein hubs associated with seed development in rice (Oryza sativa) using an ensemble network-based systems bi... by M. R. P. De Silva, J. W. J. K. Weeraman, S. Piyatissa, P. C. Fernando

“…Using a list of known seed development proteins from the Gene Ontology (GO) knowledgebase and literature, novel candidate proteins for seed development were predicted using an ensemble of network-based algorithms, including Majority Voting, Hishigaki Algorithm, Functional Flow, and Random Walk with Restart, which were selected based on their popularity and usability. …”
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Prediction of cold region dew volume based on an ECOA-BiTCN-BiLSTM hybrid model by Yi Zhang, Pengtao Liu, Yingying Xu, Meng Zhang

Subjects: “…Swarm intelligence optimization algorithm…”
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Endpoint carbon content and temperature prediction model in BOF steelmaking based on posterior probability and intra-cluster feature weight online dynamic feature selection by Wang Haodong, Liu Hui, Chen FuGang, Li Heng, Xue XiaoJun

“…A posterior probability and intra-cluster feature weight online dynamic feature selection algorithm is proposed to address the issues of high dimensionality and high volatility of data in the basic oxygen furnace (BOF) steelmaking production process. …”
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Predicting over-the-counter antibiotic use in rural Pune, India, using machine learning methods by Pravin Arun Sawant, Sakshi Shantanu Hiralkar, Yogita Purushottam Hulsurkar, Mugdha Sharad Phutane, Uma Satish Mahajan, Abhay Machindra Kudale

“…METHODS The features of OTC antibiotic use were selected using stepwise logistic, lasso, random forest, XGBoost, and Boruta algorithms. Regression and tree-based models with all confirmed and tentatively important features were built to predict the use of OTC antibiotics. …”
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Optimizing Bifacial Solar Modules with Trackers: Advanced Temperature Prediction Through Symbolic Regression by Fabian Alonso Lara-Vargas, Carlos Vargas-Salgado, Jesus Águila-León, Dácil Díaz-Bello

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A Special Points and Neural Network-Based Dynamic Multi-Objective Optimization Algorithm by Sanyi Li, Wenjie Hou, Peng Liu, Weichao Yue, Qian Wang

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Cybersecure XAI Algorithm for Generating Recommendations Based on Financial Fundamentals Using DeepSeek by Iván García-Magariño, Javier Bravo-Agapito, Raquel Lacuesta

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A Probability Integral Parameter Inversion Method Integrating a Selection-Weighted Iterative Robust Genetic Algorithm by Chuang Jiang, Wei Liu, Lei Wang, Xu Zhu, Hao Tan

“…However, the use of traditional genetic algorithms (GA) for inversion prediction has problems such as poor resistance to differences, and the accuracy of inversion parameters is affected when key monitoring points are missing. …”
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Machine learning opportunities to predict obstetric haemorrhages by Yu. S. Boldina, A. A. Ivshin

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Predicting Student Performance and Enhancing Learning Outcomes: A Data-Driven Approach Using Educational Data Mining Techniques by Athanasios Angeioplastis, John Aliprantis, Markos Konstantakis, Alkiviadis Tsimpiris

“…This study investigates the use of educational data mining (EDM) techniques to predict student performance and enhance learning outcomes in higher education. …”
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Epistemic authority and generative AI in learning spaces: rethinking knowledge in the algorithmic age by Binny Jose, Anu Cleetus, Bindhu Joseph, Lumy Joseph, Benymol Jose, Amruth K. John

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RETRACTED: Bone Age Assessment Based on Deep Convolutional Features and Fast Extreme Learning Machine Algorithm by Longjun Guo, Juan Wang, Jiaqi Teng, Yukun Chen

“…As the development of deep learning DL-based bone age prediction methods have achieved great success. However, it also faces the issue of huge computation overhead in deep features learning. …”
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Integrating proximal geophysical sensing and machine learning for digital soil mapping: Spatial prediction and model evaluation using a small dataset by Danilo César de Mello, Gustavo Vieira Veloso, Murilo Ferre de Mello, Marcos Guedes de Lana, Isabelle de Angeli Oliveira, Fellipe Alcantara de Oliveira Mello, Rafael Gomes Siqueira, Lucas Carvalho Gomes, Elpídio Inácio Fernandes-Filho, Carlos Ernesto Gonçalves Reynaud Schaefer, Márcio Rocha Francelino, Emilson Pereira Leite, Tiago Osório Ferreira, José Alexandre Melo Demattê

“…However, studies focusing the spatial prediction of geophysical data remain limited. In this research, we aimed to model and predict the spatial distribution of soil geophysical properties using parent material and terrain attributes with machine learning algorithms. …”
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Enhancing Manufacturing Precision: Leveraging Motor Currents Data of Computer Numerical Control Machines for Geometrical Accuracy Prediction Through Machine Learning by Lucijano Berus, Jernej Hernavs, David Potocnik, Kristijan Sket, Mirko Ficko

“…Different machine learning algorithms, such as Random Forest (RF), k-nearest neighbors (k-NN), and Decision Trees (DT), were used for predictive modeling. …”
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Development and Validation of a Machine Learning Model for Early Prediction of Sepsis Onset in Hospital Inpatients from All Departments by Pierre-Elliott Thiboud, Quentin François, Cécile Faure, Gilles Chaufferin, Barthélémy Arribe, Nicolas Ettahar

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A SHAP algorithm-based prediction of the interlaminar shear strength degradation of G/BFRP bars embedded in concrete exposed to marine environment by Xuan Zhao, Pei-Fu Zhang, Qi Zhao, Daxu Zhang, Yiliyaer Tuerxunmaimaiti, Heng Cao

“…To address this issue, a dataset collected from published literature was compiled and SHAP algorithm-based method was employed to predict the ILSS retention (ILSSR). …”
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Exploring explainable machine learning algorithms to model predictors of tobacco use among men in Sub Sahara Africa between 2018 and 2023 by Mequannent Sharew Melaku, Nebebe Demis Baykemagn, Lamrot Yohannes, Adem Tsegaw Zegeye

“…This study aimed to model predictors of tobacco use among men in Sub Sahara Africa between 2018 and 2023 using machine learning algorithms. Data from Demographic and Health Surveys covering 147,466 men were analyzed. …”
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Research on short-term precipitation forecasting method based on CEEMDAN-GRU algorithm by Hua Xu, Zongkai Guo, Yu Cao, Xu Cheng, Qiong Zhang, Dan Chen

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Quantitative Prediction of Low-Permeability Sandstone Grain Size Based on Conventional Logging Data by Deep Neural Network-Based BP Algorithm by Hongjun Fan, Xiaoqing Zhao, Zongjun Wang, Zheqing Zhang, Ao Chang

“…Machine learning of median grain size from conventional logging data was systematically carried out through conventional logging sensitivity curve optimization, algorithm modeling, network parameter optimization, median grain size prediction, and validation, and the relative error in its quantitative prediction met application requirements. …”
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Development of a Secured IoT-Based Flood Monitoring and Forecasting System Using Genetic-Algorithm-Based Neuro-Fuzzy Network by Hero Rafael Castillo Arante, Edwin Sybingco, Maria Antonette Roque, Leonard Ambata, Alvin Chua, Alvin Neil Gutierrez

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