Multi-UAV path planning considering multiple energy consumptions via an improved bee foraging learning particle swarm optimization algorithm by Yuanhang Qi, Haoran Jiang, Gewen Huang, Liang Yang, Fujie Wang, Yunjian Xu

“…To tackle the MUAVPP-MEC, this study proposes an improved Bee Foraging Learning Particle Swarm Optimization algorithm (IBFLPSO), which integrates the bee-foraging algorithm into the particle swarm optimization framework. …”
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Epidemiological Assessment and Inference in Race-Based Clinical Algorithms: A Narrative Review and Health Policy Analysis Focused on Living Kidney Donation by Sienna E. Schaeffer, Carolina Gonzalez Bravo, Christopher D. Ahlers, Alaina N. Elliott-Wherry, Hannah Zadeh, Precious-Junia de-Winton Cummings, Kimberly C. Dukes, Nasrien E. Ibrahim, DeShauna Jones, Patrick T. Zamba, Aloha D. Wilks, Martha L. Carvour

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Designing an explainable bio-inspired model for suspended sediment load estimation: eXtreme Gradient Boosting coupled with Marine Predators Algorithm by Roozbeh Moazenzadeh, Okan Mert Katipoğlu, Ahmadreza Shateri, Hamid Nasiri, Mohammed Abdallah

“…While Xtreme Gradient Boosting (XGB), a powerful ensemble machine learning (ML) model, has been employed in previous studies, the novelty of this research lies in the introduction of a hybrid approach that synergistically combines XGB with the bio-inspired Marine Predators Algorithm (XGB-MPA) to estimate SL in the Yeşilirmak River (Turkey). …”
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DeepGenMon: A Novel Framework for Monkeypox Classification Integrating Lightweight Attention-Based Deep Learning and a Genetic Algorithm by Abdulqader M. Almars

“…Finally, the CNN’s hyperparameters are adjusted using a genetic algorithm to enhance the model’s robustness and classification accuracy. …”
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A Weighted Voting Approach for Traditional Chinese Medicine Formula Classification Using Large Language Models: Algorithm Development and Validation Study by Zhe Wang, Keqian Li, Suyuan Peng, Lihong Liu, Xiaolin Yang, Keyu Yao, Heinrich Herre, Yan Zhu

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Enhancing neurological disease diagnostics: fusion of deep transfer learning with optimization algorithm for acute brain stroke prediction using facial images by Fadwa Alrowais, Mohammed Alqahtani, Jahangir Khan, Achraf Ben Miled, Da’ad Albalawneh, Abdulwhab Alkharashi, Samah Al Zanin, Radwa Marzouk

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Recursive feature elimination for summer wheat leaf area index using ensemble algorithm-based modeling: The case of central Highland of Ethiopia by Dereje Biru, Berhan Gessesse, Gebeyehu Abebe

“…However, building a high-performance predictive model faces challenges in selecting suitable machine learning algorithms and identifying important variables. This study explored the use of ensemble algorithm-based recursive feature elimination (RFE) for summer wheat LAI estimation using the Google Earth Engine (GEE) cloud computing platform. …”
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Forward Predicting Chromatic-Optical Parameters of the Mixed Light of White-Red Light-Emitting Diode Configurations Based on Deep Learning Algorithms by Songsheng Lin, Huanting Chen, Yin Zheng, Quanji Xie, Xuehua Shen, Huichuan Lin, Shuo Lin, Yan Li

“…Four deep learning algorithms were evaluated. Each model was trained to reconstruct the SPD curves and predict the corresponding optical and chromatic parameters. …”
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Parallelizing process model integration for model predictive control through oracle design and analysis for a Grover’s algorithm-inspired optimization strategy by Kip Nieman, Helen Durand, Saahil Patel, Daniel Koch, Paul M. Alsing

“…We also see this as forming an important first step in algorithm design/analysis, which can then translate to future works in comparing this technique computationally with classical “competitor” algorithms to guide further work in searching for relevant quantum algorithms for control applications.…”
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The utility of an artificial intelligence model based on decision tree and evolution algorithm to evaluate steatotic liver disease in a primary care setting by A.C. Goulart, A.P. Alencar, G. Tunes, L.L.T. Bianchi, M.H. Miname, C.M. Padilha, J.M.S. Pescuma, A.L.C.C. Rodrigues, B.B. Henares, M.S. de Almeida, T.A.O. Machado, D.H. Syllos, Y.P. Wang, M. Rienzo

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Value of Low Tube Voltage Combined with Deep Learning Image Reconstruction Algorithm to Reduce Radiation Dose in Combined Thoracoabdominal Enhanced CT by Weiwei QI, Jin CHENG, Chuhan CHEN, Bei AN, Xiaoyi LIU, Ling FU, Yi WANG

“…To determine the feasibility of combining low tube voltage with deep learning algorithms for low-contrast resolution, Catphan 500 phantoms were scanned under two different conditions. …”
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Complete Blood Count and Monocyte Distribution Width–Based Machine Learning Algorithms for Sepsis Detection: Multicentric Development and External Validation Study by Andrea Campagner, Luisa Agnello, Anna Carobene, Andrea Padoan, Fabio Del Ben, Massimo Locatelli, Mario Plebani, Agostino Ognibene, Maria Lorubbio, Elena De Vecchi, Andrea Cortegiani, Elisa Piva, Donatella Poz, Francesco Curcio, Federico Cabitza, Marcello Ciaccio

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Developing an Optimization Model for Minimizing Solid Waste Collection Costs by Muciz Özcan, Semih Cengiz, Mehmet Şen

“…The SA algorithm outperformed the greedy algorithm by 26.49%.…”
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A Real Data-Driven Clustering Approach for Countries Based on Happiness Score by Aditya Chakraborty, Chris P Tsokos

“…Finally, we use four popular machine learning classification algorithms to validate our cluster-based algorithm and obtained very consistent results with high accuracy.…”
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Enhancing recommender systems with provider fairness through preference distribution awareness by Elizabeth Gómez, David Contreras, Ludovico Boratto, Maria Salamó

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Promoting or Hindering: The Impact of ESG Rating Differences on Energy Enterprises’ Green Transformation—A Causal Test from Double Machine-Learning Algorithms by Jun Wan, Yuejia Wang, Yuan Wang

“…This study leverages data from companies listed on the Shanghai Stock Exchange in China, applying double machine-learning algorithms to precisely estimate the causal relationship between variations in ESG ratings and the green transition efficiency of energy companies. …”
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Comparison of Support Vector Machine (SVM) and Random Forest (RF) Algorithm Performance with Random Undersampling Technique to Predict Gestational Diabetes Mellitus Risk by Annisa Damayanti, Anna Baita

“…One of the machine learning methods that can be used to predict GDM is the Support Vector Machine (SVM) algorithm and the Random Forest (RF) algorithm. This study aims to compare, and evaluate GDM disease prediction models using the SVM and RF algorithms by balancing the target data using the Random Undersampling Technique. …”
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Pseudodynamic Bearing Capacity Analysis of Shallow Strip Footing Using the Advanced Optimization Technique “Hybrid Symbiosis Organisms Search Algorithm” with Numerical Validation... by Arijit Saha, Apu Kumar Saha, Sima Ghosh

“…This combination can improve the searching capability of the algorithm for attaining the global optimum. Numerical analysis is also done using dynamic modules of PLAXIS-8.6v for the validation of this analytical solution. …”
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An Improved Clustering Cooperative Spectrum Sensing Algorithm Based on Modified Double-Threshold Energy Detection and Its Optimization in Cognitive Wireless Sensor Networks by Shubin Wang, Huiqin Liu, Kun Liu

“…Simulation results show that the detecting accuracy of the improved algorithm is higher than conventional CSS, and the improved algorithm can also significantly improve collaborative sensing ability. …”
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Taylor-Spotted Cat Optimization (Taylor-SCO): An Energy-Efficient Cluster Head Selection Algorithm with Improved Trust Factor for Data Routing in WSN by Shivaraj Kalburgi, M. Manimozhi

“…Moreover, the developed Taylor-SCO algorithm is developed by combining the Spotted Hyena Optimizer (SHO), Cat Swarm Optimization (CSO) algorithm, and Taylor series. …”
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