Accelerating the design and discovery of tribocorrosion-resistant metals by interfacing multiphysics modeling with machine learning and genetic algorithms by Yucong Gu, Kaiwen Wang, Zhengyu Zhang, Yi Yao, Ziming Xin, Wenjun Cai, Lin Li

“…Addressing this complexity, our study develops a novel methodology fusing machine-learning (ML) and genetic algorithm (GA)-based optimization techniques to tailor aluminum-based alloys for enhanced tribocorrosion resistance. …”
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On Computability and Applicability of Mann-Reich-Sabach-Type Algorithms for Approximating the Solutions of Equilibrium Problems in Hilbert Spaces by F. O. Isiogugu, P. Pillay, P. U. Nwokoro

“…The obtained result is a partial resolution of the controversy over the computability of such algorithms in the contemporary literature.…”
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Development of Future Rule Curves for Multipurpose Reservoir Operation Using Conditional Genetic and Tabu Search Algorithms by Anongrit Kangrang, Haris Prasanchum, Rattana Hormwichian

“…This study applied the conditional genetic algorithm (CGA) and the conditional tabu search algorithm (CTSA) technique to connect with the reservoir simulation model in order to search optimal reservoir rule curves. …”
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Nondestructive Detection of Moisture Content in Palm Oil by Using Portable Vibrational Spectroscopy and Optimal Prediction Algorithms by Ernest Teye, Charles L. Y. Amuah, Tai-Sheng Yeh, Regina Nyorkeh

“…Several preprocessing methods such as standard normal variant (SNV), multiplicative scatter correction (MSC), Savitzky–Golay first derivative (SGD1), Savitzky–Golay second derivative (SGD2) together with partial least square (PLS) regression techniques, full PLS, interval PLS (iPLS), synergy interval PLS (SiPLS), genetic algorithm PLS (GAPLS), and successive projection algorithm PLS (SPA-PLS) were comparatively employed to construct an optimum quantitative prediction model for moisture content in crude palm oil. …”
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Prediction of stunting and its socioeconomic determinants among adolescent girls in Ethiopia using machine learning algorithms. by Alemu Birara Zemariam, Biruk Beletew Abate, Addis Wondmagegn Alamaw, Eyob Shitie Lake, Gizachew Yilak, Mulat Ayele, Befkad Derese Tilahun, Habtamu Setegn Ngusie

“…Eight machine learning algorithms were included for consideration of model building and comparison. …”
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Efficient Hamiltonian encoding algorithms for extracting quantum control mechanism as interfering pathway amplitudes in the Dyson series by Erez Abrams, Michael Kasprzak, Gaurav Bhole, Tak-San Ho, Herschel Rabitz

“…These new algorithms provide an exponential decrease in both computation time and memory utilization with respect to the Hilbert space dimension of the system. …”
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Validation of Two MODIS Aerosols Algorithms with SKYNET and Prospects for Future Climate Satellites Such as the GCOM-C/SGLI by Jules R. Dim, Tamio Takamura, Akiko Higurashi, Pradeep Kathri, Nobuyuki Kikuchi, Takahashi Y. Nakajima

“…The examination of the AE shows a clear underestimation (by around 0.2–0.3) by both satellites’ algorithms. The uncertainties explaining these ground-satellites’ algorithms discrepancies are examined: the cloud contamination affects differently the aerosols properties (AOT and AE) of both satellites’ algorithms due to the retrieval scale differences between these algorithms. …”
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Monotone Hybrid Projection Algorithms for an Infinitely Countable Family of Lipschitz Generalized Asymptotically Quasi-Nonexpansive Mappings by Watcharaporn Cholamjiak, Suthep Suantai

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Short-Term Power Prediction of Building Integrated Photovoltaic (BIPV) System Based on Machine Learning Algorithms by R. Kabilan, V. Chandran, J. Yogapriya, Alagar Karthick, Priyesh P. Gandhi, V. Mohanavel, Robbi Rahim, S. Manoharan

“…The proposed prediction methodology comprises a data quality stage, machine learning algorithm, weather clustering assessment, and an accuracy assessment. …”
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Enhanced vehicle routing for medical waste management via hybrid deep reinforcement learning and optimization algorithms by Norhan Khallaf, Osama Abd-El Rouf, Abeer D. Algarni, Mohy Hadhoud, Ahmed Kafafy

Subjects: “…unsupervised learning algorithm…”
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Model Optimization Analysis of Customer Churn Prediction Using Machine Learning Algorithms with Focus on Feature Reductions by Seyed Mohammad Sina Mirabdolbaghi, Babak Amiri

“…Secondly, implementing a comprehensive feature reduction system based on popular algorithms reduces the features and selects the most suitable one. …”
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Graph Theory Algorithms of Hamiltonian Cycle from Quasi-Spanning Tree and Domination Based on Vizing Conjecture by T. Anuradha, T. Lakshmi Surekha, Praveena Nuthakki, Bullarao Domathoti, Ganesh Ghorai, Faria Ahmed Shami

“…In this study, from a tree with a quasi-spanning face, the algorithm will route Hamiltonian cycles. Goodey pioneered the idea of holding facing 4 to 6 sides of a graph concurrently. …”
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Infrared Spectroscopy Coupled with Machine Learning Algorithms to Investigate Vascular Dysfunction in Ovariectomy: An Animal Model Study by Tháfanys S. Travezani, Márcia H. C. Nascimento, Tagana R. da Cunha, Roger L. dos Santos, Francis L. Martin, Valerio G. Barauna

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Immune cell profiles and predictive modeling in osteoporotic vertebral fractures using XGBoost machine learning algorithms by Yi-Chou Chen, Hui-Chen Su, Shih-Ming Huang, Ching-Hsiao Yu, Jen-Huei Chang, Yi-Lin Chiu

“…Methods This study aims to investigate the xCell signature-based immune cell profiles in osteoporotic patients with and without vertebral fractures, utilizing advanced predictive modeling through the XGBoost algorithm. Results Our findings reveal an increased presence of CD4 + naïve T cells and central memory T cells in VF patients, indicating distinct adaptive immune responses. …”
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Deep Learning Algorithms and Multicriteria Decision-Making Used in Big Data: A Systematic Literature Review by Mei Yang, Shah Nazir, Qingshan Xu, Shaukat Ali

“…The aim of the proposed study is to present a systematic literature study in order to show the applications of deep learning algorithms and multicriteria decision approaches for the problems of big data. …”
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Identification and Verification of Novel Biomarkers Involving Rheumatoid Arthritis with Multimachine Learning Algorithms: An In Silicon and In Vivo Study by Fucun Liu, Juelan Ye, Shouli Wang, Yang Li, Yuhang Yang, Jianru Xiao, Aimin Jiang, Xuhua Lu, Yunli Zhu

“…Four machine learning algorithms, including LASSO, RF, XGBoost, and SVM, were used to identify RA-related biomarkers. …”
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UAV-Assisted Space-Air-Ground Integrated Networks: A Technical Review of Recent Learning Algorithms by Atefeh Hajijamali Arani, Peng Hu, Yeying Zhu

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Inverse design of nanophotonic devices enabled by optimization algorithms and deep learning: recent achievements and future prospects by Kim Junhyeong, Kim Jae-Yong, Kim Jungmin, Hyeong Yun, Neseli Berkay, You Jong-Bum, Shim Joonsup, Shin Jonghwa, Park Hyo-Hoon, Kurt Hamza

“…We discuss representative methods commonly employed in nanophotonic design, including various meta-heuristic algorithms such as trajectory-based, evolutionary, and swarm-based approaches, in addition to adjoint-based optimization. …”
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Comparison of Machine Learning Algorithms for the Prediction of Mechanical Stress in Three-Phase Power Transformer Winding Conductors by Fausto Valencia, Hugo Arcos, Franklin Quilumba

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Some Convergence and Stability Results for Two New Kirk Type Hybrid Fixed Point Iterative Algorithms by Faik Gürsoy, Vatan Karakaya

“…We introduce Kirk-multistep-SP and Kirk-S iterative algorithms and we prove some convergence and stability results for these iterative algorithms. …”
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