Prediction of the Strength of Rubberized Concrete by an Evolved Random Forest Model by Yuantian Sun, Guichen Li, Junfei Zhang, Deyu Qian

“…In this study, an evolutionary random forest model (BRF) combining random forest (RF) and beetle antennae search (BAS) algorithms was proposed, which can be used for establishing the relationship between UCS of RC and its key variables. …”
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Small fishing boat classification and recognition method based on GASF temporal graph coding and EMPViT model by Jiaqi Deng, Xin Liu, Gang Du, Xu Yang, Liangzhong Jiang, Chenglong Sun

“…Abstract Effective classification and identification algorithms of small fishing vessels are the key to strengthen ship management. …”
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A Trajectory Prediction Method for Reentry Glide Vehicles via Adaptive Cost Function by Yangchao He, Jiong Li, Lei Shao, Chijun Zhou, Xiangwei Bu

“…The results of the simulations demonstrate that the proposed prediction method is capable of accurately inferring the vehicle’s attack intention and parameter model, and of effectively reducing the accumulation of prediction errors and the time required for the algorithmic process compared to existing methods.…”
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Design and Implementation of Xinjiang Astronomical Observatory Astronomical Data Transmission Visualization System by Xinchen Ye, Hailong Zhang, Yan Zhu, Jie Wang, Tohtonur Ergesh, Huijuan Li

“…We also design corresponding mechanisms to ensure the high stability of the system and to control the data transmission when the network is unstable through adaptive algorithms. In test, this visualization system can run stably for a long time in unmanned manner. …”
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A Comprehensive Review of Facial Beauty Prediction Using Multi-task Learning and Facial Attributes by Ali H. Ibrahem, Adnan M. Abdulazeez

“…We further examine the methodological challenges in defining and measuring beauty, such as data imbalances and algorithmic fairness. By synthesizing insights from psychology and machine learning, this work highlights the potential of interdisciplinary approaches to enhance the reliability and inclusivity of automated beauty prediction systems. …”
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Development of an Indicator for the Assessment of Damage Level in Rolling Element Bearings Based on Blind Deconvolution Methods by Marco Buzzoni, Elia Soave, Gianluca D’Elia, Emiliano Mucchi, Giorgio Dalpiaz

“…In order to improve the diagnostic performance of the kurtosis, blind deconvolution algorithms can be exploited in order to detect bearing faults and, most importantly, their position. …”
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Ensembles of spectral-spatial convolutional neural network models for classifying soil types in hyperspectral images by N.A. Firsov, V.V. Podlipnov, N.A. Ivliev, D.D. Ryskova, A.V. Pirogov, A.A. Muzyka, A.R. Makarov, V.E. Lobanov, V.I. Platonov, A.N. Babichev, V.A. Monastyrskiy, V.I. Olgarenko, D.P. Nikolaev, R.V. Skidanov, A.V. Nikonorov, N.L. Kazanskiy, V.A. Soyfer

“…The paper presents a study of various approaches to the classification of soil covers based on neural network algorithms using hyperspectral remote and proximal sensing of the Earth. …”
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Investigation of an object-detection approach for estimating the rock fragmentation in the open-pit conditions by K. Reshetnikov, M. Ronkin, S. Porshnev

“…Because of this, the use of alternative techniques based on algorithms for the real-time object detection is highly relevant. …”
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A Bioinspired Methodology Based on an Artificial Immune System for Damage Detection in Structural Health Monitoring by Maribel Anaya, Diego A. Tibaduiza, Francesc Pozo

“…Among all the aspects that are linked to a structural health monitoring (SHM) system, algorithms, strategies, or methods for damage detection are currently playing an important role in improving the operational reliability of critical structures in several industrial sectors. …”
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Causal discovery and fault diagnosis based on mixed data types for system reliability modeling by Xiaokang Wang, Siqi Jiang, Xinghan Li, Mozhu Wang

“…However, due to limitations in existing frameworks regarding model representations and learning algorithms, only a few studies have explored causal discovery on non-Euclidean data. …”
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Prediction of Rooftop Photovoltaic Solar Potential Using Machine Learning by K. Mukilan, K. Thaiyalnayaki, Yagya Dutta Dwivedi, J. Samson Isaac, Amarjeet Poonia, Arvind Sharma, Essam A. Al-Ammar, Saikh Mohammad Wabaidur, B. B. Subramanian, Adane Kassa

“…The availability of data at unprecedented levels of granularity allows for the development of data-driven algorithms to improve the estimation of solar energy generation and production. …”
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Employing Data Mining Techniques and Machine Learning Models in Classification of Students’ Academic Performance. by Hussein, Alkattan, Alhumaima, Ali Subhi, Oluwaseun, Adelaja A., Abotaleb, Mostafa, Mijwil, Maad M., Pradeep, Mishra, Sekiwu, Denis, Bamwerinde, Wilson, Turyasingura, Benson

“…Special emphasis was placed on the use of algorithms such as decision trees. The study includes an analysis of factors that affect students' academic performance such as previous academic achievement in educational activities, as well as social and psychological factors. …”
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RADAR-AD: assessment of multiple remote monitoring technologies for early detection of Alzheimer’s disease by Manuel Lentzen, Srinivasan Vairavan, Marijn Muurling, Vasilis Alepopoulos, Alankar Atreya, Merce Boada, Casper de Boer, Pauline Conde, Jelena Curcic, Giovanni Frisoni, Samantha Galluzzi, Martha Therese Gjestsen, Mara Gkioka, Margarita Grammatikopoulou, Lucrezia Hausner, Chris Hinds, Ioulietta Lazarou, Alexandre de Mendonça, Spiros Nikolopoulos, Dorota Religa, Gaetano Scebba, Pieter Jelle Visser, Gayle Wittenberg, Vaibhav A. Narayan, Neva Coello, Anna-Katharine Brem, Dag Aarsland, Holger Fröhlich, on behalf of RADAR-AD

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Prediksi Kesiapan Sekolah Menggunakan Machine Learning Berbasis Kombinasi Adam dan Nesterov Momentum by Indah Mustika Rahayu, Ahmad Yusuf, Mujib Ridwan

“…The research used Artificial Neural Network algorithms with a combination of Adam and Nesterov Momentum optimization method. …”
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An Arctic sea ice concentration data record on a 6.25 km polar stereographic grid from 3 years of Landsat-8 imagery by H.-S. Jung, S.-M. Lee, S.-M. Lee, J.-H. Kim, K. Lee

“…However, the fundamental basis of algorithms for estimating SIC has not improved much since the early days due to the lack of reference SIC data, leading to discrepancies between existing PMW SIC algorithms. …”
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Development and Validation of a Cost-Effective Machine Learning Model for Screening Potential Rheumatoid Arthritis in Primary Healthcare Clinics by Wu W, Hu X, Yan L, Li Z, Li B, Chen X, Lin Z, Zeng H, Li C, Mo Y, Wu Y, Wang Q

“…Using 10 classical machine learning algorithms, we developed screening models. Evaluation metrics determined the best model. …”
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A Detection Method Against Load Redistribution Attacks in the Interdependence of the Natural Gas Network and Power System Based on Entropy by Yaoying Wang

“…Instead of relying on deep learning algorithms, this study leverages entropy-based techniques for attack detection. …”
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Angular and CP-Violation Analyses of B-→D⁎+l-ν-l Decays at Hadron Collider Experiments by Daniele Marangotto

“…This article proposes the measurement of B-→D⁎+l-ν-l angular and CP-violating observables at hadron collider experiments, by exploiting approximate reconstruction algorithms using information from detectable final-state particles only. …”
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A Computational Complexity-Based Method for Predicting Scholars’ Ages through Articles’ Information by Jun Zhang, Xiaoyan Su, Mingliang Hou, Jing Ren

“…Our method first classifies factors that affect scholars’ ages into intuitive and complex types according to their computational complexity and then apply machine learning algorithms to predict the ages of scholars based on these factors. …”
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Growth Rates of  Morphometric Variables in Approximately Linear Sections Using Lines in R3 by Aquiles E. Darghan, Enrique Quevedo García, Sergio Esteban Gamboa Muñoz, Carlos Armando Rivera Moreno

“…In this research, different classification algorithms are applied to select the approximately linear phase present in various nonlinear models of variables or parameters used in the modeling of the growth of a crop. …”
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