General numerical solution of integral equation for long‐range low‐frequency groundwave propagation over irregular terrain by Dan‐Dan Wang, Qi‐Zirui Lu, Chao Han, Yun Fang, Yu‐Rong Pu

“…Numerical results in two surface types, including triangular mountain and actual terrain are used to demonstrate the performance of the presented algorithm. Furthermore, it is ascertained that the non‐physical perturbations at long propagation ranges in the IE predictions are caused by the inherent uniform‐grid schemes of the numerical solution rather than the several approximations in the derivation of the IE form.…”
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METHOD FOR NUMERICAL MODELING OF UNSTEADY SEPARATED FLOW AROUND AIRFOILS MOVING CLOSE TO FLAT SCREEN by T. V. Pogrebnaya, S. D. Shipilov

“…The algorithm is based on the combination of discrete vortex method and turbulent boundary layer equations. …”
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Optimal design of frame structures equipped with viscous dampers using machine learning techniques by Yi Wen, Jianze Wang, Jun Xu, Kaoshan Dai, Yuanfeng Shi, Reza Sharbati

“…The built models achieved an average R2 of 0.955 for the testing dataset, indicating a high level of predictive accuracy. Then, with the target of minimizing seismic responses of the structural system, the developed DP-based optimization algorithm effectively identifies the optimal damper arrangement for the considered three structure cases. …”
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A new approach to K-nearest neighbors distance metrics on sovereign country credit rating

“…The primary objective is to enhance KNN's predictive accuracy by integrating a feature importance mechanism derived from the random forest algorithm, which prioritizes significant features and reduces the impact of less relevant ones, refining the distance computation within KNN. …”
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Channel-Hopping Using Reinforcement Learning for Rendezvous in Asymmetric Cognitive Radio Networks by Dongsup Jin, Minho Jang, Ji-Woong Jang, Gyuyeol Kong

“…This paper addresses the rendezvous problem in asymmetric cognitive radio networks (CRNs) by proposing a novel reinforcement learning (RL)-based channel-hopping algorithm. Traditional methods like the jump-stay (JS) algorithm, while effective, often struggle with high time-to-rendezvous (TTR) in asymmetric scenarios where secondary users (SUs) have varying channel availability. …”
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Application of Digital Twin Technology in Information and Measurement Systems by V. A. Baronova, N. V. Romantsova

“…This information was further used to develop a mathematical and algorithmic support for predicting the state of technological equipment. …”
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Water Level Classification for Detect Flood Disaster Status Using KNN and SVM by Jiwa Akbar, Muchtar Ali Setyo Yudono

“…In this context, the flood disaster classification system uses water surface elevation data from the Water Resources Agency to predict the likelihood of floods using the K-Nearest Neighbors (KNN) Algorithm. …”
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Correlation between shapes and sizes of dentofacial arches and their stable parameters by E. G. Vedeshina, D. A. Domenyuk, S. V. Dmitrienko

“…The study proposed an algorithm for determining the optimised predicted individual parameters of dental arches in people with abnormal shapes and sizes of dentofacial arches. …”
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Load Balancing and Alternative Path Selection in Self-Organized Networks: A Data Plane Approach by Gergely Sarkozi, Peter Voros

“…This paper presents a novel load balancing algorithm tailored for deeply programmable networks, offering a decentralized approach to optimizing packet forwarding and load distribution. …”
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MEDULLARY THYROID CARCINOMA by V. S. Medvedev, P. A. Isayev, A. A. Ilyin, D. Yu. Semin, V. V. Polkin, D. N. Derbugov, S. V. Vasilkov

“…Multicenter trials are required to elaborate a diagnostic algorithm, to define treatment policy, and to predict an outcome.…”
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An Evolutionary Formulation of the Crossing Number Problem by Che Sheng Gan, Wee Chiat Alan Tan, Voon Chet Koo, Kwang Hwai Mak

“…A graph drawing algorithm is presented which results in complete graphs having minimum crossings equal to that of Guy's conjecture. …”
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Gas adsorption meets geometric deep learning: points, set and match by Antonios P. Sarikas, Konstantinos Gkagkas, George E. Froudakis

“…Recently, machine learning (ML) pipelines have been established as the go-to method for large scale screening by means of predictive models. These are typically built in a descriptor-based manner, meaning that the structure must be first coarse-grained into a 1D fingerprint before it is fed to the ML algorithm. …”
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Particle Filter Tracking without Dynamics by Jaime Ortegon-Aguilar, Eduardo Bayro-Corrochano

“…In this paper, an alternative to address people tracking is presented. The proposed algorithm is based in particle filters, but instead of using a dynamical model, it uses background subtraction to predict future locations of particles. …”
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Reconstruction of Wing Structure Deformation Based on Particle Swarm Optimization Ridge Regression by Xinyi Wu, Zhiwei Xu, Jie Zeng

“…To improve the precision, the PSO algorithm is used to optimize the ridge regression parameters and comparative analysis is carried out with the typical structural deformation reconstruction algorithm, such as the KO theoretical method. …”
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Analysis on waypoint-segment routing and performance evaluation for LEO satellite networks by Xin ZHAO, Guang ZHAO, Rui CHEN, Wennai WANG

“…A waypoint-segment routing (WSR) algorithm was proposed.Based on the predictable periodicity of the topological changes of satellite network, the location of satellite waypoints based on the link state of satellite nodes at the current moment was determined by WSR algorithm.The mechanism of flexible planning of packet transmission paths was responded by segment routing to changes in satellite network topology in advance, and a packet transmission path that was not affected by network topology snapshot switch was calculated.Simulation experiment was based on the NS-3, and the optimized link state routing (OLSR) algorithm and the shortest path algorithm were selected to compare with WSR in order to analyze the delay jitter and packet loss rate.It was proved that compared with OLSR, the maximum delay jitter of WSR was reduced by 46 ms and 126 ms respectively in the two scenarios, the packet loss rate was reduced by 30% and 21% respectively, and the problem of packet transmission path interruption caused by topology snapshot switching can be solved.…”
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Integer linear programming for unsupervised training set selection in molecular machine learning by Matthieu Haeberle, Puck van Gerwen, Ruben Laplaza, Ksenia R Briling, Jan Weinreich, Friedrich Eisenbrand, Clémence Corminboeuf

“…Within the context of physics-inspired machine learning (ML) applied to chemistry, we demonstrate the relevance of an ILP formulation to select molecular training sets for predictions of size-extensive properties. We show that our algorithm outperforms existing unsupervised training set selection approaches, especially when predicting properties of molecules larger than those present in the training set. …”
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Optimization of Rituximab Therapy in Adult Patients With PLA2R1-Associated Membranous Nephropathy With Artificial Intelligence by Alexandre Destere, Maxime Teisseyre, Diane Merino, Marion Cremoni, Alexandre O Gérard, Thomas Crepin, Noémie Jourde-Chiche, Daisy Graça, Kévin Zorzi, Céline Fernandez, Vesna Brglez, Sylvia Benzaken, Vincent L.M. Esnault, Sylvain Benito, Milou-Daniel Drici, Barbara Seitz-Polski

“…We developed a machine learning algorithm to predict the risk of underdosing based on patients’ characteristics at rituximab infusion. …”
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Optimisation of Crystallisation Recipe for Varied Cloud Points Characteristics in Palm Oil Fractions by John Ting Zhi Zhang, Jeng Shiun Lim

“…The artificial neural network (ANN), which uses the Levenberg-Marquardt algorithm, serves as an internal model for predicting process output, whereas the genetic algorithm (GA) investigates a wide range of recipe combinations to maximise yield. …”
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How Gait Nonlinearities in Individuals Without Known Pathology Describe Metabolic Cost During Walking Using Artificial Neural Network and Multiple Linear Regression by Arash Mohammadzadeh Gonabadi, Farahnaz Fallahtafti, Judith M. Burnfield

“…Six nonlinear metrics—Lyapunov Exponents based on Rosenstein’s algorithm (LyER), Detrended Fluctuation Analysis (DFA), the Approximate Entropy (ApEn), the correlation dimension (CD), the Sample Entropy (SpEn), and Lyapunov Exponents based on Wolf’s algorithm (LyEW)—were utilized to predict the metabolic cost during walking. …”
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Perceived age estimation from facial image and demographic data in young and middle-aged South Korean adults by Ilkoo Ahn, Younghwa Baek, Bok-Nam Seo, Su Eun Lim, Kyoungsik Jung, Ho Seok Kim, Jeongkyun Kim, Sukyung Lee, Siwoo Lee

“…Thus, this study aimed to propose a novel perceived age estimation algorithm to meet the need for an objective method to predict perceived age. …”
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