Chaotic Behaviors and Coexisting Attractors in a New Nonlinear Dissipative Parametric Chemical Oscillator by Y. J. F. Kpomahou, A. Adomou, J. A. Adéchinan, A. E. Yamadjako, I. V. Madogni

“…The performed numerical simulations confirm the obtained analytical predictions. Second, the prediction of coexisting attractors is investigated by solving numerically the new nonlinear parametric ordinary differential equation via the fourth-order Runge–Kutta algorithm. …”
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The Multiobjective Based Large-Scale Electric Vehicle Charging Behaviours Analysis by Yimin Zhou, Zhifei Li, Xinyu Wu

“…The residential traveling historical data of EVs are analyzed and fitted to predict their probability distribution, so that the models of the traveling patterns can be established. …”
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An Early Warning Method of Unbalanced Power Battery Capacity Attenuation Based on ARIMA Model by KANG Zuchao, XIONG Gang, WANG Wenming, ZHONG Xiongwu, ZHOU Yanhui

“…It is of important significance to study a timely warning algorithm of the unbalance of power battery capacity attenuation. …”
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Research on Soft-Sensing Methods for Measuring Diene Yields Using Deep Belief Networks by Xiangwu Deng, Zhiping Peng, Delong Cui

“…Motivated by this, this article has studied soft-sensing technology for measuring diene yields. A diene yield prediction method based on a deep belief network algorithm network is proposed, and the regularity of historical diene yield data is fully explored by the method. …”
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ADAPTIVE QUASICONTINUUM SIMULATION OF ELASTIC-BRITTLE DISORDERED LATTICES by Karel Mikeš, Milan Jirásek

“…In this work, the QC method is combined with an adaptive algorithm, to obtain correct predictions of crack trajectories in failure simulations. …”
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Optimization of Adversarial Reprogramming for Transfer Learning on Closed Box Models by Alexander Bott, Moritz Siems, Alexander Puchta, Jurgen Fleischer

“…In this work, we optimise a transfer learning approach for predicting the Remaining Useful Life (RUL) of ball bearings, particularly in scenarios with limited data availability. …”
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sedInterFoam 1.0: a three-phase numerical model for sediment transport applications with free surfaces by A. Mathieu, Y. Kim, T.-J. Hsu, C. Bonamy, J. Chauchat

“…Using sedInterFoam, four test cases are successfully reproduced to validate the free-surface evolution algorithm's implementation, mass conservation of sediment and fluid phases, and predictive capabilities and to demonstrate its potential in modeling a broader range of coastal applications with sediment transport dominated by surface waves.…”
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Integration of Accelerometers and Machine Learning with BIM for Railway Tight- and Wide-Gauge Detection by Jessada Sresakoolchai, Chayutpong Manakul, Ni-Asri Cheputeh

“…These data are processed and analyzed using supervised machine-learning algorithms to classify and predict potential tight- and wide-gauge events. …”
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An accuracy-privacy optimization framework considering user’s privacy requirements for data stream mining by Waruni Hewage, R. Sinha, M. Asif Naeem

“…Additionally, a data fitting module using kernel regression is integrated, a unique approach that predicts accuracy levels based on user-defined privacy thresholds. …”
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Design of Trabecular Bone Mimicking Voronoi Lattice-Based Scaffolds and CFD Modelling of Non-Newtonian Power Law Blood Flow Behaviour by Haja-Sherief N. Musthafa, Jason Walker

“…A Finite Element Method-based computational fluid dynamics (CFD) simulation was performed on all designed Voronoi scaffolds to predict the pressure drops and permeability of non-Newtonian blood flow behaviour using the power law material model. …”
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Gaussian Process Regression and Machine Learning Methods for Carbon-Based Material Adsorption by Manar Ahmed Hamza, Maha M. Althobaiti, Fahd N. Al-Wesabi, Rana Alabdan, Hany Mahgoub, Anwer Mustafa Hilal, Abdelwahed Motwakel, Mesfer Al Duhayyim

“…In the existing system, random forest and ANN methods were used for TC and SMX for predicting the quantities of antibiotics in the CBMs. …”
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Topology aware multitask cascaded U-Net for cerebrovascular segmentation. by Pierre Rougé, Nicolas Passat, Odyssée Merveille

“…This loss requires computing the skeletons of both the manual annotation and the predicted segmentation in a differentiable way. Currently, differentiable skeletonization algorithms are either inaccurate or computationally demanding. …”
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Higgs boson production in association with massive bottom quarks at NNLO+PS by Christian Biello, Javier Mazzitelli, Aparna Sankar, Marius Wiesemann, Giulia Zanderighi

“…We present an extensive phenomenological analysis both at the inclusive level and considering bottom jets using flavour-tagging algorithms. By comparing four-flavour and five-flavour scheme predictions at NNLO+PS, we find that the NNLO corrections in the four-flavour scheme resolve the long-standing tension between the two schemes. …”
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Proteína LIC10494 de Leptospira interrogans serovar Copenhageni: modelo estructural y regiones funcionales asociadas by Orlando Emilio Acevedo, George Emílio Barreto, Janneth González-Santos

“…Protein LIC10494 of Leptospira interrogans serovar Copenhageni: structural model and associated functional regions. Objective.Predict by computational means the 3D structure of the antigenic protein LIC10494 and report associated important functional regionsfor its pathogenicity and immunogenicity. …”
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Towards Machine Learning-Driven Catalyst Design and Optimization of Operating Conditions for the Production of Jet Fuel Via Fischer-Tropsch Synthesis by Parisa Shafiee, Bogdan Dorneanu, Harvey Arellano-Garcia

“…The random forest ML algorithm was evaluated for predicting CO conversion and C8-C16 selectivity using this dataset. …”
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Challenges of International Trade and Government Governance from the Perspective of Economic Globalization by Dan Ge

“…On the basis of expounding the particle swarm optimization algorithm and GMDH algorithm, the optimization mode, method, and process of GMDH network based on particle swarm optimization are also expounded. …”
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Blind Direction-of-Arrival Estimation with Uniform Circular Array in Presence of Mutual Coupling by Song Liu, Lisheng Yang, Shizhong Yang, Qingping Jiang, Haowei Wu

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A Novel Admixture-Based Pharmacogenetic Approach to Refine Warfarin Dosing in Caribbean Hispanics. by Jorge Duconge, Alga S Ramos, Karla Claudio-Campos, Giselle Rivera-Miranda, Luis Bermúdez-Bosch, Jessicca Y Renta, Carmen L Cadilla, Iadelisse Cruz, Juan F Feliu, Cunegundo Vergara, Gualberto Ruaño

“…<h4>Results</h4>The admixture-adjusted, genotype-guided warfarin dosing refinement algorithm developed in Caribbean Hispanics showed better predictability (R2 = 0.70, MAE = 0.72mg/day) than a clinical algorithm that excluded genotypes and admixture (R2 = 0.60, MAE = 0.99mg/day), and outperformed two prior pharmacogenetic algorithms in predicting effective dose in this population. …”
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Machine Learning Modeling of Disease Treatment Default: A Comparative Analysis of Classification Models by Michael Owusu-Adjei, James Ben Hayfron-Acquah, Frimpong Twum, Gaddafi Abdul-Salaam

“…The focus on contextual nonbiomedical measurements using a supervised machine learning modeling technique is aimed at creating an understanding of the reasons why treatment default occurs, including identifying important contextual parameters that contribute to treatment default. The predicted accuracy scores of four supervised machine learning algorithms, namely, gradient boosting, logistic regression, random forest, and support vector machine were 0.87, 0.90, 0.81, and 0.77, respectively. …”
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Coverage Restoration Method for Wireless Sensor Networks of Distributed PV System by Zhixin Fu, Zhen Liu, Yue Yuan, Min Zhao, Qiaomu Li

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