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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Seismic Failure Probability of a Curved Bridge Based on Analytical and Neural Network Approaches by K. Karimi-Moridani, P. Zarfam, M. Ghafory-Ashtiany

“…This study focuses on seismic fragility assessment of horizontal curved bridge, which has been derived by neural network prediction. The objective is the optimization of structural responses of metaheuristic solutions. …”
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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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Knowledge management system as a basis for smart learning by Natalia V. Dneprovskaya

“…However, the issues of the content of education become most relevant. Research in the field of knowledge management remain relevant because, the more perfect the technologies become, that notice the algorithmized work of specialists, the higher the value of creativity for society and the economy.Materials and methods of research include discourse analysis of domestic and foreign scientific sources devoted to the issues of smart education and knowledge management, the systematization of the material. …”
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Ensemble machine learning model for forecasting wind farm generation by A. G. Rusina, Osgonbaatar Tuvshin, P. V. Matrenin, N. N. Sergeev

“…Thus, to ensure the normal operating modes of the energy system, it is necessary to predict the generation of renewable sources with an acceptable error.   …”
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Modeling Techniques and Boundary Conditions in Abdominal Aortic Aneurysm Analysis: Latest Developments in Simulation and Integration of Machine Learning and Data-Driven Approaches by Burcu Ramazanli, Oyku Yagmur, Efe Cesur Sarioglu, Huseyin Enes Salman

“…High-fidelity hemodynamic and biomechanical predictions are essential for clinicians to optimize preoperative planning and minimize therapeutic risks. …”
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Multi-omics analysis untangles the crosstalk between intratumor microbiome, lactic acid metabolism and immune status in lung squamous cell carcinoma by Xun Qiu, Dan Li

“…Moreover, the histopathology image-based deep learning model accurately predicted our LM-based LUSC taxonomy, significantly improving its clinical utility. …”
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Evaluating the strength properties of high-performance concrete in the form of ensemble and hybrid models using deep learning techniques by Zhe Wang, Tao Sun, Yan Sun, Na Liu

“…Deep learning techniques, including hybrid and ensemble methods, were developed to predict these properties with high accuracy. This paper focuses on forecasting models using T-SFIS, GBMBoost, and Decision Tree, combined with metaheuristic algorithms (GWO, QPSO) in hybrid and ensemble frameworks. …”
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A novel ensemble support vector machine model for land cover classification by Ying Liu, Lihua Huang

“…We then combined finally individual prediction through AdaBoost algorithm to induce the final classification results on this new training set. …”
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Hybrid Energy Management of Solid Oxide Fuel Cell/Lithium Battery System by Dong Li, Xiaobo Zhong, Yuanwu Xu, Chongyang Wei, Song Zhao, Jianhua Jiang, Zhonghua Deng, Xiaowei Fu, Xi Li

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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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Snake-inspired trajectory planning and control for confined pipeline inspection with hyper-redundant manipulators by Junjie Zhu, Mingming Su, Longchuan Li, Yuxuan Xiang, Jianming Wang, Xuan Xiao

“…To address this issue, a pipeline inspection approach that combines nonlinear model predictive control (NMPC) with the snake-inspired crawling algorithm(SCA) is proposed. …”
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Sensitivity Analysis of Unmanned Aerial Vehicle Composite Wing Structural Model Regarding Material Properties and Laminate Configuration by Artur Kierzkowski, Jakub Wróbel, Maciej Milewski, Angelos Filippatos

“…A Multi-Objective Genetic Algorithm (MOGA), well suited for complex engineering problems, was employed alongside Design of Experiments to develop a precise response surface model, achieving predictive errors of 0% for mass and 2.99% for frequency. …”
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Trustworthiness Assessment for Crowdsourcing-Based Citywide Parking Availability Sensing via Connected and Automated Vehicles by Shiyu Wang, Cong Zhao, Zekai Wang, Yupeng Shi, Shengchuan Jiang, Yuchuan Du

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Estimating comprehensive growth index for drip-irrigated spring maize in junggar basin via satellite imagery and machine learning by Mingjie Ma, Jinghua Zhao, Tingrui Yang, Feng Liu, Yingying Yuan, Shijiao Ma, Zikang Chang

“…The total stage model significantly outperformed the single growth stage models in CGI prediction, yielding R2 values between 0.982 and 0.994. …”
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Advanced Solar Irradiance Forecasting Using Hybrid Ensemble Deep Learning and Multisite Data Analytics for Optimal Solar-Hydro Hybrid Power Plants by Sudharshan Konduru, Naveen C., Jagabar Sathik M.

“…A novel hybrid decomposed residual ensembling model for deep learning (SBLTSRARW) using models such as autoregressive integrated moving average (ARIMA) and seasonal-trend decomposition using loess (STL) along with prediction and optimization models such as Bidirectional LSTM (Bi-LSTM), and Whale Optimization Algorithm (WOA) methods are used to predict the irradiances. …”
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