Robust Design Optimization of Viscoelastic Damped Composite Structures Integrating Model Order Reduction and Generalized Stochastic Collocation by Tianyu Wang, Chao Xu, Teng Li

“…Pareto optimal solutions are determined by combining the proposed MOR and gSC approaches with a well-established Non-dominated Sorting Genetic Algorithm II (NSGA-II) algorithm, which accounts for robustness in handling design variables, objectives, and constraints. …”
Get full text

An Online Tool for Correcting Performance Measures of Electronic Phenotyping Algorithms for Verification Bias by Ajay Bhasin, Sue Bielinski, Abel N. Kho, Nicholas Larson, Laura J. Rasmussen-Torvik

“… Objectives Computable or electronic phenotypes of patient conditions are becoming more commonplace in quality improvement and clinical research. During phenotyping algorithm validation, standard classification performance measures (i.e., sensitivity, specificity, positive predictive value, negative predictive value, and accuracy) are often employed. …”
Get full text

Performance comparison of machine learning algorithms for condition monitoring of tapered roller bearings by Harshal Aher, Nilesh Ghuge

“…This paper investigated the implementation of machine learning algorithms for health monitoring and fault detection of tapered roller bearings (TRBs) (30205 J2/Q, 30206 J2/Q and 30207 J2/Q). …”
Get full text

MODELLING FLUCTUATIONS OF GROUNDWATER LEVEL USING MACHINE LEARNING ALGORITHMS IN THE SOKOTO BASIN by Samson Alfa, Haruna Garba, Augustine Odeh

“…Among the models, the XGBoost algorithm demonstrated the highest performance, providing precise predictions that closely aligned with the actual groundwater levels. …”
Get full text

Mahalanobis distance–based kernel supervised machine learning in spectral dimensionality reduction for hyperspectral imaging remote sensing by Jing Liu, Yulong Qiao

“…Spectral dimensionality reduction is a crucial step for hyperspectral image classification in practical applications. …”
Get full text

An Approach to Data Reduction for Learning from Big Datasets: Integrating Stacking, Rotation, and Agent Population Learning Techniques by Ireneusz Czarnowski, Piotr Jędrzejowicz

“…We propose to use an agent-based population learning algorithm for data reduction in the feature and instance dimensions. …”
Get full text

Freedom under algorithms: how unpredictable and asocial management erodes free choice by Robert Donoghue

“…This issue is further complicated by the fact that as algorithms become more resilient and useful, their outputs grow increasingly opaque and unpredictable—what some refer to as the resilience-predictability paradox. …”
Get full text

Inverse Design of Broadband Artificial Magnetic Conductor Metasurface for Radar Cross Section Reduction Using Simulated Annealing by Haoda Xia, Xiaoyu Liang, Bowen Jia, Pei Shi, Zhihong Chen, Shi Pu, Ning Xu

“…The experimental results show a significant RCS reduction of 10 dB within the 7.6–15.5 GHz range, with the peak reduction reaching-28 dB at normal incidence. …”
Get full text

Estimating latent heat flux of subtropical forests using machine learning algorithms by Harekrushna Sahu, Pramit Kumar Deb Burman, Palingamoorthy Gnanamoorthy, Qinghai Song, Yiping Zhang, Huimin Wang, Yaoliang Chen, Shusen Wang

“…By harnessing diverse datasets, we employ various machine learning regression algorithms. We find the support vector regression superior to linear, lasso, random forest, adaptive boosting and gradient boosting algorithms. …”
Get full text

Fast optimization of the emission reduction pathways of major air pollutants in China: From the perspective of different decision preferences by Yihao Wang, Xuying Wang, Yixuan Zheng, Zeyuan Liu, Yu Zhang, Jiani Kang, Wenbo Xue, Jing Zhang, Yu Lei

“…Six emission reduction scenarios with varying decision preferences were analyzed. …”
Get full text

Dimensionality cutback and deep learning algorithms efficacy as to the breast cancer diagnostic dataset by Gennady Chuiko, Denys Honcharov

“…The results indicate that the dimensionality of the Wisconsin Breast Cancer dataset, which is increasingly becoming the "gold standard" for diagnosing Malignant-Benign tumors, can be significantly reduced without losing predictive power. The Deep Learning algorithms in WEKA deliver excellent performance for both supervised and unsupervised learning, regardless of whether dealing with full or reduced datasets.…”
Get full text

Peak Arm Current Reduction of Modular Multilevel Converter Based on Particle Swarm Optimizer for Circulating Current Injections by Riyadh Toman Thahab, Tahani Hamodi Al-Mhana

Get full text

Research on Vibration Reduction Method of Nonpneumatic Tire Spoke Based on the Mechanical Properties of Domestic cat’s Paw Pads by Haichao Zhou, Huiyun Li, Ye Mei, Guolin Wang, Congzhen Liu, Lingxin Zhang

“…The three parameters, the asymmetric arc, the thickness, and the curvature of spokes, were used as design variables to maximize the vibration reduction. The orthogonal experimental, the Kriging approximate model, and the genetic algorithm were carefully selected for optimal solutions. …”
Get full text

A brief comparison of algorithms and methods for optimization of electric vehicles charging strategies by Arpita Bharti, Rajeev Kumar Chauhan

Get full text

Security situational awareness of power information networks based on machine learning algorithms by Chao Wang, Jia-han Dong, Guang-xin Guo, Tian-yu Ren, Xiao-hu Wang, Ming-yu Pan

“…To properly predict the security posture of these networks, we provide a method based on machine learning algorithms to detect the security condition of power information networks. …”
Get full text

Performance of machine learning algorithms to evaluate the physico-mechanical properties of nanoparticle panels by Derrick Mirindi, James Hunter, David Sinkhonde, Tajebe Bezabih, Frederic Mirindi

“…This review analyzes secondary data on nanoparticle integration in board production, aiming to evaluate the relationships among physical (water absorption (WA) and thickness swelling (TS)) and mechanical (modulus of rupture (MOR), modulus of elasticity (MOE); and internal bond (IB) strength) properties and to predict performance using machine learning (ML) algorithms. …”
Get full text

Exploring the limits of scan time reduction for ferumoxytol-enhanced whole-heart angiography in congenital heart disease patients by Ludovica Romanin, Milan Prsa, Christopher W. Roy, Xavier Sieber, Jérôme Yerly, Bastien Milani, Tobias Rutz, Salim Si-mohamed, Estelle Tenisch, Davide Piccini, Matthias Stuber

Get full text

THE TECHNIQUE OF THE COMPARATIVE ANALYSIS OF THE ROUTE TRACKING INFORMATION ALGORITHMS DURING THE TERTIARY PROCESSING by A. A. Belous

Get full text

A Methodology for Evaluating Algorithms That Calculate Social Influence in Complex Social Networks by Vanja Smailovic, Vedran Podobnik, Ignac Lovrek

“…However, these approaches introduce uncertainty in calculating (i.e., predicting) the value of social influence. Hence, a methodology is proposed for evaluating algorithms that calculate social influence in complex social networks; this is done by identifying the most accurate and precise algorithm. …”
Get full text

Multi-objective-based economic dispatch and loss reduction in the presence of electric vehicles considering different optimization techniques by David Hmingthanmawia, Subhasish Deb, Subir Datta, Ksh. Robert Singh, Umit Cali, Umit Cali, Taha Selim Ustun

“…The multi-objective grasshopper optimization algorithm and the ant-lion optimization are compared to observe the minimum cost and total loss of the system. …”
Get full text