Results 121 to 130 of about 8,464,096 (315)
Performance Optimal PI controller Tuning Based on Integrating Plus Time Delay Models
Algorithms, 2018 A method for tuning PI controller parameters, a prescribed maximum time delay error or a relative time delay error is presented. The method is based on integrator plus time delay models.
Christer Dalen, David Di Ruscio
doaj +1 more source
Advanced Engineering Materials, EarlyView.Iron‐based metallic glass alloys exhibit excellent soft‐magnetic properties, and unprecedented geometrical freedom in the design of soft‐magnetic metallic glass components is made possible by additive manufacturing. An efficient workflow for developing parameters for laser‐based powder bed fusion of a Fe‐based metallic glass alloy is presented along ...
Julia Löfstrand +7 more
wiley +1 more source
IMPLEMENTATION OF PROPHET IN AMERICAN ELECTRICITY FORECASTING WITH AND WITHOUT PARAMETER TUNING
Media StatistikaProphet is one of the machine learning approximation methods that accommodate trends, seasonality, and holiday impacts in time series data. Generally, the performance of machine learning models can be improved by implementing hyperparameter tuning.
Winita Sulandari +4 more
doaj +1 more source
A Workflow to Accelerate Microstructure‐Sensitive Fatigue Life Predictions
Advanced Engineering Materials, EarlyView.This study introduces a workflow to accelerate predictions of microstructure‐sensitive fatigue life. Results from frameworks with varying levels of simplification are benchmarked against published reference results. The analysis reveals a trade‐off between accuracy and model complexity, offering researchers a practical guide for selecting the optimal ...
Luca Loiodice +2 more
wiley +1 more source
Tuning parameters in random forests [PDF]
ESAIM: Proceedings and Surveys, 2017 Summary: \textit{L. Breiman}'s [Mach. Learn. 45, No. 1, 5--32 (2001; Zbl 1007.68152)] random forests are a very popular class of learning algorithms often able to produce good predictions even in high-dimensional frameworks, with no need to accurately tune its inner parameters.
openaire +3 more sources
Advanced Engineering Materials, EarlyView.Curvature‐tuned auxetic lattices are designed, fabricated, and mechanically characterized to reveal how geometric curvature governs stretchability, stress redistribution, and Poisson's ratio evolution. Photoelastic experiments visualize stress pathways, while hyperelastic simulations quantify deformation mechanics.
Shuvodeep De +3 more
wiley +1 more source
Advanced Engineering Materials, EarlyView.In this experimental study, the mechanical properties of additively manufactured Ti‐6Al‐4V lattice structures of different geometries are characterized using compression, four point bending and fatigue testing. While TPMS designs show superior fatigue resistance, SplitP and Honeycomb lattice structures combine high stiffness and strength. The resulting
Klaus Burkart +3 more
wiley +1 more source
Parameter Tuning Method of Active Disturbance Rejection Controller for AUVs Based on VRFT
水下无人系统学报Active disturbance rejection control(ADRC) is model-independent and exhibits strong robustness against disturbances, effectively addressing the uncertainties of autonomous undersea vehicle(AUV) models and complex external environments. However, parameter
Xiaodong HOU, Rui YANG, Ming LI
doaj +1 more source
Can Ti‐Based MXenes Serve as Solid Lubricants for Brake Applications? A Tribological Study
Advanced Engineering Materials, EarlyView.This study explores the first implementation of Ti‐based MXenes materials in brake pad friction composite material. The resulting composite material exhibits a 48% reduction in the wear rate; alongside significant improvements are observed for thermal and mechanical properties.
Eslam Mahmoud +7 more
wiley +1 more source