Results 81 to 90 of about 95,139 (292)

What to Make and How to Make It: Combining Machine Learning and Statistical Learning to Design New Materials

Advanced Intelligent Discovery, EarlyView.
Combining machine learning and probabilistic statistical learning is a powerful way to discover and design new materials. A variety of machine learning approaches can be used to identify promising candidates for target applications, and causal inference can help identify potential ways to make them a reality.
Jonathan Y. C. Ting, Amanda S. Barnard
wiley   +1 more source

THE SEQUENTIAL ESTIMATION OF SUBSET VAR WITH FORGETTING FACTOR AND INTERCEPT VARIABLE

International Journal of Theoretical and Applied Finance, 2004
In this paper we propose a forward time update algorithm to recursively estimate subset vector autoregressive models (including an intercept term) with a forgetting factor, using the exact window case. The proposed recursions cover, for the first time, subset vector autoregressive models (VAR) with a forgetting factor and an intercept variable. We then
O'Neill, Terence, Penm, Jammie H C, Terrell, Richard   +2 more
openaire   +2 more sources

Adaptive Disturbance Torque Estimation for Orbiting Spacecraft Using Recursive Least-Squares Methods [PDF]

This paper develops a novel disturbance torque estimator for an orbiting spacecraft by using the adaptive least-squares parameter estimation technique. The disturbance estimation is first formulated as an adaptive least-squares minimization problem using
Nguyen, Nhan T., Swei, Sean Shan-Min
core   +1 more source

Deep Learning Prediction of Surface Roughness in Multi‐Stage Microneedle Fabrication: A Long Short‐Term Memory‐Recurrent Neural Network Approach

Advanced Intelligent Discovery, EarlyView.
A sequential deep learning framework is developed to model surface roughness progression in multi‐stage microneedle fabrication. Using real‐world experimental data from 3D printing, molding, and casting stages, an long short‐term memory‐based recurrent neural network captures the cumulative influence of geometric parameters and intermediate outputs ...
Abdollah Ahmadpour, Sara Soltanabadi Farshi, Tuanna Ozcan, Amir Mohammad Ketabchi, Alper Kiraz, Savas Tasoglu   +5 more
wiley   +1 more source

Attitude Control System Design for CubeSats Configured with Exo-Brake Parachute [PDF]

This paper develops a novel attitude control strategy for an Earth orbiting CubeSat spacecraft by utilizing the exo-brake parachute to modulate the atmospheric drag forces as a source of attitude control authority, enabling orbital exo-sail maneuvers. In
Swei, Sean Shan-Min, Westfall, Alexander J.   +1 more
core   +1 more source

Advances in Thermal Modeling and Simulation of Lithium‐Ion Batteries with Machine Learning Approaches

Advanced Intelligent Discovery, EarlyView.
Heat generation in lithium‐ion batteries affects performance, aging, and safety, requiring accurate thermal modeling. Traditional methods face efficiency and adaptability challenges. This article reviews machine learning‐based and hybrid modeling approaches, integrating data and physics to improve parameter estimation and temperature prediction ...
Qi Lin, Kang Fu, Junjie Ding, Kai Sun, Peng Tan   +4 more
wiley   +1 more source

Adaptive thermal error prediction for CNC machine tool spindle using online measurement and an improved recursive least square algorithm

Case Studies in Thermal Engineering
Establishing models for predicting and compensating for spindle thermal errors is cost-effective and necessary to improve the accuracy of machine tools for smart manufacturing.
Xinyuan Wei, Honghan Ye, Gao Wang, Weidong Hu   +3 more
doaj   +1 more source

A Multimodal Intelligent System for Human Digital Twin Simulation with Continuous Kinematic Data Tracking, Biometric Prognosis, and Cognitive State Feedback in Industrial Environments

Advanced Intelligent Discovery, EarlyView.
This article implements a unified human digital twin framework that integrates cutting edge actuation, sensing, simulation, and bidirectional feedback capability. The approach includes integrating multimodal sensing, AI, and biomechanical simulation into one compact system.
Tajbeed Ahmed Chowdhury, Sebastian Gratz‐Kelly, Eric Wagner, Paul Motzki, Martina Lehser   +4 more
wiley   +1 more source

Evaluation of power system inertia based on recursive least squares with variable forgetting factors

电力工程技术
With the integration of large-scale renewable energy and the increased electrification of power systems, issues related to the weakening of power system stability due to insufficient inertia levels have become frequent in recent years.
Maoyi ZHOU, Tingyu HUANG, Ziwen LIU, Ziyan DANG, Yunhao XU, Ziyang NIU   +5 more
doaj   +1 more source

VAE+DDPG: An Attention‐Enhanced Variational Autoencoder for Deep Reinforcement Learning‐Based Autonomous Navigation in Low‐Light Environments

Advanced Intelligent Systems, EarlyView.
Variational Autoencoder+Deep Deterministic Policy Gradient addresses low‐light failures of infrared depth sensing for indoor robot navigation. Stage 1 pretrains an attention‐enhanced Variational Autoencoder (Convolutional Block Attention Module+Feature Pyramid Network) to map dark depth frames to a well‐lit reconstruction, yielding a 128‐D latent code ...
Uiseok Lee, Chanhong Hwang, Hyunseok Kang, Yechan Park, Hangwoo Jin, Tuan Anh Nguyen, Eunmi Choi, Dugki Min   +7 more
wiley   +1 more source