Results 51 to 60 of about 63,095 (231)
Effect of Ductile Damage Evolution in Sheet Metal Forming: Experimental and Numerical Investigations [PDF]
, 2010 The numerical simulation based on the Finite Element Method (FEM) is widely used in academic institutes and in the industry. It is a useful tool to predict many phenomena present in the classical manufacturing forming processes such as necking, fracture,
Abbassi, Fethi +4 more
core +1 more source
Machine Learning‐Driven Variability Analysis of Process Parameters for Semiconductor Manufacturing
Advanced Intelligent Systems, EarlyView.This research presents a machine learning approach that integrates nonlinear variation decomposition (NLVD) with statistical techniques to quantify the contribution of individual unit processes to performance and variance of figure of merit (FoM) at the LOT level.
Sinyeong Kang +6 more
wiley +1 more source
EXCHANGE RATE DETERMINATION BY ARTIFICIAL NEURAL NETWORKS: TURKISH CASE
Mehmet Akif Ersoy Üniversitesi İktisadi ve İdari Bilimler Fakültesi Dergisi, 2021 Artificial Neural Networks as one of the Artificial Intelligence applications, which is the leading candidate for the greatest innovation of the century, has been started to be used in solving the complex problems of the economy for a while. Among them,
Ayça Sarıalioğlu Hayali +1 more
doaj +1 more source
Use of Parameter Estimation for Stereolithography Surface Finish Improvement [PDF]
, 2005 In order to improve Stereolithography (SLA) surface finish, a systematic approach based on estimation of process parameters is needed. In this paper, the exposure on a desired SLA build surface is formulated as a function of process parameters.
Rosen, David W., Sager, Benay
core +1 more source
Advanced Intelligent Systems, EarlyView.This study introduces a data‐driven framework that combines deep reinforcement learning with classical path planning to achieve adaptive microrobot navigation. By training a surrogate neural network to emulate microrobot dynamics, the approach improves learning efficiency, reduces training time, and enables robust real‐time obstacle avoidance in ...
Amar Salehi +3 more
wiley +1 more source
Applied Sciences, 2022 This paper presents an analysis of nonsynchronous rotor blade vibrations in the last stage of an LP steam turbine at various condenser pressures. The nonlinear least squares Levenberg–Marquardt method is used in a tip-timing analysis to determine ...
Romuald Rzadkowski +4 more
doaj +1 more source
Parameter estimation of Stochastic Logistic Model : Levenberg-Marquardt Method [PDF]
, 2009 In this paper, we estimate the drift and diffusion parameters of the stochas- tic logisticmodels for the growth of Clostridium Acetobutylicum P262 using Levenberg- Marquardt optimization method of non linear least squares.
Abd. Rahman, Haliza +5 more
core
Enabling Stochastic Dynamic Games for Robotic Swarms
Advanced Intelligent Systems, EarlyView.This paper scales stochastic dynamic games to large swarms of robots through selective agent modeling and variable partial belief space planning. We formulate these games using a belief space variant of iterative Linear Quadratic Gaussian (iLQG). We scale to teams of 50 agents through selective modeling based on the estimated influence of agents ...
Kamran Vakil, Alyssa Pierson
wiley +1 more source
Five planets and an independent confirmation of HD 196885Ab from Lick Observatory [PDF]
, 2009 We present time series Doppler data from Lick Observatory that reveal the presence of long-period planetary companions orbiting nearby stars. The typical eccentricity of these massive planets are greater than the mean eccentricity of known exoplanets ...
Andrew Howard +33 more
core +2 more sources
Online Signature for Attendance Verification System using Levenberg-Marquardt Neural Network [PDF]
, 2015 This work focuses on the application of Levenberg-Marquardt based Back-propagation Neural Network for training features extracted from online signature images.
Adefuminiyi, Morakinyo A. +2 more
core +1 more source