AN IMPROVED RANDOM FOREST-MONTE CARLO METHOD AND APPLICATION FOR STRUCTURAL RELIABILITY ANALYSIS OF A-TYPE INDEPENDENT LIQUID TANK SUPPORT STRUCTURE

An improved random forest-Monte Carlo method and application for structural reliability analysis of A-type independent liquid tank support structure

ObjectivesIn response to the increasing depth of research and design on liquefied natural gas (LNG) ship structures, higher requirements are put forward for a reliability analysis method that can quickly and accurately evaluate uncertain factors.This paper proposes a method based on an improved random forest-Monte Carlo method (RF-MC) to solve the

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The Interactions Between Digitalization, Innovation and Employment in European Companies: Insights from a Latent Class Analysis

There is increasing concern regarding the association between technological change and jobs.This study explores how different patterns of digitalization and innovation relate to job creation in European companies.We use data from the European Company Survey 2019 collected by Eurofound and Cedefop.We apply Latent Class Analysis (LCA) to identify the

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Edge of Chaos in Memristor Cellular Nonlinear Networks

Information processing Hose Extension Kit in the brain takes place in a dense network of neurons connected through synapses.The collaborative work between these two components (Synapses and Neurons) allows for basic brain functions such as learning and memorization.The so-called von Neumann bottleneck, which limits the information processing capabi

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