scholarly journals Prediction of Critical Distance Between Two MDOF Systems Subjected to Seismic Excitation in Terms of Artificial Neural Networks

2017 ◽  
Author(s):  
Hosein Naderpour ◽  
Seyed Mohammad Khatami ◽  
Rui Carneiro Barros
Keyword(s):  
Neural Networks ◽  
Artificial Neural Networks ◽  
Separation Distance ◽  
Critical Distance ◽  
Building Codes ◽  
Seismic Excitation ◽  
Gap Size ◽  
Mdof Systems ◽  
Lateral Displacements ◽  
New Equation

This study focuses on preventing collisions between structuresduring seismic excitation based on gap size. Several approximatedequations in order to estimate separation distancebetween buildings are collected and evaluated to measure gapsize in order to avoid impact between them when large lateraldisplacements occurred due to earthquake. Artificial neuralnetworks are utilized to estimate the required distance betweenstructures. The majority of building codes suggest separationdistances based on maximum lateral displacements of eachbuilding or height of buildings in order to provide safety gapsize between them. Subsequently, researchers have proposedseveral equations to predict the critical distance. In currentstudy, some MDOF models are equivalently modelled and optimumgap size between buildings is approximately estimatedand finally a new equation for separation distance is suggestedand the accuracy of formula is numerically investigated.

scholarly journals Critical distance between two irregular adjacent buildings in order to prevent collision during earthquake

2021 ◽  
Author(s):  
Yaghub Ebrahimi ◽  
◽  
Ali Hemmati ◽  
Ali Reza Mortezaei ◽  
Mahmud Nikkhah Shahmirzadi ◽  
...  
Keyword(s):  
Neural Network ◽  
Lateral Displacement ◽  
Critical Distance ◽  
Gap Size ◽  
Story Model ◽  
Adjacent Buildings ◽  
Mathematical Equations ◽  
Lateral Displacements ◽  
The Impact ◽  
Tabas Earthquake

The aim of this study is to evaluate the value of suitable distance due to prevent the impact between two irregular adjacent buildings when earthquake is caused to occur large lateral displacement and damage the elements of buildings. For this purpose, by using a mathematical program based on neural network, the number of stories, the period and height of investigated models, PGD, PGV and PGA of earthquake records are defined and the nonlinear lateral displacements of different structures are determined in order to use in the program. Thus, the results of displacements based on all inputs are listed and the minimum critical distance is approximately estimated based on especial regression. For instance, a 3-4 story model is numerically investigated by Tabas earthquake record, which is suggested to provide required gap size about 70 cm. In fact, each model has to observe a 35 cm gap. A newly developed program based on mathematical equations are applied for determining the lateral displacements of each story. A new mathematical formula is proposed by neural network, which shows the least distance between irregular adjacent buildings. For investigating the accuracy of formula, two different ways are performed and the results of analyses confirm suggested equation. For this challenge, a 2-4 story model is considered and three different critical distances are calculated to be 59, 62 and 75 cm which show the last gap size is able to provide safety gap size, determined by suggested formula.

FUTURE OF ARTIFICIAL NEURAL NETWORKS IN SPACE EXPLORATION AND SPACE ENGINEERING

2018 ◽  
pp. 6-11
Author(s):  
Kobiljon Kh. Zoidov ◽  
◽  
Svetlana V. Ponomareva ◽  
Daniel I. Serebryansky ◽  
◽  
...  
Keyword(s):  
Neural Networks ◽  
Artificial Neural Networks ◽  
Space Exploration ◽  
Artificial Neural

Bankruptcy Prediction Models: A Bet on Artificial Neural Networks

2012 ◽  
Vol 3 (2) ◽  
pp. 48-50
Author(s):  
Ana Isabel Velasco Fernández ◽  
◽  
Ricardo José Rejas Muslera ◽  
Juan Padilla Fernández-Vega ◽  
María Isabel Cepeda González
Keyword(s):  
Neural Networks ◽  
Artificial Neural Networks ◽  
Prediction Models ◽  
Bankruptcy Prediction ◽  
Artificial Neural
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