Performance-based optimum seismic design of steel structures by a modified firefly algorithm and a new neural network

2015 ◽  
Vol 81 ◽  
pp. 50-65 ◽  
Author(s):  
Saeed Gholizadeh
Keyword(s):  
Neural Network ◽  
Seismic Design ◽  
Firefly Algorithm ◽  
Steel Structures ◽  
Modified Firefly Algorithm

Optimum Seismic Zoning Using An Artificial Neural Network

2016 ◽  
Vol 32 (2) ◽  
pp. 1187-1207 ◽  
Author(s):  
Jaime García-Pérez ◽  
René Riaño
Keyword(s):  
Neural Network ◽  
Artificial Neural Network ◽  
Seismic Design ◽  
Seismic Zoning ◽  
Present Value ◽  
Total Cost ◽  
Structural Types ◽  
Initial Cost ◽  
Different Types ◽  
Artificial Neural

The Kohonen artificial neural network is employed to divide a region of known seismicity into zones. Optimum boundaries and seismic design coefficients for each zone are determined by computing the expected present value of the total cost, including the initial cost of structures and damages due to earthquakes. The region is discretized into cells containing information on seismicity and the number of structural types. Then regionalization is performed, first without considering jurisdictional limits and later including this restriction. Up to four different types of structures are considered simultaneously in the regionalization. The results are presented in maps showing both zones and corresponding seismic design coefficients.

Structural Performance of Automated Multi-Depth Shuttle Warehouses (Amsws) Under Low-to-Moderate Seismic Actions

2021 ◽  
Author(s):  
Aleksei Kondratenko ◽  
Alper Kanyilmaz ◽  
Carlo Andrea Castiglioni ◽  
Francesco Morelli ◽  
Mohsen Kohrangi
Keyword(s):  
Seismic Design ◽  
Brittle Failure ◽  
Structural Characteristics ◽  
Time History ◽  
Steel Structures ◽  
Current Approach ◽  
Structural Performance ◽  
Future Design ◽  
The Future ◽  
Base Connections

Abstract Automated Multi-Depth Shuttle Warehouses (AMSWs) are compact storage systems that provide a large surface occupation and therefore maximum storage density. AMSWs represent the future of storage technology, providing substantial savings in terms of cost, space, and energy with respect to traditional warehouses. Currently, designers refer to the standard building codes for the seismic design of AMSWs. Since structural characteristics of AMSWs are considerably different from the steel structures of typical buildings, this current approach used by designers is questionable in terms of safety and efficiency. In this article, the behavior of 5 AMSW structures has been studied performing 150 time-history analyses by direct integration including P-Delta effects. Demand/capacity ratios calculated for each element showed the dominance of the brittle failure mechanism in AMSWs subjected to low-to-moderate seismic actions. These mechanisms mainly took place in upright columns and their base connections prior to the activation of ductile energy dissipation mechanisms of the structure. Based on the results, further improvements have been recommended for the future design provisions, which may lead to a safer seismic design of AMSWs.

scholarly journals Optimization of Artificial Neural Network for Stock Market Price Prediction Using an Enhanced Firefly Algorithm

2019 ◽  
Vol 13 (9) ◽  
pp. 532-543
Author(s):  
Ameen Ahmed Oloduowo ◽  
Fashoto Stephen Gbenga ◽  
Ogeh Clement ◽  
Balogun Abdullateef ◽  
Mashwama Petros
Keyword(s):  
Neural Network ◽  
Artificial Neural Network ◽  
Stock Market ◽  
Firefly Algorithm ◽  
Market Price ◽  
Price Prediction ◽  
Artificial Neural
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