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   Neurocomputing in civil infrastructure  
   
نویسنده amezquita-sanchez j.p. ,valtierra-rodriguez m. ,aldwaik m. ,adeli h.
منبع scientia iranica - 2016 - دوره : 23 - شماره : 6-A - صفحه:2417 -2428
چکیده    This article presents a review of the recent applications of artificial neural networks (ann) for civil infrastructure including structural system identification, structural health monitoring, structural vibration control, structural design and optimization, prediction applications, construction engineering, and geotechnical engineering. the most common ann used in structural engineering is the backpropagation neural network followed by recurrent neural networks and radial basis function neural networks. in recent years, a number of researchers have used newer hybrid techniques in structural engineering such as the neuro-fuzzy inference system, time-delayed neuro-fuzzy inference system, and wavelet neural networks. deep machine learning techniques are among the newest techniques to find applications in civil infrastructure systems.
کلیدواژه Artificial neural networks; Civil structures; System identification; Structural health monitoring; Control; Prediction; Optimization; Construction; Geotechnical
آدرس autonomous university of queretaro, campus san juan del rio, faculty of engineering, departments of electromechanical, civil, and biomedical engineering, Mexico, autonomous university of queretaro, campus san juan del riofaculty of engineering, departments of electromechanical, civil, and biomedical engineering, Mexico, ohio state university, department of civil, environmental, and geodetic engineering, USA, ohio state university, department of civil, environmental, and geodetic engineering, USA
پست الکترونیکی adeli.1@osu.edu
 
     
   
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