The use of neural network to predict the behavior of small plastic pipes embedded in reinforced sand and surface settlement under repeated load

Engineering Applications of Artificial Intelligence

Volumn 21, Issue 6, 2008, Pages 883-894

  Moghaddas Tafreshi, S N ^a   Tavakoli Mehrjardi, Gh ^a  

^a K N TOOSI UNIVERSITY OF TECHNOLOGY   (Iran)

Author keywords

Buried pipe; Neural network; Settlement of soil surface; Soil reinforcement; Vertical diametral strain

Indexed keywords

DIGITAL SIGNAL PROCESSING; GEOLOGIC MODELS; IMAGE CLASSIFICATION; LOADS (FORCES); MILITARY OPERATIONS; PIPE; PLASTIC PIPE; PLASTICS; SAND;

APPLIED (CO); BACK-PROPAGATION NEURAL NETWORK MODEL (BPM); EMBEDMENT DEPTH; EXPERIMENTAL DATA; FEED FORWARD (FF); FLEXIBLE PIPES; HEAVY VEHICLES; HIGH-DENSITY POLYETHYLENE (HDPE); INPUT LAYERS; OUTPUT LAYERS; REINFORCED LAYERS; REINFORCED SAND; RELATIVE DENSITIES; REPEATED LOADS; SMALL DIAMETER; SOIL SURFACES; SURFACE SETTLEMENTS; VERTICAL DEFORMATION;

NEURAL NETWORKS;

EID: 46349095126     PISSN: 09521976     EISSN: None     Source Type: Journal    
DOI: 10.1016/j.engappai.2007.09.001     Document Type: Article

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