Prediction of effective thermal conductivity of moist porous materials using artificial neural network approach

Building and Environment

Volumn 46, Issue 12, 2011, Pages 2603-2608

  Singh, Ramvir ^a   Bhoopal, R S ^a   Kumar, Sajjan ^a  

^a UNIVERSITY OF RAJASTHAN   (India)

Author keywords

Artificial neural network; Effective thermal conductivity; Moist porous materials; Volume fraction

Indexed keywords

ARTIFICIAL NEURAL NETWORK; ARTIFICIAL NEURAL NETWORK APPROACH; BROYDEN; COMPLEX STRUCTURE; CONJUGATE GRADIENT; EFFECTIVE THERMAL CONDUCTIVITY; EXPERIMENTAL DATA; FEEDFORWARD BACKPROPAGATION; HIDDEN LAYERS; LEVENBERG-MARQUARDT; MOIST POROUS MATERIALS; POROUS SYSTEM; QUASI-NEWTON; THRESHOLD FUNCTIONS; TRAINING ALGORITHMS; TRAINING FUNCTION;

BACKPROPAGATION ALGORITHMS; CONJUGATE GRADIENT METHOD; FORECASTING; MOISTURE METERS; NEURAL NETWORKS; POROSITY; POROUS MATERIALS; STREAM FLOW;

THERMAL CONDUCTIVITY;

ALGORITHM; ARTIFICIAL NEURAL NETWORK; MODELING; POROUS MEDIUM; PREDICTION; THERMAL CONDUCTIVITY;

EID: 79960927834     PISSN: 03601323     EISSN: None     Source Type: Journal    
DOI: 10.1016/j.buildenv.2011.06.019     Document Type: Article

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