A micromechanics-based artificial neural networks model for elastic properties of short fiber composites

Estimation of coal swelling index based on chemical properties of coal using artificial neural networks

Free swelling index (FSI) is an important parameter for cokeability and combustion of coals. In this research, the effects of chemical properties of coals on the coal free swelling index were studied by artificial neural network methods. The artificial neural networks (ANNs) method was used for 200 datasets to estimate the free swelling index value. In this investigation, ten input parameters ...

Comparison of Two Computational Microstructure Models for Predicting Effective Transverse Elastic Properties of Unidirectional Fiber Reinforced Composites

Characterization of properties of composites has attracted a great deal of attention towards exploring their applications in engineering. The purpose of this work is to study the difference of two computational microstructure models which are widely used for determining effective transverse elastic properties of unidirectional fiber reinforced composites. The first model based on the classic me...

studies on properties of short fiber reinforced natural rubber composites

natural rubber/fiber composites were prepared in a laboratory mixer using new and waste short nylon fiber by a one-step mixing process. fiber loading and bonding agent effects on the microstructure and mechanical properties of the composites were studied. the cure characteristics of composites were investigated by using rheometer. cure and scorching times of the composites decreased while maxim...

Developing an Artificial Neural Networks Model for Predicting Output Energy and GHG Emission of Strawberry Production

An Approach of Artificial Neural Networks Modeling Based on Fuzzy Regression for Forecasting Purposes

In this paper, a new approach of modeling for Artificial Neural Networks (ANNs) models based on the concepts of fuzzy regression is proposed. For this purpose, we reformulated ANN model as a fuzzy nonlinear regression model while it has advantages of both fuzzy regression and ANN models. Hence, it can be applied to uncertain, ambiguous, or complex environments due to its flexibility for forecas...