I.3.7. Engineering
Artificial neural networks, genetic algorithm and response surface methods: The energy consumption of food and beverage industries in Iran

B. Hosseinzadeh Samani; H. HouriJafari; H. Zareiforoush

Volume 5, Issue 1 , March 2017, , Pages 79-88

https://doi.org/10.22044/jadm.2016.782

Abstract
  In this study, the energy consumption in the food and beverage industries of Iran was investigated. The energy consumption in this sector was modeled using artificial neural network (ANN), response surface methodology (RSM) and genetic algorithm (GA). First, the input data to the model were calculated ...  Read More

Yarn tenacity modeling using artificial neural networks and development of a decision support system based on genetic algorithms

Mohaddeseh Dashti; Vali Derhami; Esfandiar Ekhtiyari

Volume 2, Issue 1 , March 2014, , Pages 73-78

https://doi.org/10.22044/jadm.2014.187

Abstract
  Yarn tenacity is one of the most important properties in yarn production. This paper addresses modeling of yarn tenacity as well as optimally determining the amounts of the effective inputs to produce yarn with desired tenacity. The artificial neural network is used as a suitable structure for tenacity ...  Read More