Evaluating the Combined Effect of Temperature, Shear Rate and Water Content on Wild-Flower Honey Viscosity Using Adaptive Neural Fuzzy Inference System and Artificial Neural Networks: Honey Viscosity Using Artificial Neural Networks

Magazine article

Peer reviewed

M.A. Al-Mahasneh, T.M. Rababah and A.S. Ma'Abreh

Journal of food process engineering, Vol.36(4), pp.510-520

08/2013

Metrics

1 Record Views

Title: Evaluating the Combined Effect of Temperature, Shear Rate and Water Content on Wild-Flower Honey Viscosity Using Adaptive Neural Fuzzy Inference System and Artificial Neural Networks
Creators - without role: M.A. Al-Mahasneh - Jordan University of Science and Technology
T.M. Rababah - Jordan University of Science and Technology
A.S. Ma'Abreh - King Saud University
Publication Details: Journal of food process engineering, Vol.36(4), pp.510-520
Identifiers: 9949244608331
Academic Unit: King Saud University
Language: English
Resource Type: Magazine article