Comparison of genetic algorithm and neural network approaches for the drying process of carrot

Abstract Drying kinetic of carrot was investigated considering different drying conditions, in this study. The drying experiments were performed at four levels of drying air temperatures of 60–90 °C, together with three levels of air flow velocities of 0.5–1.5 m/s, and also three levels of thickness 0.5–1 cm. Four different mathematical models available in the literature were fitted to the experimental data. Among the considered mathematical drying models, modified Page model, was found to be more suitable for predicting drying of carrot. In order to optimize mathematical models obtained by using regression analysis, genetic algorithm was used. In all stages of the mathematical modeling, genetic algorithms were applied. In addition, a feed-forward artificial neural network was employed to estimate moisture content of carrot. Back propagation algorithm, the most common learning method for the feed-forward neural networks, was used in training and testing the network. Comparing the r (correlation coefficient), r 2 (coefficient of determination), χ 2 , and SSR (sum of squares of the difference between the experimental data and fit values) values of the four models, together with the optimized model by using genetic algorithms and the feed-forward neural network based estimator, it was concluded that neural network represented drying characteristics better than the others.

[1]  I. Farkas,et al.  A neural network topology for modelling grain drying , 2000 .

[2]  Pawel Strumillo,et al.  NEUROCOMPUTING APPROACHES TO MODELLING OF DRYING PROCESS DYNAMICS , 1998 .

[3]  Sangeeta Prakash,et al.  Performance evaluation of blanched carrots dried by three different driers , 2004 .

[4]  R. S. Harris,et al.  Vitamins and Hormones , 1948 .

[5]  Saliha Erenturk,et al.  The effects of cutting and drying medium on the vitamin C content of rosehip during drying , 2005 .

[6]  Ibrahim Dincer,et al.  Sun drying of Sultana grapes , 1996 .

[7]  D. R. Pangavhane,et al.  Drying behaviour of brined onion slices , 1999 .

[8]  Robert H. Driscoll,et al.  The thin-layer drying characteristics of garlic slices , 1996 .

[9]  Joseph Miltz,et al.  Dehydration of carrots by a combination of freeze drying, microwave heating and air or vacuum drying , 1998 .

[10]  F. Chytil,et al.  Vitamin A and cancer. , 1983, Vitamins and hormones.

[11]  Medeni Maskan,et al.  Drying, shrinkage and rehydration characteristics of kiwifruits during hot air and microwave drying , 2001 .

[12]  L. Diamante,et al.  Mathematical modelling of the thin layer solar drying of sweet potato slices , 1993 .

[13]  İbrahim Doymaz,et al.  Convective air drying characteristics of thin layer carrots , 2004 .

[14]  Tetsuo Morimoto,et al.  An intelligent approach for optimal control of fruit-storage process using neural networks and genetic algorithms , 1997 .

[15]  E. Akpinar,et al.  Thin layer drying of red pepper , 2003 .

[16]  István Farkas,et al.  Modelling aspects of grain drying with a neural network. , 2000 .

[17]  C. Geankoplis.  Transport processes and unit operations , 1978 .

[18]  Christine H. Scaman,et al.  Characterization of vacuum microwave, air and freeze dried carrot slices , 1998 .

[19]  Gilles Trystram,et al.  Dynamic models for drying and wet-milling quality degradation of corn using neural networks , 1997 .

[20]  Tetsuo Morimoto,et al.  Optimization of heat treatment for fruit during storage using neural networks and genetic algorithms , 1997 .

[21]  Saliha Erenturk,et al.  The Thin-layer Drying Characteristics of Rosehip , 2004 .

[22]  Y. Hashimoto,et al.  Applications of artificial neural networks and genetic algorithms to agricultural systems , 1997 .

[23]  A. Midilli.  Determination of pistachio drying behaviour and conditions in a solar drying system , 2001 .

[24]  P. Panchariya,et al.  Thin-layer modelling of black tea drying process , 2002 .

[25]  Lope G. Tabil,et al.  A comparative study for the estimation of dynamical drying behavior of Echinacea angustifolia: regression analysis and neural network , 2004 .

[26]  Da‐Wen Sun,et al.  Microwave–vacuum drying kinetics of carrot slices , 2004 .