Genetic Algorithm Optimizing Approach in Rosa Petals Hot Air Dryer

Damask rose (scientific name: Rosa Damascene) belongs to Rosaceae families and is valuable in medicine. In this study, the influence of air temperature and velocity are investigated on hot air dryer of the rose petals. Artificial drying of the agricultural products is one of the most common maintenance procedures. Suitable drying methods reduce the waste and damage during the storage and save the quality of the products. Optimization and control of the drying process is also based on the precise modeling. Here, moisture ratio was estimated by feed-forward neural network via temperature, air velocity, time period and moisture content to predict the next moisture content and therefore the drying rate. Later by using a genetic algorithm the optimum inputs condition is obtained. The results show that the drying procedure time is minimized perfectly by using the optimum conditions. The result show that neural network with one hidden layer and 29 hidden neurons can models the drying procedure very well with the performance of 1.69×10. Applying the optimum condition decreases the drying time from 40 minutes to 15 minutes. © 2011 Universal Research Publications. All rights reserved