توجه: محتویات این صفحه به صورت خودکار پردازش شده و مقاله‌های نویسندگانی با تشابه اسمی، همگی در بخش یکسان نمایش داده می‌شوند.
۱Perediction of Moisture Ratio in Drying Process of Garlic Cloves by GMDH type–Neural Network
نویسنده(ها): ، ،
اطلاعات انتشار: چهاردهمین کنگره ملی مهندسی شیمی ایران، سال
تعداد صفحات: ۷
Drying kinetic of garlic cloves was investigated by considering different drying conditions. In this study, drying of garlic cloves was done by microwave–convective technique, using microwave powers of 100,180 and 300 W, air temperature of 40,100 and 140 0C. The samples sizes were about 1.09 gr. each, and with thickness of 5 and 7 mm and air velocity were held stable at 1m\s. A GMDH type–neural network was employed to estimate moisture content of garlic slices. Accuracy of the models was measured using the coefficient of correlation (R2) and root mean square error (RMSE). ). The results were found that GMDH had a good agriment with experimental data<\div>

۲Prediction LLE data of 2–butanol in the organic phase at various tempratures by GMDH Type– Neural Network
نویسنده(ها): ، ، ،
اطلاعات انتشار: چهاردهمین کنگره ملی مهندسی شیمی ایران، سال
تعداد صفحات: ۶
In this study, A GMDH type–neural network was developed to predict LLE data for 2–butanol in the organic phase of ternary system (water + 2–butanol + 2–ethyl–1–hexanol) at various temperatures of 298.2, 308.2, 318.2, and 328.2K and atmospheric pressure. The predicted data were compared with the experimental data which have been previously reported. The average root mean square deviation (RMSD) between the observed and calculated mole fractions was used to reported errors, the estimated\predicted values of GMDH had a good agreement with experimental data<\div>
نمایش نتایج ۱ تا ۲ از میان ۲ نتیجه