# مقالههای A Daghbandan

**توجه:**محتویات این صفحه به صورت خودکار پردازش شده و مقالههای نویسندگانی با تشابه اسمی، همگی در بخش یکسان نمایش داده میشوند.

##### ۱Prediction of Dehydration Characteristics and Effective Moisture Content of Tarom Garlic Slices Undergoing Microwaveconvective Drying process

اطلاعات انتشار:
هفتمین همایش ملی دانشجویی مهندسی شیمی،
سال ۱۳۸۶

تعداد صفحات:
۹

This study was undertaken to investigate the dehydration characteristics of the Tarom garlic in a microwaveconvective dryer. Drying of the garlic cloves was done using microwaveconvective technique, using microwave power of 100,180 and 300 W, air temperature of 40,100 and 140 o C and sample thickness of 5 and 7 mm and air velocity was held stable at 1 m. s – 1 . The effects of air temperature and a sample thickness on the dehydration characteristics were determined. Fick’s equation described the transport of water during dehydration. A third order polynomial relationship was found to correlate the effective moisture diffusivity ( ) eff D with moisture content. The ( ) eff D increased for the same values of dry air temperature as the applied microwave power was increased. The activation energy in the microwaveconvective drying was much lower than the convenctionally heating activation energy values. The obtained experimental dehydration data of garlic slices were fitted to the five semitheoretical

drying models, i.e. Henderson and Pabis, twoterm, Lewis, Page, Verma et al., and a developed model by the researchers. Accuracy of the models were measured using the coefficient of determination ( R 2 ), root mean square error (RMSE) and sum of square error (SSE). All of the six models were acceptable for describing dehydration characteristics of garlic slices; however, based on statistical analysis, the developed model was the best one for prediction of dehydration characteristics of garlic slices.<\div>

drying models, i.e. Henderson and Pabis, twoterm, Lewis, Page, Verma et al., and a developed model by the researchers. Accuracy of the models were measured using the coefficient of determination ( R 2 ), root mean square error (RMSE) and sum of square error (SSE). All of the six models were acceptable for describing dehydration characteristics of garlic slices; however, based on statistical analysis, the developed model was the best one for prediction of dehydration characteristics of garlic slices.<\div>

##### ۲Perediction of Moisture Ratio in Drying Process of Garlic Cloves by GMDH type–Neural Network

اطلاعات انتشار:
چهاردهمین کنگره ملی مهندسی شیمی ایران،
سال ۱۳۹۱

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>

##### ۳Prediction LLE data of 2–butanol in the organic phase at various tempratures by GMDH Type– Neural Network

اطلاعات انتشار:
چهاردهمین کنگره ملی مهندسی شیمی ایران،
سال ۱۳۹۱

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>

##### ۴Comparison of Mathmatical Models for Drying Process of Garlic Cloves by Genetic Algorithm

اطلاعات انتشار:
چهاردهمین کنگره ملی مهندسی شیمی ایران،
سال ۱۳۹۱

تعداد صفحات:
۷

Drying techniques are used for maintaining and long survival of garlic cloves. 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. The effects of air temperature, microwave power and a samples thickness on the dehydration characteristics were determined. Two different mathematical models (Modified Page; Henderson and Pabis) and a developed model by the researchers were fitted to the experimental data. A developed model, was found to be more suitable for predicting drying of garlic cloves. In all stages of the mathematical modeling, multi– objective genetic algorithm was applied. Accuracy of the models was measured using the coefficient of correlation (R2) and root mean square error (RMSE). The results were found that the predictions of the developed model more accurately in comparison to other mathematical models<\div>

##### ۵MULTI OPTIMAL DESIGN OF GMDH TYPE–NN FOR MODELING AND PREDICTION OF GAS CONSUMPTION IN RASHT CITY

اطلاعات انتشار:
اولین همایش ملی تکنولوژی های نوین در شیمی و پتروشیمی،
سال ۱۳۹۳

تعداد صفحات:
۷

It is widely accepted that natural gas is a clean energy source that can be used to meet energy demand for heating and industrial purpose among the fossil fuels and its usage remarkably increases in order to maintain a clean environment in many countries in the world. Therefore, energy demand for various sectors should be estimated in the frame of short–term energy policy. In this paper, multi–objective evolutionary pareto optimal design of GMDH type–Neural Network has been used for modeling and predicting of gas consumption in Rasht, Guilan, Iran, using input–output data sets. In this way, multi–objective uniform–diversity genetic algorithms (MUGA) are then used for pareto optimization of GMDH networks. Input data set (mean temperature, moisture, rainfall and number of units) were obtained from the regional gas distribution company and the local meteorology office in last 7 years. The predicted values were compared with those of experimental values in order to estimate the performance of the GMDH network<\div>

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