استفاده از روش نرو- فازی برای مدلسازی فرآیند آبگیری از برشهای موز به روش اسمز- فراصوت

نویسندگان
فخرالدین صالحی 1
رعنا چراغی 2
مجید رسولی 3
1 دانشیار، دانشکده کشاورزی، دانشگاه بوعلی سینا، همدان، ایران
2 دانشجوی کارشناسی ارشد، دانشکده کشاورزی، دانشگاه بوعلی سینا، همدان، ایران
3 استادیار، دانشکده کشاورزی، دانشگاه بوعلی سینا، همدان، ایران
10.22034/FSCT.19.125.243
چکیده
سیستم استنتاج تطبیقی فازی- عصبی (نرو- فازی یا انفیس) یک شبکه ترکیبی عصبی- فازی شناخته شده برای مدل‌سازی سیستم‌های پیچیده است. در این سیستم متداول‌ترین روش خوشه‌بندی فازی، الگوریتم خوشه‌بندی کاهشی فازی است. در این الگوریتم، یک خوشه با درجه مشخص برای هر نقطه داده وجود دارد که توسط یک سطح تابع عضویت توضیح داده می‌شود. در این مطالعه از مدل انفیس برای پیش‌بینی کاهش وزن (%)، جذب مواد جامد (%)، کاهش آب (%) و آبگیری مجدد (%) برش‌های موز آب‌گیری شده به روش اسمز-فراصوت استفاده شد. مدل انفیس با 3 ورودی توان فراصوت (در سه سطح 0، 75 و 150 وات)، زمان تیمار فراصوت (در سه زمان 10، 15 و 20 دقیقه) و غلظت محلول ساکارز (در سه سطح 30، 45 و 60 درجه بریکس) برای پیش‌بینی ویژگی‌های برش‌های موز آبگیری شده، توسعه یافت. مقادیر ضریب تبیین محاسبه‌شده برای پیش‌بینی کاهش وزن (%)، جذب مواد جامد (%)، کاهش آب (%) و آبگیری مجدد (%) برش‌های موز آبگیری شده با استفاده از الگوریتم خوشه‌بندی کاهشی مبتنی بر انفیس به ترتیب برابر 93/0، 95/0، 94/0 و 91/0 بود. در مجموع می‌توان بیان داشت که میزان ضرایب تبیین بالای بین نتایج تجربی و خروجی‌های مدل انفیس بیانگر دقت قابل قبول و قابلیت استفاده از این روش در کنترل فرایندهای پیچیده صنایع غذایی از جمله فرآیندهای آبگیری و خشک‌کردن است.
کلیدواژه‌ها
انفیس
خوشه‌بندی کاهشی
سیستم استنتاج تطبیقی فازی-عصبی
فراصوت
مدل‌سازی

موضوعات

عنوان مقاله English

Application of neuro-fuzzy approach for modeling of dehydration process from banana slices by osmosis-ultrasound method

نویسندگان English

Fakhreddin Salehi 1
Rana Cheraghi 2
Majid Rasouli 3
1 Associate Professor, Faculty of Agriculture, Bu-Ali Sina University, Hamedan, Iran
2 MSc Student, Faculty of Agriculture, Bu-Ali Sina University, Hamedan, Iran
3 Assistant Professor, Faculty of Agriculture, Bu-Ali Sina University, Hamedan, Iran
چکیده English

Adaptive neuro-fuzzy inference system (neuro-fuzzy or ANFIS) is a well-known hybrid neuro-fuzzy network for modeling complex systems. In this system ,the most frequently used fuzzy clustering method is the fuzzy subtractive clustering algorithm. In this algorithm, a cluster with a certain degree has each data point, explained by a membership function level. In this study, ANFIS model was used for prediction of weight reduction (%), solid gain (%),water loss (%) and rehydration (%) of banana slices dehydrated by osmosis-ultrasound method. The ANFIS model was developed with 3 inputs of sonication power (at three levels of 0, 75 and 150 watts), ultrasound treatment time (at three times of 10, 15 and 20 minutes) and sucrose solution concentration (at three levels of 30, 45 and 60 °Brix) to predict the characteristics of dehydrated banana slices. The calculated coefficient of determination values for prediction of weight reduction (%), solid gain (%),water loss (%) and rehydration (%) of dehydrated banana slices using the ANFIS-based subtractive clustering algorithm were 0.93, 0.95, 0.94, and 0.91, respectively. In general, it can be said that the high coefficients of determination between the experimental results and the outputs of the ANFIS model indicate acceptable accuracy and usability this method in controlling complex processes in the food industry, including dehydration and drying processes.

کلیدواژه‌ها English

Adaptive Neuro-Fuzzy Inference System
ANFIS
Modeling
Sonication
Subtractive clustering
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