artificial neural network modeling of drying kinetics and

Experimental and neural network prediction of a tray drier

2012-1-13Neural networks mimic the human intelligence for objective learning Artificial neuronal networks have been utilized for classification prediction and image segmentation in quality evaluation of food products in recent years [3] Kaminisky et al [2] reported the application of an artificial neural network (NN) to modeling of drying

Prediction of carrot cubes drying kinetics during

This article presents static and recurrent artificial neural networks (ANNs) to predict the drying kinetics of carrot cubes during fluidized bed drying Experiments were performed on square−cubed carrot with dimensions of 4 7 and 10 mm air temperatures of 50 60 and 70C and bed depths of 3 6 and 9 cm Initially static ANN was used to correlate the outputs (moisture ratio and drying

Convective drying of garlic (Allium sativum L

In this study artificial neural networks (ANNs) was utilized for modeling and the prediction of moisture content (MC) of garlic during drying The application of a multi-layer perceptron (MLP) neural network entitled feed forward back propagation (FFBP) was used

Modeling of Osmotic Dehydration Kinetics of Banana

2017-5-5Modeling of Osmotic Dehydration Kinetics of Banana Slices using Artificial Neural Network S L Pandharipande Associate Professor Department of Chemical Engineering LIT RTMNU Nagpur India Saurav Paul B Tech Department of Chemical Engineering LIT RTMNU Nagpur India Ankit Singh M Tech IV semester

M Mousavi 1* and S Javan 1

Modeling and Simulation of Apple Drying Using Arti ficial Neural Network and Neuro -Taguchi s Method M Mousavi 1* and S Javan 1 ABSTRACT Important parameters on apple drying process are i nvestigated experimentally and modeled employing artificial neural network and neu ro-Taguchi's method Experimental

Modeling of Microwave Vacuum Drying Kinetics of

In microwave vacuum drying the microwave energy was mainly absorbed by liquid water present in food that results in the temperature to rise resulting in drying of bael pulp In this study modeling of microwave vacuum drying kinetics and effective moisture diffusivity of bael pulp was investigated The effect of microwave power varying between 400 and 800 W and vacuum levels between 380 and

Microwave–vacuum drying of sour cherry: comparison

Artificial neural network modeling An artificial neural network (ANN) was developed based on the experimental work Results showed that the Back Propagation training algorithm was well suited for predicting of Moisture Ratio and Drying Rate based on different

Drying kinetics study of parboiled rice by using

Abstract: The objective of this research was to predict hybrid hot air-infrared radiation drying kinetics of Leb Nok Pattani parboiled rice using a mathematical model and an artificial neural network model Drying kinetics of parboiled rice was investigated considering different drying conditions The drying experiments were performed at three levels of drying air temperatures of 60-100C

Kinetic and artificial neural network modeling

Kinetic and artificial neural network modeling techniques to predict the drying kinetics of Mentha spicata L Author: Karakaplan Nihan Goz Eda Tosun Emir Yuceer Mehmet Source: Journal of food processing and preservation 2019 v 43 no 10 pp e14142 ISSN: 0145-8892 Subject:

Comparison of Mathematical Equation and Neural

Mendong (Fimbristylis globulosa) has a potentially industrial application We investigate a predictive model for heat and mass transfer in drying kinetics during drying a Mendong We experimentally dry the Mendong by using a microwave oven In this study we analyze three mathematical equations and feed forward neural network (FNN) with back propagation to describe the drying behavior of Mendong

Mathematical and neural networks modeling of thin

2016-9-26Artificial neural network is a well-known tool for solving complex non-linear biological systems The Multi-layer perceptron network was used for modeling drying kinetics With regard to the results the network with LOGSIG-TANSIG- PURELIN activation function and 3-6-4-1 topology showed the best performance in which RMSE was 0 00196 and

XVIIth World Congress of the International Commission of

2013-1-16The artificial neural network (ANN) is a wellknown tool for solving complex problems - and it can give reasonable solutions even in extreme cases or in the event of technological faults (Lin and Lee 1995) The literature cited clearly encourages further study of the application of artificial ANNs to model the drying process The ANN model

Osmotic Drying Rate Estimation for Dehydration of

2013-11-13for drying of food materials with advantages of retention of gloss texture colour of dried products Artificial neural network is emerging as a modeling tool for complex operations involving non linear multivariable relationships The present work is aimed at estimation of the osmotic drying rates

Experiment on Neural Network Prediction Modeling of Far

The factors influenced infrared radiation drying rates for Agaricus bisporus such as radiation intensity radiation distance material temperature material thickness and drying time were analyzed The network model structure between moisture content and all the

Empirical Model and Artificial Neural Network Model

2013-1-11drying kinetics approached by empirical modeling To addition some work reported the artificial neural network modeling approach to drying kinetic of biomaterials [3 5-7] An artificial neural network models (ANN) applying to biomaterials can describe the drying behavior very well [3 8-10]

Convective drying of garlic (Allium sativum L

In this study artificial neural networks (ANNs) was utilized for modeling and the prediction of moisture content (MC) of garlic during drying The application of a multi-layer perceptron (MLP) neural network entitled feed forward back propagation (FFBP) was used

Temas para TCC Artificial neural networks modeling of

Abstract The objective of this study was to predict celeriac drying curves using artificial neural networks (ANNs) The experimental data for vacuum drying kinetics of celeriac slices reported by other researcher in the previously published article was used The air temperature chamber pressure and time values were used as ANN inputs To predict the moisture content the multilayer feed

Neurocomputing approaches to modelling of drying

2020-7-8The application of artificial neural networks to mathematical modeling of drying kinetics degradation kinetics and smoothing of experimental data is discussed in the paper A theoretical foundation of drying process description by means of artificial neural networks is presented Two network

A GHADERI COMPARISON OF MATHEMATICAL MODELS

2015-1-30drying process [12] prediction of drying kinetics [13] solar drying performance [14] tomato drying [15] po-megranate arils drying with microwave pretreatment [16] and mushroom slice [17] Therefore the main objectives of this study were to investigate the drying kinetics as well as comparing the capabilities of artificial neural network

A hybrid neural network‐first principles approach to

A hybrid neural network‐first principles modeling scheme is developed and used to model a fedbatch bioreactor The hybrid model combines a partial first principles model which incorporates the available prior knowledge about the process being modeled with a neural network which serves as an estimator of unmeasured process parameters that are difficult to model from first principles

Prediction of carrot cubes drying kinetics during

The critically aspect of drying technology is the modeling of the drying process (Demir et al 2007) The prediction of drying kinetics of agricultural products under various conditions is vital for equipment and process design quality control energy and fuel management choice of appropriate storage handling practices and etc

MODELING OF FREEZE DRYING BEHAVIORS OF

2018-5-20determination of the drying kinetics (k and n) used in Page equation in drying potato slices by Islam Sablani and Mujumdar (Islam et al 2003) Cubillos and Reyes (2003) also used ANN approach for modeling the drying of carrots The progress of neurobiology has allowed researchers to build mathematical models of neurons to simulate neural

Artificial Neural Network Modeling of Drying Kinetics

Artificial Neural Network Modeling of Drying Kinetics and Color Changes of Ginkgo Biloba Seeds during Microwave Drying Process Jun-Wen Bai 1 Hong-Wei Xiao 2 Hai-Le Ma 1 and Cun-Shan Zhou 1 1 School of Food and Biological Engineering Jiangsu University Zhenjiang 212013 China

Artificial neural network modeling of process and product

This study aimed to model the performance indices of deep bed drying of rough rice using artificial neural networks (ANNs) compare the ANN approach to the multivariate regression method and determine the sensitivity of the ANN model to the input variables

Determination of freeze

2012-5-2Modeling of freeze drying behaviors of strawberries by using arti?cial neural network Journal of Thermal Science and Technology 29(2) 11–21 Muthukumaran A Ratti C Raghavan V G S (2008) Foam-mat freeze drying of egg white – Mathematical part

Drying kinetics study of parboiled rice by using

The objective of this research was to predict hybrid hot air-infrared radiation drying kinetics of Leb Nok Pattani parboiled rice using a mathematical model and an artificial neural network model Drying kinetics of parboiled rice was investigated considering different drying conditions

MOHSEN BEIGI PREDICTION OF PADDY DRYING

2017-8-3PREDICTION OF PADDY DRYING KINETICS: A COMPARATIVE STUDY BETWEEN MATHEMATICAL AND ARTIFICIAL NEURAL NETWORK MODELING Article Highlights • Drying curves of paddy were modeled using mathematical and ANN modeling tech-niques • Among the applied models the Midilli model was determined as t he best one describing drying curves

Kinetic and artificial neural network modeling

This study presented both the empirical and artificial neural network (ANN) approaches to estimate the moisture content of Mentha spicata Two different types of drying methods (in shade and in oven (35 and 50C)) were used to investigate the drying kinetics of the Mentha spicata samples The effects of drying methods on effective diffusion

A Neural Based Modeling Approach for Drying Kinetics

2017-3-13based on artificial neural network (ANN) The results showed that the model based on the ANN predicted the drying kinetics of the different parts better than the diffusive model A single network was built to describe the kinetic behavior of branches and