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 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

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

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

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

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

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:

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

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

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

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

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

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]

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

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

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 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

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

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