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Drying Technology
An International Journal
Volume 15, 1997 - Issue 10
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Original Articles

DEVELOPMENT OF ANN MODEL FOR NON-LINEAR DRYING PROCESS

T. Thyagarajan Crescent Engineering college, Central Leather Research Institute, Madras Institute of Technology, Madras, India
,
RC. Panda Central Leather Research Institute, Madras Institute of Technology, Madras, India
,
J. Shanmugan Madras Institute of Technology, Madras, India
,
V.P.G. Rao Central Leather Research Institute, Madras Institute of Technology, Madras, India
&
M. Ponnavaikko Crescent Engineering college, Central Leather Research Institute, Madras Institute of Technology, Madras, India
Pages 2527-2540 | Published online: 03 May 2007

Citations (15)

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Read on this site (5)

Mortaza Aghbashlo, Soleiman Hosseinpour & Arun S. Mujumdar. (2015) Application of Artificial Neural Networks (ANNs) in Drying Technology: A Comprehensive Review. Drying Technology 33:12, pages 1397-1462.
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Jules Thibault, PedroI. Alvarez, Roman Blasco & Rolando Vega. (2010) Modeling the Mean Residence Time in a Rotary Dryer for Various Types of Solids. Drying Technology 28:10, pages 1136-1141.
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Najmeh Neshat, Nasser Salmasi & Aliyeh Kazemi. (2010) A Hybrid Approach of Partial Least Squared Analysis and Artificial Neural Networks for Predictive Control of a Ceramic Process. Transactions of the Indian Ceramic Society 69:2, pages 89-98.
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P. C. Panchariya, D. Popovic & A. L. Sharma. (2002) DESORPTION ISOTHERM MODELLING OF BLACK TEA USING ARTIFICIAL NEURAL NETWORKS. Drying Technology 20:2, pages 351-362.
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María C. Palancar, José M. Aragón & José A. Castellanos. (2001) NEURAL NETWORK MODEL FOR FLUIDISED BED DRYERS. Drying Technology 19:6, pages 1023-1044.
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Articles from other publishers (10)

Narayani Thirunavukarasu, Rames C. Panda, Atanu Panda & Kalaivani K. (2023) Parametric Identification of a Countercurrent Aqueous Hydrolysis Process for the Production of Glycerine under Higher Pressure and Temperature. Chemical Engineering & Technology.
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Sam Durairaj, Joanofarc Xavier, Sanjib Kumar Patnaik & Rames C Panda. (2023) Deep Learning Based System Identification and Nonlinear Model Predictive Control of pH Neutralization Process. Industrial & Engineering Chemistry Research.
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Kang Peng, Longliang Wu, Yousef Zandi, Alireza Sadighi Agdas, Ali Majdi, Nebojsa Denic, Aleksandar Zakić, Ahmed Abdel Khalek Ebid, Mohamed Amine Khadimallah & H. Elhosiny Ali. (2022) Application of Polyacrylic Hydrogel in Durability and Reduction of Environmental Impacts of Concrete through ANN. Gels 8:8, pages 468.
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N. Neshat, H. Mahlooji & A. Kazemi. (2011) An enhanced neural network model for predictive control of granule quality characteristics. Scientia Iranica 18:3, pages 722-730.
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A. Azadeh, N. Neshat & M. Saberi. (2010) An intelligent approach for improved predictive control of spray drying process. An intelligent approach for improved predictive control of spray drying process.
R. Amiri Chayjan & Y. Moazez. (2008) Estimation of Paddy Equilibrium Moisture Sorption Using ANNs. Journal of Applied Sciences 8:2, pages 346-351.
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Xueqiang Liu, Xiaoguang Chen, Wenfu Wu & Guilan Peng. (2007) A neural network for predicting moisture content of grain drying process using genetic algorithm. Food Control 18:8, pages 928-933.
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Xueqiang Liu, Xiaoguang Chen, Wenfu Wu & Yaqiu Zhang. (2006) Process control based on principal component analysis for maize drying. Food Control 17:11, pages 894-899.
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I. Farkas, P. Reményi & A. Biró. (2000) Modelling aspects of grain drying with a neural network. Computers and Electronics in Agriculture 29:1-2, pages 99-113.
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I Farkas, P Reményi & A Biró. (2000) A neural network topology for modelling grain drying. Computers and Electronics in Agriculture 26:2, pages 147-158.
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