Estimation of Carrageenan concentration using radial basis function neural network

被引：0

作者：

Krishnaiah, D ^{[1
]}

Bono, A ^{[1
]}

Yaacob, S ^{[1
]}

Pandiyan, P ^{[1
]}

Karthikeyan, C ^{[1
]}

Prasad, DMR ^{[1
]}

机构：

[1] Univ Malaysia Sabah, Sch Informat Technol & Engn, Sabah 88999, Malaysia

来源：

ISAS/CITSA 2004: INTERNATIONAL CONFERENCE ON CYBERNETICS AND INFORMATION TECHNOLOGIES, SYSTEMS AND APPLICATIONS AND 10TH INTERNATIONAL CONFERENCE ON INFORMATION SYSTEMS ANALYSIS AND SYNTHESIS, VOL 2, PROCEEDINGS: COMMUNICATIONS, INFORMATION AND CONTROL SYSTEMS, TECHNOLOGIES AND APPLICATIONS | 2004年

关键词：

Carrageenan; seaweed; Sono chemical technique; power spectrum; radial basis function neural network (RBFNN); Euclidean distance;

D O I：

暂无

中图分类号：

TP [自动化技术、计算机技术];

学科分类号：

0812 ;

摘要：

The application of Artificial Neural Networks in chemical engineering field is being under immense research. Every material has its own intensity to absorb the sound waves. It is due to the physical characteristic of the chemical compound. Carrageenans are water-soluble gums, which occur in certain species of red seaweeds. They are sulfated natural polymers made up of galactose units. Carrageenan consists of a main chain of D-galactose residues linked alternately alpha - (1 -> 3) and beta - (1 -> 4). The differences between the fractions are due to the number and to the position of the sulflate groups and also due to the possible presence of a 3.6 anhydro-bridge on the galactose linked through the 1 - and 4 -positions. The sound absorption capability changes with respect to the concentration of the carrageenan in the solution. A simple scheme using Radial Basis Function Neural Networks is used for training the above signals. The proposed procedure improves the training time and will have less number of failures. This method is useful for the direct estimation of carrageenan in food, pharmaceutical and cosmetic industries. It can also be used for the online measurement of compounds in the industries.

引用

页码：173 / 177

页数：5

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