ABC Algorithm based Fuzzy Modeling of Optical Glucose Detection

SARAÇOĞLU Ö. G., BAĞIŞ A., KONAR M., TABARU T. E.

ADVANCES IN ELECTRICAL AND COMPUTER ENGINEERING, vol.16, no.3, pp.37-42, 2016 (SCI-Expanded) identifier

  • Publication Type: Article / Article
  • Volume: 16 Issue: 3
  • Publication Date: 2016
  • Doi Number: 10.4316/aece.2016.03006
  • Journal Name: ADVANCES IN ELECTRICAL AND COMPUTER ENGINEERING
  • Journal Indexes: Science Citation Index Expanded (SCI-EXPANDED), Scopus
  • Page Numbers: pp.37-42
  • Keywords: fuzzy systems, heuristic algorithms, evolutionary computation, optical sensors, computational modeling, IN-VIVO, SEARCH ALGORITHM, RULE BASE, SYSTEMS, BIOSENSORS, IDENTIFICATION, SENSOR, OPTIMIZATION, SPECTROSCOPY, DESIGN
  • Erciyes University Affiliated: Yes

Abstract

This paper presents a modeling approach based on the use of fuzzy reasoning mechanism to define a measured data set obtained from an optical sensing circuit. For this purpose, we implemented a simple but effective an in vitro optical sensor to measure glucose content of an aqueous solution. Measured data contain analog voltages representing the absorbance values of three wavelengths measured from an RGB LED in different glucose concentrations. To achieve a desired model performance, the parameters of the fuzzy models are optimized by using the artificial bee colony (ABC) algorithm. The modeling results presented in this paper indicate that the fuzzy model optimized by the algorithm provide a successful modeling performance having the minimum mean squared error (MSE) of 0.0013 which are in clearly good agreement with the measurements.