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Stefan cel Mare
University of Suceava
Faculty of Electrical Engineering and
Computer Science
13, Universitatii Street
Suceava - 720229
ROMANIA

Print ISSN: 1582-7445
Online ISSN: 1844-7600
WorldCat: 643243560
doi: 10.4316/AECE


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2019-Jun-20
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  3/2016 - 6

ABC Algorithm based Fuzzy Modeling of Optical Glucose Detection

SARACOGLU, O. G. See more information about SARACOGLU, O. G. on SCOPUS See more information about SARACOGLU, O. G. on IEEExplore See more information about SARACOGLU, O. G. on Web of Science, BAGIS, A. See more information about  BAGIS, A. on SCOPUS See more information about  BAGIS, A. on SCOPUS See more information about BAGIS, A. on Web of Science, KONAR, M. See more information about  KONAR, M. on SCOPUS See more information about  KONAR, M. on SCOPUS See more information about KONAR, M. on Web of Science, TABARU, T. E. See more information about TABARU, T. E. on SCOPUS See more information about TABARU, T. E. on SCOPUS See more information about TABARU, T. E. on Web of Science
 
Click to see author's profile in See more information about the author on SCOPUS SCOPUS, See more information about the author on IEEE Xplore IEEE Xplore, See more information about the author on Web of Science Web of Science

Download PDF pdficon (1,221 KB) | Citation | Downloads: 636 | Views: 3,027

Author keywords
fuzzy systems, heuristic algorithms, evolutionary computation, optical sensors, computational modeling

References keywords
fuzzy(21), glucose(13), systems(12), biosensors(9), algorithm(9), measurement(8), modeling(7), control(7), vivo(6), system(5)
Blue keywords are present in both the references section and the paper title.

About this article
Date of Publication: 2016-08-31
Volume 16, Issue 3, Year 2016, On page(s): 37 - 42
ISSN: 1582-7445, e-ISSN: 1844-7600
Digital Object Identifier: 10.4316/AECE.2016.03006
Web of Science Accession Number: 000384750000006
SCOPUS ID: 84991111440

Abstract
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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.


References | Cited By  «-- Click to see who has cited this paper

[1] G. A. Bray, "Energy and fructose from beverages sweetened with sugar or high-fructose corn syrup pose a health risk for some people", Advances in Nutrition: An International Review Journal, 4(2), pp.220-225, 2013.
[CrossRef] [Web of Science Times Cited 72] [SCOPUS Times Cited 94]


[2] L. D. Mello, L. T. Kubota, "Review of the use of biosensors as analytical tools in the food and drink industries", Food Chemistry, 77(2), pp.237-256, 2002.
[CrossRef] [Web of Science Times Cited 314] [SCOPUS Times Cited 349]


[3] S. F. Clarke, J. R. Foster, "A history of blood glucose meters and their role in self-monitoring of diabetes mellitus", British Journal of Biomedical Science, 69(2), pp.83-93, 2012. [PubMed]

[4] A. Arnoldi (Ed.). "Functional Foods, Cardiovascular Disease and Diabetes", pp.19-55, Elsevier, 2004.

[5] D. A. Stuart, J. M. Yuen, N. Shah, O. Lyandres, C. R. Yonzon, M. R. Glucksberg, J. T. Walsh, R. P. Van Duyne, "In Vivo Glucose Measurement by Surface-Enhanced Raman Spectroscopy", Analytical Chemistry, 78(20), pp.7211-7215, 2006.
[CrossRef] [Web of Science Times Cited 256] [SCOPUS Times Cited 281]


[6] D. Chen, C. Wang, W. Chen, Y. Chen, J.X. Zhang, "PVDF-Nafion Nanomembranes Coated Microneedles for in Vivo Transcutaneous Implantable Glucose Sensing", Biosensors and Bioelectronics, 74, pp. 1047-1052, 2015.
[CrossRef] [Web of Science Times Cited 20] [SCOPUS Times Cited 21]


[7] L. B. Mohammadi, T. Klotzbuecher, S. Sigloch, K. Welzel, M. Goeddel, T.R. Pieber, L. Schaupp, L., "Clinical Performance of A Low Cost Near Infrared Sensor for Continuous Glucose Monitoring Applied with Subcutaneous Microdialysis", Biomedical Microdevices, 17(4), pp.1-10, 2015.
[CrossRef] [Web of Science Times Cited 2] [SCOPUS Times Cited 6]


[8] D. Li, Y. Sun, S. Yu, C. Sun, H. Yu, K. Xu, "A Single-Loop Fiber Attenuated Total Reflection Sensor Enhanced by Silver Nanoparticles for Continuous Glucose Monitoring". Sensors and Actuators B: Chemical, 220, pp.1033-1042, 2015.
[CrossRef] [Web of Science Times Cited 10] [SCOPUS Times Cited 10]


[9] P. U. Abel, T. von Woedtke, "Biosensors for In Vivo Glucose Measurement: Can We Cross The Experimental Stage", Biosensors and Bioelectronics, 17(11), pp. 1059-1070, 2002.
[CrossRef] [Web of Science Times Cited 57] [SCOPUS Times Cited 75]


[10] G. S. Wilson, R. Gifford, "Biosensors for Real-Time In Vivo Measurements", Biosensors and Bioelectronics, 20(12), pp. 2388-2403, 2005.
[CrossRef] [Web of Science Times Cited 449] [SCOPUS Times Cited 512]


[11] H. E. Koschwanez, W.M. Reichert, "In Vitro, In Vivo and Post Explantation Testing of Glucose-Detecting Biosensors: Current Methods and Recommendations", Biomaterials, 28(25), pp.3687-3703, 2007.
[CrossRef] [Web of Science Times Cited 95] [SCOPUS Times Cited 123]


[12] S. Yu, D. Li, H. Chong, C. Sun, H. Yu, K. Xu, "In Vitro Glucose Measurement Using Tunable Mid-Infrared Laser Spectroscopy Combined with Fiber-Optic Sensor", Biomedical Optics Express, 5(1), pp.275-286, 2014.
[CrossRef] [SCOPUS Times Cited 30]


[13] J. C. Pickup, F. Hussain, N. D. Evans, N. Sachedina, "In Vivo Glucose Monitoring: The Clinical Reality and The Promise", Biosensors and Bioelectronics, 20(10), pp. 1897-1902, 2005.
[CrossRef] [Web of Science Times Cited 136] [SCOPUS Times Cited 161]


[14] D. Li, J. Wu, P. Wu, Y. Lin, Y. Sun, R. Zhu, J. Yang, K. Xu, "Affinity based Glucose Measurement using Fiber Optic Surface Plasmon Resonance Sensor with Surface Modification by Borate Polymer", Sensors and Actuators B: Chemical, 213, pp. 295-304, 2015.
[CrossRef] [Web of Science Times Cited 17] [SCOPUS Times Cited 20]


[15] S. Singh, B.D. Gupta, "Fabrication and Characterization of A Surface Plasmon Resonance based Fiber Optic Sensor using Gel Entrapment Technique for The Detection of Low Glucose Concentration", Sensors and Actuators B: Chemical, 177, pp.589-595, 2013.
[CrossRef] [Web of Science Times Cited 52] [SCOPUS Times Cited 54]


[16] B. Nacht, C. Larndorfer, S. Sax, S.M. Borisov, M. Hajnsek, F. Sinner, E.J.W. List-Kratochvil, I. Klimant, "Integrated Catheter System for Continuous Glucose Measurement and Simultaneous Insulin Infusion", Biosensors and Bioelectronics, 64, pp.102-110, 2015.
[CrossRef] [Web of Science Times Cited 15] [SCOPUS Times Cited 19]


[17] P. Squara, M. Imhoff, M. Cecconi, "Review Article: Metrology in Medicine: From Measurements to Decision, with Specific Reference to Anesthesia and Intensive Care", Anesthesia and Analgesia, 120(1), pp.66-75, 2015.
[CrossRef] [Web of Science Times Cited 16] [SCOPUS Times Cited 16]


[18] T. J. Ross, "Fuzzy Logic with Engineering Applications", pp.476-536, McGrawHill, 1995.

[19] H. T. Nguyen, M. Sugeno, "Fuzzy Systems: Modeling and Control", pp.63-90, Kluwer Academic Publishers, 1998.

[20] A. Bagis, "Fuzzy Rule Base Design using Tabu Search Algorithm for Nonlinear System Modeling", ISA Transactions, 47(1), pp.32-44, 2008.
[CrossRef] [Web of Science Times Cited 34] [SCOPUS Times Cited 41]


[21] A. Bagis, M. Konar, "Comparison of Sugeno and Mamdani Fuzzy Models Optimized by Artificial Bee Colony Algorithm for Nonlinear System Modelling", Transactions of the Institute of Measurement and Control,38(5), pp.579-592, 2016.
[CrossRef] [Web of Science Times Cited 7] [SCOPUS Times Cited 12]


[22] M. Konar, A. Bagis, "Performance Comparison of Particle Optimization, Differential Evolution and Artificial Bee Colony Algorithms for Fuzzy Modelling of Nonlinear Systems (Accepted for publication)", Elektronika IR Elektrotechnika, 2016, to be published.

[23] H. Du, N. Zhang, "Application of Evolving Takagi-Sugeno Fuzzy Model to Nonlinear System Identification", Applied Soft Computing, vol.8, pp.676-686, 2008.
[CrossRef] [Web of Science Times Cited 82] [SCOPUS Times Cited 102]


[24] A. Evsukoff, A. C. S. Branco, S. Galichet, "Structure Identification and Parameter Optimization for Non-Linear Fuzzy Modeling", Fuzzy Sets and Systems, vol.132, pp.173-188, 2002.
[CrossRef] [Web of Science Times Cited 47] [SCOPUS Times Cited 54]


[25] W. A. Farag, V. H. Quintana, G. L. Torres, "A Genetic based Neuro-Fuzzy Approach for Modeling and Control of Dynamical Systems", IEEE Trans. Neural Netw., 9(5), pp.756-767, 1998.
[CrossRef] [Web of Science Times Cited 145] [SCOPUS Times Cited 184]


[26] K. Guney, N. Sarikaya, "Comparison of Mamdani and Sugeno Fuzzy Inference System Models for Resonant Frequency Calculation of Rectangular Microstrip Antennas", Progress In Electromagnetics Research B, vol.12, pp.81-104, 2009.
[CrossRef] [SCOPUS Times Cited 47]


[27] S.-J. Kang, C.-H. Woo, H.-S. Hwang, K. B. Woo, "Evolutionary Design of Fuzzy Rule Base for Nonlinear Systems Modeling and Control", IEEE Transactions on Fuzzy Systems, (8)1, pp.37-45, 2000.
[CrossRef] [Web of Science Times Cited 78] [SCOPUS Times Cited 97]


[28] T. Takagi, M. Sugeno, "Fuzzy Identification of Systems and Its Applications to Modeling and Control", IEEE Transactions on Systems, Man, and Cybernetics, vol.15, pp.116-132, 1985.
[CrossRef] [Web of Science Times Cited 10497] [SCOPUS Times Cited 13710]


[29] R. M. Tong, "The Evaluation of Fuzzy Models Derived from Experimental Data", Fuzzy Sets and Systems, vol.4, pp.1-12, 1980.
[CrossRef] [Web of Science Times Cited 140] [SCOPUS Times Cited 194]


[30] L. Wang, R. Langari, "Complex Systems Modeling via Fuzzy Logic", IEEE Trans. Syst. Man Cybern-Part B: Cybern, 26(1), pp.100-106, 1996.
[CrossRef] [Web of Science Times Cited 120] [SCOPUS Times Cited 155]


[31] J. R. Jang , C. Sun, E. Mizutani, "Neuro-Fuzzy and Soft Computing: A Computational Approach to Learning and Machine Intelligence", pp.333-368, Prentice-Hall, Inc., 1997.

[32] F. Kulic, D. Matic, B. Dumnic, V. Vasic, "Optimal Fuzzy Controller Tuned by TV-PSO for Induction Motor Speed Control", Advances in Electrical and Computer Engineering, 11(1), pp.49-54, 2011.
[CrossRef] [Full Text] [Web of Science Times Cited 10] [SCOPUS Times Cited 10]


[33] R. E. Precup, R.C. David, E.M. Petriu, S. Preitl, M.B. Radac, "Fuzzy Logic based Adaptive Gravitational Search Algorithm for Optimal Tuning of Fuzzy-Controlled Servo Systems", IET Control Theory Appl., 7(1), pp.99-107, 2013.
[CrossRef] [Web of Science Times Cited 55] [SCOPUS Times Cited 64]


[34] M. J. Gacto, M. Galende, R. Alcala, F. Herrera, "METSK-HDe: A Multiobjective Evolutionary Algorithm to Learn Accurate TSK-Fuzzy Systems in High-Dimensional and Large-Scale Regression Problems, Information Sciences, 276, pp. 63-79, 2014.
[CrossRef] [Web of Science Times Cited 38] [SCOPUS Times Cited 41]


[35] D. Karaboga, "An idea based on honey bee swarm for numerical optimization", Technical Report-TR06, Erciyes University, Engineering Faculty, Computer Engineering Department, 2005.

[36] D. Karaboga, B. Akay, "A Powerful and Efficient Algorithm for Numerical Function Optimization: Artificial Bee Colony (ABC) Algorithm", Journal of Global Optimization, vol.39, pp.459-471, 2007.
[CrossRef] [Web of Science Times Cited 2534] [SCOPUS Times Cited 3293]


[37] D. Karaboga, B. Akay, "A Comparative Study of Artificial Bee Colony Algorithm", Applied Mathematics and Computation, vol.214, pp.108-132, 2009.
[CrossRef] [Web of Science Times Cited 1420] [SCOPUS Times Cited 1880]


[38] D. Karaboga, C. Ozturk, "A Novel Clustering Approach: Artificial Bee Colony (ABC) Algorithm", Applied Soft Computing, 11(1), pp.652-657, 2011.
[CrossRef] [Web of Science Times Cited 501] [SCOPUS Times Cited 668]


[39] A. Kulanthaisamy, R. Vairamani, N.K. Karunamurthi, C. Koodalsamy, "A Multi-Objective PMU Placement Method Considering Observability and Measurement Redundancy using ABC Algorithm", Advances in Electrical and Computer Engineering, 14(2), pp.117-128, 2014.
[CrossRef] [Full Text] [Web of Science Times Cited 7] [SCOPUS Times Cited 8]


[40] T. E. Tabaru, O. G. Saracoglu, E. Aslan, "Optical absorbance measurement of glucose in aqueous solution by using an RGB based simple spectrophotometer", Cankaya University 7th Engineering and Technology Symposium, May 15-16, 2014, pp. 219-223, Ankara, Turkey (in Turkish).



References Weight

Web of Science® Citations for all references: 17,226 TCR
SCOPUS® Citations for all references: 22,331 TCR

Web of Science® Average Citations per reference: 420 ACR
SCOPUS® Average Citations per reference: 545 ACR

TCR = Total Citations for References / ACR = Average Citations per Reference

We introduced in 2010 - for the first time in scientific publishing, the term "References Weight", as a quantitative indication of the quality ... Read more

Citations for references updated on 2019-08-22 12:56 in 231 seconds.




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