A Hybrid of Artificial Bee Colony, Genetic Algorithm, and Neural Network for Diabetic Mellitus Diagnosing

  • Tarik A. Rashid (1) Department of Science and Engineering, University of Kurdistan Hewler, Erbil, Kurdistan Region – F.R. Iraq. (2) Department of Software and Informatics Engineering, Salahaddin University, Erbil, Kurdistan Region – F.R. Iraq. http://orcid.org/0000-0002-8661-258X
  • Saman M. Abdullah (1) Department of Software Engineering, Faculty of Engineering, Koya University, Kurdistan Region – F.R. Iraq. (2) Department of Computer Engineering, Ishik University, Erbil, Kurdistan Region – F.R. Iraq. http://orcid.org/0000-0002-7046-3401
Keywords: Artificial Bee Colony, Artificial Neural Networks, Diabetic Mellitus, Evolutionary Algorithms.

Abstract

Researchers widely have introduced the Artificial Bee Colony (ABC) as an optimization algorithm to deal with classification and prediction problems. ABC has been combined with different Artificial Intelligent (AI) techniques to obtain optimum performance indicators. This work introduces a hybrid of ABC, Genetic Algorithm (GA), and Back Propagation Neural Network (BPNN) in the application of classifying, and diagnosing Diabetic Mellitus (DM). The optimized algorithm is combined with a mutation technique of Genetic Algorithm (GA) to obtain the optimum set of training weights for a BPNN. The idea is to prove that weights’ initial index in their initialized set has an impact on the performance rate. Experiments are conducted in three different cases; standard BPNN alone, BPNN trained with ABC, and BPNN trained with the mutation based ABC. The work tests all three cases of optimization on two different datasets (Primary dataset, and Secondary dataset) of diabetic mellitus (DM). The primary dataset is built by this work through collecting 31 features of 501 DM patients in local hospitals. The secondary dataset is the Pima dataset. Results show that the BPNN trained with the mutation based ABC can produce better local solutions than the standard BPNN and BPNN trained in combination with ABC.

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Author Biographies

Tarik A. Rashid, (1) Department of Science and Engineering, University of Kurdistan Hewler, Erbil, Kurdistan Region – F.R. Iraq. (2) Department of Software and Informatics Engineering, Salahaddin University, Erbil, Kurdistan Region – F.R. Iraq.
Dr. Tarik Ahmed Rashid received his Ph.D. in Computer Science and Informatics degree from College of Engineering, Mathematical and Physical Sciences, University College Dublin (UCD) in 2001-2006. He pursued his Post-Doctoral Follow at the Computer Science and Informatics School, College of Engineering, Mathematical and Physical Sciences, University College Dublin (UCD) from 2006-2007. He was a Professor at Salahaddin University-Erbil, Hawler, Kurdistan. He Joined the University of Kurdistan Hewlêr (UKH) in 2017.
Saman M. Abdullah, (1) Department of Software Engineering, Faculty of Engineering, Koya University, Kurdistan Region – F.R. Iraq. (2) Department of Computer Engineering, Ishik University, Erbil, Kurdistan Region – F.R. Iraq.
Saman Mirza is a Ph.D. holder in Computer Security (Malware detection and classification) in the Department of Software Engineering, where he joined the work at Koya University since 2012. Before that he was a Master degree lecture at the same university, computer system department from (2006-2009). From January-2009 to December-2012, he was a PhD researcher in University of Malaya, Computer System department, Faculty of Computer Science and Information Technology in Malaysia. He got a B.Sc. degree in Electrical Engineering from Salahuddin  University in 1990, M.Sc. degree in Compute Security Engineering from Koya University in December 2005.He started his academic teaching in 1997 in Koya Technical Institute as a lecture of computer Programming subject.  In 1999 he joined UN-Habitat Erbil Office as a technician and data administration. He is member in IEEE Communication Society, International Association of Engineering, and ICATT-China, IJPS, and IAENG . He worked as a reviewer for IJPS -ISI international Journals.He awarded as a second runner for the 3MUM presentation for the academic year 2011-2012.

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Published
2018-06-13
How to Cite
Rashid, T. A. and Abdullah, S. M. (2018) “A Hybrid of Artificial Bee Colony, Genetic Algorithm, and Neural Network for Diabetic Mellitus Diagnosing”, ARO-THE SCIENTIFIC JOURNAL OF KOYA UNIVERSITY, 6(1), pp. 55-64. doi: 10.14500/aro.10368.
Section
Articles