Estimating the Semen Quality from Life Style Using Fuzzy Radial Basis Functions - Volume 8 Number 1 (Feb. 2018) - IJMLC
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Editor-in-chief
Dr. Lin Huang
Metropolitan State University of Denver, USA
It's my honor to take on the position of editor in chief of IJMLC. We encourage authors to submit papers concerning any branch of machine learning and computing.
IJMLC 2018 Vol.8(1): 44-48 ISSN: 2010-3700
DOI: 10.18178/ijmlc.2018.8.1.661

Estimating the Semen Quality from Life Style Using Fuzzy Radial Basis Functions

Cemre Candemir
Abstract—Infertility is a major problem that directly affects many people worldwide. In recent years, fertility rates decreased up to 15% in young men. Changing live conditions, stress level, environmental factors, nutritional habits play an important role on infertility. This paper suggests a novel method estimating semen quality from lifestyle, environmental factors and daily habits using the radial basis function neural networks. The accuracy of the suggested method measured as 90%. The result shows that the proposed method can be applied as a practical, fast and cheap alternative method to the laboratory tests.

Index Terms—Classification, fertility, fcm, fuzzy radial basis functions, neural networks.

C. Candemir is with the International Computer Institute at Ege University, 35100, Bornova, Izmir, Turkey (e-mail: cemre.candemir@ege.edu.tr).

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Cite: Cemre Candemir, "Estimating the Semen Quality from Life Style Using Fuzzy Radial Basis Functions," International Journal of Machine Learning and Computing vol. 8, no. 1, pp. 44-48, 2018.

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