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Mehmet Fatih Akay
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2020 – today
- 2024
- [j19]Fatih Abut
, Ezgi Akça, Mehmet Fatih Akay
Harnessing AI for Health: Optimized Neural Network Models for Resting Metabolic Rate Prediction. IEEE Access 12: 156050-156064 (2024)
2010 – 2019
- 2019
- [j18]Fatih Abut, Mehmet Fatih Akay, James D. George:
A robust ensemble feature selector based on rank aggregation for developing new VO2max prediction models using support vector machines. Turkish J. Electr. Eng. Comput. Sci. 27(5): 3648-3664 (2019) - 2017
- [j17]Mehmet Fatih Akay, Fatih Abut, Ebru Çetin, Imdat Yarim, Boubacar Sow:
Support vector machines for predicting the hamstring and quadriceps muscle strength of college-aged athletes. Turkish J. Electr. Eng. Comput. Sci. 25: 2567-2582 (2017) - 2016
- [j16]Fatih Abut, Mehmet Fatih Akay, James D. George:
Developing new VO2max prediction models from maximal, submaximal and questionnaire variables using support vector machines combined with feature selection. Comput. Biol. Medicine 79: 182-192 (2016) - [j15]Mehmet Fatih Akay, Fatih Abut, Mikail Özçiloglu
Identifying the discriminative predictors of upper body power of cross-country skiers using support vector machines combined with feature selection. Neural Comput. Appl. 27(6): 1785-1796 (2016) - 2015
- [j14]Çigdem Inan Aci
A hybrid congestion control algorithm for broadcast-based architectures with multiple input queues. J. Supercomput. 71(5): 1907-1931 (2015) - [c11]Derman Akgol, Mehmet Fatih Akay:
Predicting upper body power of cross-country skiers using machine learning methods combined with feature selection. SIU 2015: 148-151 - [c10]Fatih Abut, Mehmet Fatih Akay:
Determination of the variables affecting the maximal oxygen uptake of cross-country skiers by using machine learning and feature selection algorithms. SIU 2015: 156-159 - [c9]Gozde Ozsert, Mehmet Fatih Akay:
Performance comparison of different regression methods for maximal oxygen uptake estimation of cross-country skiers. SIU 2015: 168-171 - [c8]Incilay Yildiz, Mehmet Fatih Akay:
Prediction of maximum oxygen uptake with different machine learning methods by using submaximal data. SIU 2015: 184-187 - [c7]Esin Genc, Mehmet Fatih Akay:
Development of new non-exercise maximum oxygen uptake models by using different machine learning methods. SIU 2015: 196-199 - [c6]Shahaboddin Daneshvar, Fatih Abut, Incilay Yildiz, Mehmet Fatih Akay:
Development of new upper body power prediction models for cross-country skiers by using different machine learning methods. SIU 2015: 260-263 - 2013
- [j13]Elrasheed Ismail Mohommoud Zayid
Predicting the performance measures of a message-passing multiprocessor architecture using artificial neural networks. Neural Comput. Appl. 23(7-8): 2481-2491 (2013) - [c5]Mustafa Açikkar
Intelligent regression techniques for non-exercise prediction of VO2max. SIU 2013: 1-4 - [c4]Mehmet Fatih Akay, Erman Aktürk, Aynur Balikci:
VO2max prediction from submaximal exercise test using artificial neural network. SIU 2013: 1-3 - [c3]Mehmet Fatih Akay, Erman Aktürk, Ali Erce Tuncdemir, Nezih Nusret Sen:
Predicting VO2max from submaximal exercise and non-exercise data using artificial neural networks. SIU 2013: 1-4 - [c2]Ece Aktarla, Mehmet Fatih Akay, Erman Aktürk, Mustafa Açikkar
Neural network based VO2max prediction models using maximal exercise and non-exercise data. SIU 2013: 1-4 - [c1]Erman Aktürk, Mehmet Fatih Akay, Hasan Kilitcioglu:
Performance comparison of different regression methods for VO2max estimation. SIU 2013: 1-4 - 2011
- [j12]Mehmet Fatih Akay, Elrasheed Ismail Mohommoud Zayid
Artificial neural network-based model for predicting VO2max from a submaximal exercise test. Expert Syst. Appl. 38(3): 2007-2010 (2011) - 2010
- [j11]Ipek Abasikeles, Mehmet Fatih Akay:
Performance evaluation of directory protocols on an optical broadcast-based distributed shared memory multiprocessor. Comput. Electr. Eng. 36(1): 114-131 (2010) - [j10]Mehmet Fatih Akay, Ipek Abasikeles, Mustafa Oral
Application of self organizing maps for investigating network latency on a broadcast-based distributed shared memory multiprocessor. Expert Syst. Appl. 37(4): 2937-2942 (2010) - [j9]Mehmet Fatih Akay, Ipek Abasikeles:
Predicting the performance measures of an optical distributed shared memory multiprocessor by using support vector regression. Expert Syst. Appl. 37(9): 6293-6301 (2010) - [j8]Cigdem Inan Aci
A new congestion control algorithm for improving the performance of a broadcast-based multiprocessor architecture. J. Parallel Distributed Comput. 70(9): 930-940 (2010)
2000 – 2009
- 2009
- [j7]Mehmet Fatih Akay:
Support vector machines combined with feature selection for breast cancer diagnosis. Expert Syst. Appl. 36(2): 3240-3247 (2009) - [j6]Mustafa Açikkar
Support vector machines for aerobic fitness prediction of athletes. Expert Syst. Appl. 36(2): 3596-3602 (2009) - [j5]Mustafa Açikkar
Support vector machines for predicting the admission decision of a candidate to the School of Physical Education and Sports at Cukurova University. Expert Syst. Appl. 36(3): 7228-7233 (2009) - [j4]Mehmet Fatih Akay, Cigdem Inan Aci
Support vector regression and multilayer feed forward neural networks for non-exercise prediction of VO2max. Expert Syst. Appl. 36(6): 10112-10119 (2009) - 2008
- [j3]Mehmet Fatih Akay, Constantine Katsinis:
Contention resolution on a broadcast-based distributed shared memory multiprocessor. IET Comput. Digit. Tech. 2(1): 45-55 (2008) - [j2]Mehmet Fatih Akay, Constantine Katsinis:
Performance improvement of parallel programs on a broadcast-based distributed shared memory multiprocessor by simulation. Simul. Model. Pract. Theory 16(3): 338-352 (2008) - 2002
- [j1]Sergey N. Kharkovsky, Mehmet Fatih Akay, Ugur Cem Hasar
Measurement and monitoring of microwave reflection and transmission properties of cement-based specimens. IEEE Trans. Instrum. Meas. 51(6): 1210-1218 (2002)
Coauthor Index
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