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Borahan Tümer
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2020 – today
- 2023
- [j7]Kutalmis Coskun
, Borahan Tümer
:
Learning under concept drift and non-stationary noise: Introduction of the concept of persistence. Eng. Appl. Artif. Intell. 123(Part B): 106363 (2023) - [j6]Zeynep Kumralbas
, Hazel Çavus
, Kutalmis Coskun
, Borahan Tümer
:
Autonomous acquisition of arbitrarily complex skills using locality based graph theoretic features: a syntactic approach to hierarchical reinforcement learning. Evol. Syst. 14(6): 957-980 (2023) - 2022
- [j5]Engin Durmaz
, M. Borahan Tümer
:
Intelligent software debugging: A reinforcement learning approach for detecting the shortest crashing scenarios. Expert Syst. Appl. 198: 116722 (2022) - [j4]Kutalmis Coskun
, M. Borahan Tümer
:
An adaptive estimation method with exploration and exploitation modes for non-stationary environments. Pattern Recognit. 129: 108702 (2022) - [c9]Kutalmis Coskun
, Zeynep Kumralbas
, Hazel Çavus
, Borahan Tümer
:
A Syntactic Pattern Recognition Based Approach to Online Anomaly Detection and Identification on Electric Motors. GCPR 2022: 116-132 - [c8]Müjdat Soytürk
, Kutalmis Coskun
, Onur Izmitlioglu, Borahan Tümer
, Deniz Günes, Sinan Saraçoglu, Baris Bulut, Hasan Burak Ketmen, Ismethan Hanedar, Tasemir Asan, Eray Aydin:
An AI-based Architecture Framework for Improving End-of-line Reliability Tests of Electric Motors. IECON 2022: 1-6 - [c7]Ekrem Talha Selamet, Borahan Tümer:
Context Detection and Identification In Multi-Agent Reinforcement Learning With Non-Stationary Environment. SIU 2022: 1-4 - 2020
- [j3]Baris Gün Sürmeli, M. Borahan Tümer
:
Multivariate Time Series Clustering and its Application in Industrial Systems. Cybern. Syst. 51(3): 315-334 (2020)
2010 – 2019
- 2017
- [c6]Ezdin Aslanci, Kutalmis Coskun
, Peter Schüller
, M. Borahan Tümer
:
Detection of regime switching points in non-stationary sequences using stochastic learning based weak estimation method. INDIN 2017: 787-792 - [c5]Baris Gün Sürmeli, Feyza Eksen, Bilal Dinc, Peter Schüller
, M. Borahan Tümer
:
Unsupervised mode detection in cyber-physical systems using variable order Markov models. INDIN 2017: 841-846
2000 – 2009
- 2006
- [j2]M. Borahan Tümer
, Mert C. Demir:
An adaptive signal compression system with pre-specified reconstruction quality and compression rate. Comput. Methods Programs Biomed. 81(2): 99-105 (2006) - 2005
- [c4]Aleksei Ustimov, M. Borahan Tümer
:
Construction of a Learning Automaton for Cycle Detection in Noisy Data Sequences. ISCIS 2005: 543-552 - [c3]M. Borahan Tümer
, Mert C. Demir:
A Genetic Approach to Data Dimensionality Reduction Using a Special Initial Population. IWINAC (2) 2005: 310-316 - 2003
- [j1]M. Borahan Tümer
, Lee A. Belfore II, Kristina M. Ropella:
A syntactic methodology for automatic diagnosis by analysis of continuous time measurements using hierarchical signal representations. IEEE Trans. Syst. Man Cybern. Part B 33(6): 951-965 (2003) - [c2]M. Borahan Tümer
, Betül Demiröz:
Signal Compression Using Growing Cell Structures: A Transformational Approach. ISCIS 2003: 952-959
1990 – 1999
- 1998
- [c1]M. Borahan Tümer, Lee A. Belfore II, Kristina M. Ropella:
A diagnosis methodology for continuous time measurements using hierarchical signal representations. SMC 1998: 3038-3043
Coauthor Index
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