Prof. Dr. MUSTAFA BORAHAN TÜMER

International Conference on Intelligent and Fuzzy Systems, INFUS 2019, İstanbul, Türkiye, 23 - 25 Temmuz 2019, cilt.1029, ss.247-256, (Tam Metin Bildiri)

5. Unsupervised Mode Detection in Cyber-Physical Systems using Variable Order Markov Models

Surmeli B. G., Eksen F., Dinc B., Schuller P., Tumer B.

15th IEEE International Conference on Industrial Informatics (INDIN), Emden, Almanya, 24 - 26 Temmuz 2017, ss.841-846, (Tam Metin Bildiri)

6. Detection of Regime Switching Points in Non-Stationary Sequences using Stochastic Learning based Weak Estimation Method

Aslanci E., Coskun K., Schuller P., Tumer B.

15th IEEE International Conference on Industrial Informatics (INDIN), Emden, Almanya, 24 - 26 Temmuz 2017, ss.787-792, (Tam Metin Bildiri)

Kitaplar 1

1. Signal Compression Using Growing Cell Structures: A Transformational Approach

Tümer M. B.

Lecture Notes in Computer Science - vol. LNCS2869, Adnan Yazıcı,Cevat Şener, Editör, Springer-Verlag , Heidelberg, ss.952-959, 2003

Metrikler

Yayın

Yayın (WoS)

Yayın (Scopus)

Atıf (WoS)

H-İndeks (WoS)

Atıf (Scopus)

H-İndeks (Scopus)

Atıf (Scholar)

H-İndeks (Scholar)

Proje

Tez Danışmanlığı

Açık Erişim

BM Sürdürülebilir Kalkınma Amaçları

Prof. Dr. MUSTAFA BORAHAN TÜMER

Yayınlar & Eserler

1. Incremental learning of spatio-temporal Markov chains: An introductory theoretical framework for composite domain Markov chains

2. Autonomous acquisition of arbitrarily complex skills using locality based graph theoretic features: a syntactic approach to hierarchical reinforcement learning

3. Learning under concept drift and non-stationary noise: Introduction of the concept of persistence

4. An adaptive estimation method with exploration and exploitation modes for non-stationary environments

5. Intelligent software debugging: A reinforcement learning approach for detecting the shortest crashing scenarios

6. Multivariate Time Series Clustering and its Application in Industrial Systems

7. An adaptive signal compression system with pre-specified reconstruction quality and compression rate

8. A syntactic methodology for automatic diagnosis by analysis of continuous time measurements using hierarchical signal representations

1. An AI-based Architecture Framework for Improving End-of-line Reliability Tests of Electric Motors

2. A Syntactic Pattern Recognition Based Approach to Online Anomaly Detection and Identification on Electric Motors

3. Context Detection and Identification In Multi-Agent Reinforcement Learning With Non-Stationary Environment Çok Etmenli Pekiştirmeli Öǧrenmede Devingen Ortamlarda Baǧlam Deǧişim Tespiti ve Tanimlama

4. Multi-class categorization of user-generated content in a domain specific medium: Inferring product specifications from e-commerce marketplaces

5. Unsupervised Mode Detection in Cyber-Physical Systems using Variable Order Markov Models

6. Detection of Regime Switching Points in Non-Stationary Sequences using Stochastic Learning based Weak Estimation Method

7. Hierarchical Reinforcement Learning with Context Detection (HRL-CD)

8. A Low-Complexity Constructive Learning Automaton Approach to Handwritten Character Recognition

9. Construction of a learning automaton for cycle detection in noisy data sequences

10. A Genetic Approach to Data Dimensionality Reduction Using a Special Initial Population

11. Signal compression using growing cell structures: A transformational approach

12. Demand Forecasting via Learning Automata

13. A diagnosis methodology for continuous time measurements using hierarchical signal representations

14. Applying hierarchical fuzzy automatons to automatic diagnosis