Melek Acar Boyacioglu

Management Science and Operations Research · 2010–2011

A researcher in the Science corpus: 2 papers; trusts 10 researchers and is trusted by 14 researchers here, as inferred from the citation graph.

Subfields

• Management Science and Operations Research — 22 citations into it; #2,856 of 11,946 by trust here, #2,667 by citations
• Artificial Intelligence — 15 citations into it; #18,374 of 35,345 by trust here, #26,682 by citations
• Economics and Econometrics — 10 citations into it; #6,427 of 23,481 by trust here, #7,944 by citations
• Time-Series & Forecasting — 7 citations into it
• Control and Systems Engineering — 6 citations into it
• Electrical and Electronic Engineering — 5 citations into it

Whom Melek Acar Boyacioglu trusts overall

Their strongest outbound trust, strongest first, inferred from their citations.

1. D. McMillan
2. Kyoung-jae Kim
3. George S. Atsalakis
4. Mark T. Leung
5. Vladimir Naumovich Vapni
6. Chih-Jen Lin
7. An-Sing Chen
8. Kimon P. Valavanis
9. Hazem Daouk
10. Yudong Zhang

Who trusts Melek Acar Boyacioglu overall

1. Hakan Gunduz
2. Ahmad Bagheri
3. Will Serrano
4. Yusuf Yaslan
5. Ehsan Hoseinzade
6. Jingyi Shen
7. Hamed Mohammadi Peyhani
8. Jigar Patel
9. Alaa F. Sheta
10. Mojtaba Nabipour

Papers from Melek Acar Boyacioglu's perspective

Ordered by how strongly the researchers Melek Acar Boyacioglu trusts endorse each paper. Same corpus, a different order for every researcher.

1. Common risk factors in the returns on stocks and bonds
2. The Nature of Statistical Learning Theory
3. Genetic algorithms approach to feature discretization in artificial neural networks for the prediction of stock price index
4. A comparison between Fama and French's model and artificial neural networks in predicting the Chinese stock market
5. Forecasting stock market short-term trends using a neuro-fuzzy based methodology
6. Surveying stock market forecasting techniques - Part II: Soft computing methods
7. LIBSVM: A library for support vector machines
8. Support vector machine approach for protein subcellular localization prediction (Bioinform.)
9. Financial time series forecasting using support vector machines
10. A TSK type fuzzy rule based system for stock price prediction

Their papers

• Predicting direction of stock price index movement using artificial neural networks and support vector machines: The sample of the Istanbul Stock Exchange (2011) — 886 citations
• An Adaptive Network-Based Fuzzy Inference System (ANFIS) for the prediction of stock market return: The case of the Istanbul Stock Exchange (2010) — 409 citations