Michal Tkác
Management Science and Operations Research · 2016
A researcher in the Science corpus: 1 paper; trusts 14 researchers and is trusted by 2 researchers here, as inferred from the citation graph.
Subfields
- Management Science and Operations Research — 39 citations into it; #9,991 of 11,946 by trust here, #6,888 by citations
- Artificial Intelligence — 33 citations into it; #29,602 of 35,345 by trust here, #25,040 by citations
- Economics and Econometrics — 20 citations into it
- Accounting — 18 citations into it; #7,404 of 8,970 by trust here, #6,570 by citations
- Finance — 17 citations into it
- Time-Series & Forecasting — 11 citations into it
- Electrical and Electronic Engineering — 9 citations into it
Whom Michal Tkác trusts overall
Their strongest outbound trust, strongest first, inferred from their citations.
- David West
- S. Mirjalili
- Esmaeil Hadavandi
- Tian-Shyug Lee
- Chih-Fong Tsai
- Siti Zaiton Mohd Hashim
- Scott A. Dellana
- Hassan Shavandi
- Hong Wang
- Pei-Chann Chang
Who trusts Michal Tkác overall
Papers from Michal Tkác's perspective
Ordered by how strongly the researchers Michal Tkác trusts endorse each paper. Same corpus, a different order for every researcher.
- Neural networks in business: techniques and applications for the operations researcher (Computers & Operations Research)
- Stock market prediction of S&P 500 via combination of improved BCO approach and BP neural network
- Credit scoring using the hybrid neural discriminant technique (Expert systems with applications)
- Credit rating analysis with support vector machines and neural networks: a market comparative study
- Using neural networks for forecasting volatility of S&P 500 Index futures prices
- Neural network applications in finance: A review and analysis of literature (1990-1996)
- Forecasting stock markets using wavelet transforms and recurrent neural networks: An integrated system based on artificial bee colony algorithm
- Neural network ensemble strategies for financial decision applications (Computers & Operations Research)
- Using neural network ensembles for bankruptcy prediction and credit scoring (Expert systems with applications)
- A two-stage hybrid credit scoring model using artificial neural networks and multivariate adaptive regression splines (Expert systems with applications)
Their papers
- Artificial neural networks in business: Two decades of research (2016) — 313 citations