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ORCIDPetr Hájek 0002
Person information
- affiliation: University of Pardubice, Czech Republic
Other persons with the same name
- Petr Hájek 0001 — Czech Academy of Sciences, Institute of Computer Science (ICS), Prague, Czech Republic
- Petr Hájek 0003
![[0000-0003-1814-1904]](https://dblp.org/img/orcid-mark.12x12.png "0000-0003-1814-1904")
— Brno University of Technology, Czech Republic (and 1 more)
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2020 – today
- 2024
[j34]Md. Iftekharul Alam Efat, Petr Hájek, Mohammad Zoynul Abedin, Rahat Uddin Azad, Md. Al Jaber, Shuvra Aditya, Mohammad Kabir Hassan:
Deep-learning model using hybrid adaptive trend estimated series for modelling and forecasting sales. Ann. Oper. Res. 339(1-2): 297-328 (2024)- [j33]Fan Yang, Mohammad Zoynul Abedin, Petr Hájek:
An explainable federated learning and blockchain-based secure credit modeling method. Eur. J. Oper. Res. 317(2): 449-467 (2024) - [j32]Fan Yang, Yanan Qiao, Petr Hájek, Mohammad Zoynul Abedin:
Enhancing cardiovascular risk assessment with advanced data balancing and domain knowledge-driven explainability. Expert Syst. Appl. 255: 124886 (2024) - [j31]Petr Hájek, Michal Munk:
Corporate financial distress prediction using the risk-related information content of annual reports. Inf. Process. Manag. 61(5): 103820 (2024) - [c47]Petr Hájek, Josef Novotny:
Beyond Sentiment in Stock Price Prediction: Integrating News Sentiment and Investor Attention with Temporal Fusion Transformer. AIAI (3) 2024: 30-43 - [c46]Andrew Asante, Petr Hájek:
Detecting Antisocial Behavior on Social Media During COVID-19 Lockdown. NiDS 2024: 189-200 - [c45]Zeru Kifle Kebede, Petr Hájek:
Detection of IoT Cyberattacks in Smart Cities: A Comparative Analysis of Deep Learning and Ensemble Learning Methods. NiDS 2024: 549-560 - 2023
- [j30]Md Shajalal, Petr Hájek, Mohammad Zoynul Abedin:
Product backorder prediction using deep neural network on imbalanced data. Int. J. Prod. Res. 61(1): 302-319 (2023) - [j29]Petr Hájek, Mohammad Zoynul Abedin, Uthayasankar Sivarajah:
Fraud Detection in Mobile Payment Systems using an XGBoost-based Framework. Inf. Syst. Frontiers 25(5): 1985-2003 (2023) - [j28]Petr Hájek, Michal Munk:
Speech emotion recognition and text sentiment analysis for financial distress prediction. Neural Comput. Appl. 35(29): 21463-21477 (2023) - [c44]Petr Hájek, Vladimír Olej:
Hierarchical Intuitionistic TSK Fuzzy System for Bitcoin Price Forecasting. FUZZ 2023: 1-6 - 2022
- [j27]Farhana Akter Sunny, Petr Hájek, Michal Munk, Mohammad Zoynul Abedin, Md. Shahriare Satu, Md. Iftekharul Alam Efat, Md. Jahidul Islam:
A Systematic Review of Blockchain Applications. IEEE Access 10: 59155-59177 (2022) - [j26]Petr Hájek, Josef Novotny:
Fuzzy Rule-Based Prediction of Gold Prices using News Affect. Expert Syst. Appl. 193: 116487 (2022) - [j25]Petr Hájek, Wojciech Froelich, Vladimír Olej, Josef Novotny:
Neural intuitionistic fuzzy system with justified granularity. Neural Comput. Appl. 34(22): 19423-19439 (2022) - [c43]Petr Hájek:
Speech Emotion Recognition from Earnings Conference Calls in Predicting Corporate Financial Distress. AIAI (1) 2022: 216-228 - 2021
- [j24]Mohammad Zoynul Abedin, Guotai Chi, Mohammed Mohi Uddin, Md. Shahriare Satu, Md. Imran Khan, Petr Hájek:
Tax Default Prediction Using Feature Transformation-Based Machine Learning. IEEE Access 9: 19864-19881 (2021) - [j23]Jan Stejskal, Petr Hájek, Viktor Prokop:
The role of library user preferences in the willingness to read and pay for e-books: case of the Czech Republic. Electron. Libr. 39(4): 639-660 (2021) - [j22]Petr Hájek, Aliaksandr Barushka, Michal Munk:
Neural Networks with Emotion Associations, Topic Modeling and Supervised Term Weighting for Sentiment Analysis. Int. J. Neural Syst. 31(10): 2150013:1-2150013:18 (2021) - [j21]Jan Stejskal, Petr Hájek, Pavel Cerny:
A novel methodology for surveying children for designing library services: A case study of the Municipal Library of Prague. J. Libr. Inf. Sci. 53(2) (2021) - [j20]Dasa Munková, Michal Munk, Lubomír Benko, Petr Hájek:
The role of automated evaluation techniques in online professional translator training. PeerJ Comput. Sci. 7: e706 (2021) - [c42]Petr Hájek, Vladimír Olej, Wojciech Froelich, Josef Novotny:
Intuitionistic Fuzzy Neural Network for Time Series Forecasting - The Case of Metal Prices. AIAI 2021: 411-422 - [c41]Abdelrahman Youssef, Petr Hájek:
The Role of Smart Economy in Developing Smart Cities. ISCSIC 2021: 276-279 - 2020
- [j19]Petr Hájek, Mohammad Zoynul Abedin:
A Profit Function-Maximizing Inventory Backorder Prediction System Using Big Data Analytics. IEEE Access 8: 58982-58994 (2020) - [j18]Petr Hájek, Wojciech Froelich, Ondrej Prochazka:
Intuitionistic fuzzy grey cognitive maps for forecasting interval-valued time series. Neurocomputing 400: 173-185 (2020) - [j17]Aliaksandr Barushka, Petr Hájek:
Spam detection on social networks using cost-sensitive feature selection and ensemble-based regularized deep neural networks. Neural Comput. Appl. 32(9): 4239-4257 (2020) - [j16]Petr Hájek, Aliaksandr Barushka, Michal Munk:
Fake consumer review detection using deep neural networks integrating word embeddings and emotion mining. Neural Comput. Appl. 32(23): 17259-17274 (2020) - [c40]Petr Hájek, Aliaksandr Barushka, Michal Munk:
Opinion Mining of Consumer Reviews Using Deep Neural Networks with Word-Sentiment Associations. AIAI (1) 2020: 419-429 - [c39]Wojciech Froelich, Petr Hájek:
Combining Rough Set-based Relevance and Redundancy for the Ranking and Selection of Nominal Features. KES 2020: 1459-1468
2010 – 2019
- 2019
- [j15]Petr Hájek, Roberto Henriques, Mauro Castelli, Leonardo Vanneschi:
Forecasting performance of regional innovation systems using semantic-based genetic programming with local search optimizer. Comput. Oper. Res. 106: 179-190 (2019) - [j14]Monika Papousková, Petr Hájek:
Two-stage consumer credit risk modelling using heterogeneous ensemble learning. Decis. Support Syst. 118: 33-45 (2019) - [j13]Petr Hájek, Wojciech Froelich:
Integrating TOPSIS with interval-valued intuitionistic fuzzy cognitive maps for effective group decision making. Inf. Sci. 485: 394-412 (2019) - [c38]Evelyn Toseafa, Petr Hájek:
Predicting Regional Credit Ratings Using Ensemble Classification with MetaCost. CSOC (2) 2019: 332-342 - [c37]Aliaksandr Barushka, Petr Hájek:
Review Spam Detection Using Word Embeddings and Deep Neural Networks. AIAI 2019: 340-350 - [c36]Petr Hájek:
Interpretable Fuzzy Rule-Based Systems for Detecting Financial Statement Fraud. AIAI 2019: 425-436 - [c35]Wojciech Froelich, Petr Hájek:
IVIFCM-TOPSIS for Bank Credit Risk Assessment. KES-IDT (1) 2019: 99-108 - [c34]Monika Papousková, Petr Hájek:
Modelling Loss Given Default in Peer-to-Peer Lending Using Random Forests. KES-IDT (1) 2019: 133-141 - 2018
- [j12]Aliaksandr Barushka, Petr Hájek:
Spam filtering using integrated distribution-based balancing approach and regularized deep neural networks. Appl. Intell. 48(10): 3538-3556 (2018) - [j11]Petr Hájek:
Predicting corporate investment/non-investment grade by using interval-valued fuzzy rule-based systems - A cross-region analysis. Appl. Soft Comput. 62: 73-85 (2018) - [j10]Petr Hájek:
Combining bag-of-words and sentiment features of annual reports to predict abnormal stock returns. Neural Comput. Appl. 29(7): 343-358 (2018) - [c33]Petr Hájek, Ondrej Prochazka, Wojciech Froelich:
Interval-valued intuitionistic fuzzy cognitive maps for stock index forecasting. EAIS 2018: 1-7 - [c32]Petr Hájek, Vladimír Olej:
Interval-Valued Intuitionistic Fuzzy Inference System for Supporting Corporate Financial Decisions. FUZZ-IEEE 2018: 1-7 - [c31]Aliaksandr Barushka, Petr Hájek:
Spam Filtering in Social Networks Using Regularized Deep Neural Networks with Ensemble Learning. AIAI 2018: 38-49 - [c30]Jan Stejskal, Viktor Prokop, Petr Hájek:
Leverage of Knowledge Sources in Firm Innovation Activities: The Case of European ICT Industries. PACIS 2018: 25 - [c29]Petr Hájek, Michaela Striteska, Viktor Prokop:
Integrating Balanced Scorecard and Fuzzy TOPSIS for Innovation Performance Evaluation. PACIS 2018: 26 - 2017
- [j9]Petr Hájek, Vladimír Olej:
Intuitionistic neuro-fuzzy network with evolutionary adaptation. Evol. Syst. 8(1): 35-47 (2017) - [j8]Petr Hájek, Roberto Henriques:
Mining corporate annual reports for intelligent detection of financial statement fraud - A comparative study of machine learning methods. Knowl. Based Syst. 128: 139-152 (2017) - [j7]Petr Hájek, Jan Stejskal:
Library usage mining in the context of alternative costs: The case of the Municipal Library of Prague. Libr. Hi Tech 35(4): 565-583 (2017) - [c28]Richard Gardiner, Petr Hájek:
Impact of GDP, Capital and Employment on Waste Generation-The Case of France, Germany and UK Regions. ICEME 2017: 94-97 - [c27]Petr Hájek, Ondrej Prochazka:
Interval-Valued Intuitionistic Fuzzy Cognitive Maps for Supplier Selection. KES-IDT (1) 2017: 207-217 - [c26]Petr Hájek, Jan Stejskal:
Innovation Paths in Knowledge Intensive Industries based on Fuzzy Set Qualitative Comparative Analysis. PACIS 2017: 287 - [c25]Petr Hájek, Ondrej Prochazka:
Learning Interval-Valued Fuzzy Cognitive Maps with PSO Algorithm for Abnormal Stock Return Prediction. TPNC 2017: 113-125 - 2016
- [c24]Aliaksandr Barushka, Petr Hájek:
Spam Filtering Using Regularized Neural Networks with Rectified Linear Units. AI*IA 2016: 65-75 - [c23]Petr Hájek, Jana Bohácová:
Predicting Abnormal Bank Stock Returns Using Textual Analysis of Annual Reports - a Neural Network Approach. EANN 2016: 67-78 - [c22]Petr Hájek, Vladimír Olej, Ondrej Prochazka:
Predicting Corporate Credit Ratings Using Content Analysis of Annual Reports - A Naïve Bayesian Network Approach. FinanceCom 2016: 47-61 - [c21]Petr Hájek, Ondrej Prochazka:
Interval-valued fuzzy cognitive maps for supporting business decisions. FUZZ-IEEE 2016: 531-536 - 2015
- [j6]Petr Hájek, Jan Stejskal:
Modelling public library value using the contingent valuation method: The case of the Municipal Library of Prague. J. Libr. Inf. Sci. 47(1): 43-55 (2015) - [c20]Petr Hájek, Vladimír Olej, Renáta Mysková:
Predicting Financial Distress of Banks Using Random Subspace Ensembles of Support Vector Machines. CSOC (1) 2015: 131-140 - [c19]Petr Hájek, Vladimír Olej:
Intuitionistic Fuzzy Neural Network: The Case of Credit Scoring Using Text Information. EANN 2015: 337-346 - [c18]Ondrej Prochazka, Petr Hájek:
Modelling Knowledge Management Processes Using Fuzzy Cognitive Maps. KMO 2015: 41-50 - [c17]Petr Hájek, Lucie Mansfeldova:
Assessing the Effect of Knowledge Management Initiatives on Stakeholder Objectives Using Fuzzy TOPSIS. KMO 2015: 60-70 - [c16]Jan Stejskal, Petr Hájek:
Modelling Knowledge Spillover Effects Using Moderated and Mediation Analysis - The Case of Czech High-Tech Industries. KMO 2015: 329-341 - [c15]Petr Hájek, Vladimír Olej:
Word Categorization of Corporate Annual Reports for Bankruptcy Prediction by Machine Learning Methods. TSD 2015: 122-130 - [c14]Renáta Mysková, Petr Hájek:
Novel Multi-word Lists for Investors' Decision Making. TSD 2015: 131-139 - 2014
- [c13]Petr Hájek, Vladimír Olej:
Defuzzification methods in intuitionistic fuzzy inference systems of Takagi-Sugeno type: The case of corporate bankruptcy prediction. FSKD 2014: 232-236 - [c12]Petr Hájek, Vladimír Olej:
Comparing corporate financial performance and qualitative information from annual reports using self-organizing maps. ICNC 2014: 93-98 - [c11]Petr Hájek, Vladimír Olej:
Predicting Firms' Credit Ratings Using Ensembles of Artificial Immune Systems and Machine Learning - An Over-Sampling Approach. AIAI 2014: 29-38 - 2013
- [j5]Petr Hájek, Krzysztof Michalak:
Feature selection in corporate credit rating prediction. Knowl. Based Syst. 51: 72-84 (2013) - [c10]Petr Hájek, Vladimír Olej:
Evaluating Sentiment in Annual Reports for Financial Distress Prediction Using Neural Networks and Support Vector Machines. EANN (2) 2013: 1-10 - [c9]Petr Hájek, Vladimír Olej:
Prediction of Air Quality Indices by Neural Networks and Fuzzy Inference Systems - The Case of Pardubice Microregion. EANN (1) 2013: 302-312 - 2012
- [j4]Petr Hájek:
Credit rating analysis using adaptive fuzzy rule-based systems: an industry-specific approach. Central Eur. J. Oper. Res. 20(3): 421-434 (2012) - [j3]Petr Hájek, Vladimír Olej:
Ozone prediction on the basis of neural networks, support vector regression and methods with uncertainty. Ecol. Informatics 12: 31-42 (2012) - [c8]Petr Hájek, Vladimír Olej:
Adaptive Intuitionistic Fuzzy Inference Systems of Takagi-Sugeno Type for Regression Problems. AIAI (1) 2012: 206-216 - 2011
- [j2]Petr Hájek:
Municipal credit rating modelling by neural networks. Decis. Support Syst. 51(1): 108-118 (2011) - [j1]Petr Hájek, Vladimír Olej:
Credit rating modelling by kernel-based approaches with supervised and semi-supervised learning. Neural Comput. Appl. 20(6): 761-773 (2011) - [c7]Vladimír Olej, Petr Hájek:
Comparison of Fuzzy Operators for IF-Inference Systems of Takagi-Sugeno Type in Ozone Prediction. EANN/AIAI (2) 2011: 92-97 - 2010
- [c6]Vladimír Olej, Petr Hájek:
IF-Inference Systems Design for Prediction of Ozone Time Series: The Case of Pardubice Micro-region. ICANN (1) 2010: 1-11 - [c5]Petr Hájek:
Probabilistic Neural Networks for Credit Rating Modelling. IJCCI (ICFC-ICNC) 2010: 289-294
2000 – 2009
- 2009
- [c4]Petr Hájek, Vladimír Olej:
Municipal Creditworthiness Modelling by Kernel-Based Approaches with Supervised and Semi-supervised Learning. EANN 2009: 35-44 - [c3]Vladimír Olej, Petr Hájek:
Municipal Creditworthiness Modelling by Radial Basis Function Neural Networks and Sensitive Analysis of Their Input Parameters. ICANN (2) 2009: 505-514 - 2008
- [c2]Petr Hájek, Vladimír Olej:
Municipal Creditworthiness Modelling by Kohonen's Self-organizing Feature Maps and LVQ Neural Networks. ICAISC 2008: 52-61 - [c1]Petr Hájek, Vladimír Olej:
Municipal Creditworthiness Modelling by Kohonen's Self-Organizing Feature Maps and Fuzzy Logic Neural Networks. ICANN (1) 2008: 533-542
Coauthor Index
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