prof.dr.ir. (Hennie) HAM Daniels

prof.dr.ir. (Hennie) HAM Daniels

Professor of Knowledge Management

Full Professor RSM - Rotterdam School of Management Department of Technology and Operations Management
Location
Burg. Oudlaan 50, Rotterdam
Email
hdaniels@rsm.nl
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Hennie Daniels is a professor of knowledge management at the Department of Technology and Operations Management, Rotterdam School of Management, Erasmus University.

Hennie Daniels is a professor of knowledge management at the Department of Technology and Operations Management, Rotterdam School of Management, Erasmus University.

        • R.J.M.A. Triepels, H.A.M. Daniels & A.F. Feelders (2018). Data Driven Fraud Detection in International Shipping. Expert Systems with Applications, 99, 193-202. doi: 10.1016/j.eswa.2018.01.007
        • R.J.M.A. Triepels, A.F. Feelders & H.A.M. Daniels (2015). Uncovering Document Fraud in Maritime Freight Transport Based on Probabilistic Classification. Lecture Notes in Computer Science, 9339 (23), 1-12. doi: 10.1007/978-3-319-24369-623
        • E. van Beek & H.A.M. Daniels (2014). A non-parametric test for partial monotonicity in multiple regression. Computational Economics, 44 (1), 87-100. doi: 10.1007/s10614-013-9386-7
        • L. Liu, H.A.M. Daniels, M.P.A. van Oosterhout & J. van Dalen (2013). Business Intelligence for Improving Supply Chain Risk Management. International Journal in Advanced Logistics, 2 (2), 18-29. doi: 10.1080/2287108X.2013.11006084
        • E.A.M. Caron & H.A.M. Daniels (2013). Explanatory analytics in OLAP. International Journal of Business Intelligence Research, 4 (3), 67-82. doi: 10.4018/ijbir.2013070105
        • H.A.M. Daniels & M. Velikova (2010). Monotone and partially monotone neural networks. IEEE Transactions on Neural Networks, 21 (6), 906-917. doi: 10.1109/TNN.2010.2044803
        • A. Minin, B. Lang, M. Velikova & H.A.M. Daniels (2010). Comparison of universal approximators incorporating partial monotonicity by structure. Neural Networks, 23 (4), 471-475. doi: 10.1016/j.neunet.2009.09.002
        • H.A.M. Daniels & E.A.M. Caron (2009). Automated explanation of financial data. International Journal of Intelligent Systems in Accounting, Finance and Management, 16 (1-2), 5-19. doi: 10.1002/isaf.290
        • E.A.M. Caron & H.A.M. Daniels (2008). Explanation of exceptional values in multi-dimensional databases. European Journal of Operational Research, 188 (3), 884-897. doi: 10.1016/j.ejor.2007.04.039
        • M. Velikova, H.A.M. Daniels & A.J. Feelders (2006). Mixtures of Monotone Networks for Prediction. International Journal of Computational Intelligence, 3 (3), 205-214.
        • H.A.M. Daniels & N. Noordhuis (2005). Project selection based on intellectual capital scorecards. International Journal of Intelligent Systems in Accounting, Finance and Management, 13 (1), 27-32.
        • M. Velikova & H.A.M. Daniels (2004). Decision Tree's for Monotone Price Models. Computational Management Science, 1 (3/4), 231-244.
        • A.J. Feelders & H.A.M. Daniels (2001). A General Model for Automated Business Diagnosis. European Journal of Operational Research, 130 (3), 623-637. doi: 10.1016/S0377-2217(99)00428-2
        • H.A.M. Daniels, A.J. Feelders & M. Holzheimer (2000). Methodological and Practical Aspects of Datamining. Information and Management, 37 (5), 271-281. doi: 10.1016/S0378-7206(99)00051-8
        • H.A.M. Daniels & B. Kamp (1999). Application of MLP Networks to Bond Rating and House Pricing. Neural Computing and Applications, 8 (3), 226-234.
        • J.E.J. Plasmans, H.A.M. Daniels & W. Verkooijen (1998). Estimating structural exchange rate models by artificial neural networks. Applied Financial Economics, 8 (5), 541-551. doi: 10.1080/096031098332844
        • H.A.M. Daniels, B. Kamp & W. Verkooijen (1997). Modelling non-linearity in economic classification with neural networks. International Journal of Intelligent Systems in Accounting, Finance and Management, 6 (4), 287-301.
        • W.J. Verkooijen & H.A.M. Daniels (1995). Building error-correction models with neural networks: an application to the Dutch mortgage loan market. Economic and Financial Computing, 5 (2), 101-130.
        • R.J. Berndsen & H.A.M. Daniels (1994). Causal Reasoning and Explanation in Dynamic Economic Systems. Journal of Economic Dynamics and Control, 251-271.
        • W.J. Verkooijen & H.A.M. Daniels (1994). Connectionist Projection Pursuit Regression. Computational Economics, 7 (3), 155-161.
        • J.M. Broek & H.A.M. Daniels (1991). Application of constraint logic programming to asset and liability management in banks. Computer Science in Economics and Management, 4, 107-116. doi: 10.1007/BF00436285
        • H.A.M. Daniels (2016). Beveiliging Persoonsgegevens van Levensbelang (interview by Ruby Sanders). Elseviers Weekblad, oktober (bijlage Digital Transformation), 11-12.
      • M. Velikova & H.A.M. Daniels (2008). Monotone prediction models in data mining. Saarbrücken: VDM Verlag
      • H.A.M. Daniels (1998). Van Kunstmatige Intelligentie naar de Kenniseconomie. Rotterdam: Eburon
      • R.J.M.A. Triepels, H.A.M. Daniels & R. Heijmans (2018). Detection and Explanation of Anomalous Payment Behaviour in Real-Time Gross Settlement Systems. In Lecture Notes in Business Information Processing (pp. 145-161). Cham: Springer Verlag
      • H.A.M. Daniels & H. Noordhuis (2002). Management of Intellectual Capital by Optimal Portfolio Selection. In G. Goos & J. Hartmanis (Eds.), Practical Aspects of Knowledge Management - Lecture Notes on Artificial Intelligence. Berlin: Springer
      • H.A.M. Daniels & H.G. van Dissel (2002). Risk Management based on Expert Rules and Data Mining: A case study in Insurance. In Proceedings of the 10th European Conference on Information Systems (ECIS), Gdansk
      • H.A.M. Daniels & A.J. Feelders (2001). Integrating economic knowledge in data mining algorithms. In Proceedings SBIT Symposium, Tilburg
      • H.A.M. Daniels & A.J. Feelders (2001). Combining Domain Knowledge and Data for House Price Modelling with Classification Trees and Neural Networks. In Proceedings of the 5th European Conference on Principles and Practice of Knowledge Discovery in Databases, Datamining in Marketing Applications, Freiburg
      • H.A.M. Daniels & A.J. Feelders (2001). On the Implementation of Monotonicity in Economic Decision Problems. In - - (Ed.), Proceedings of the 8th International Conference on Connexionist Approaches in Economics and Management, Rennes (pp. 25-34). Rennes: ACSEG
      • A.J. Feelders & H.A.M. Daniels (1999). Knowledge Discovery in Practice. In H. Jessen (Ed.), Proceedings of the International Conference Machine Learning and Applications, ACAI 99, Workshop 08: Data Mining in Economics, Marketing and Finance, Chania (pp. 1-8). -: -
      • H.A.M. Daniels, B. Kamp & W. Verkooijen (1998). Forecasting and classification with neural networks: application to the mortgage market and bond rating. In ? redacteur? (Ed.), Proceedings 18th International Symposium on Forecasting (ISF 98) (pp. 10-10). Edinburgh: Napier University
      • H.A.M. Daniels & B. Kamp (1998). Application of neural networks to bond rating. In J.-M. Aurifeille & C. Deissenberg (Eds.), Bio-mimetic approaches in management science Chapter 3 (Advances in computational management science, 1) (pp. 27-45). Boston, Dordrecht: Kluwer Academic Publishers
      • H.A.M. Daniels, W. Verkooijen & A.J. Feelders (1996). Kennissystemen voor financiële diagnose: taak en modelperspectief. In J.A.M. Oonincx, P.M.A. Ribbers & C.A.Th. Takkenberg (Eds.), Organisatie, Besturing en Informatie: Ontwikkeling van Theorie en Praktijk. Liber Amicorum bij het afscheid van Prof.dr.ir. G.C.J.F. Nielen (pp. 307-332). Alphen a/d Rijn: Samson
      • H.A.M. Daniels, B. Kamp & W. Verkooijen (1996). Controlling the Flexibility of Neural Networks: An empirical study in Financial Modelling (Management Report Series,ERASM). In - - (Ed.), Paper presented as abstract in the Proceedings of the third International Conference on Computing in Economics and Finance, Stanford(1997( (pp. 1-20). -: -
      • H.A.M. Daniels, B. Kamp & W. Verkooijen (1996). Design of neural networks for prediction and classification in economic problems. In Lj. Vlaecic, T. Nguyen & D. 'Ce'cez-Kecmanovi'c (Eds.), Modelling and Control of National and Regional Economics, 1995. Proceedings of the IFAC/IFIP/IFORS/SEDS Symposium, Gold Coast, Queensland, Australia (pp. 387-397). Brisbane, Australia: Pergamon Press
      • A.J. Feelders & H.A.M. Daniels (1994). A formal Framework for Diagnosis in Business Performance. In @ @ (Ed.), Proceedings of the International Conference on Intelligent Systems (pp. 123-134). Singapore: 2
        • E.A.M. Caron & H.A.M. Daniels (2004). Diagnosis in the OLAP context. (Intern rapport, ERIM report series Research in Management, no 2004-063). :
        • H.A.M. Daniels & B. de Jonge (2003). Project Selection Directed by Intellectual Capital Scorecards. (Intern rapport, ERIM series, no ERS-2003-l). onbekend: Rotterdam School of Management
        • H.A.M. Daniels & A.J. Feelders (2000). Combining Domain Knowledge and Data in Datamining Systems. (Extern rapport, 2000-63). Tilburg: Tilburg University
        • H.A.M. Daniels, B. Kamp & W. Verkooijen (1997). Application of neutral networks to house pricing and bond rating. (Extern rapport, Discussion paper, no 9796). Tilburg: Tilburg University
        • H.A.M. Daniels & A.J. Feelders (2000). Combining Domain Knowledge and Data in Datamining Systems. (Extern rapport, CentER research paper, no 2000-63). Tilburg: Tilburg University, CentER
        • H.A.M. Daniels, B. Kamp & W.J. Verkooijen (1996). Controlling the flexibility of neural networks: an empirical study in financial modelling. (Intern rapport, Management Report, no 288). :
        • R.P.A.J. Verkooijen & H.A.M. Daniels (1995). Long Run Exchange Rate Determination: a Neural Network Study. (Extern rapport). Tilburg: Tilburg University, Centre for Economic Research
        • A.J. Feelders & H.A.M. Daniels (1999). Business aspects of Data Mining. (Intern rapport, ERASM Management Report Series, no 48-1999). :
        • A.J. Feelders & H.A.M. Daniels (1998). A general model for automated business diagnosis. (Intern rapport, Management Report Series, no 22-1998). : ERIM
        • E.A.M. Caron & H.A.M. Daniels (2018). Sensitivity Analysis in OLAP databases. In Proceedings of the 20th International Conference on Enterprise Information Systems
        • R.J.M.A. Triepels & H.A.M. Daniels (2016). A Comparison of Three Models to Predict Liquidity Flows between Banks Based on Daily Payments Transactions. In 14th Payment and Settlement System Simulation Seminar and Workshop. Helsinki: Bank of Finland
        • R.J.M.A. Triepels & H.A.M. Daniels (2016). Supervision of Financial Market Infrastructures using Temporal Network Analysis. In Book of Abstracts, 22nd International Conference on Computational Economics. Bordeaux
        • E.A.M. Caron & H.A.M. Daniels (2016). Identification of Organization Name Variants in Large Databases using Rule-based Scoring and Clustering - With a Case Study on the Web of Science Database. In 18th International Conference on Enterprise Information Systems (ICEIS 2016) (pp. 182-187). Rome, Italy: SCITEPRESS
        • L. Liu, H.A.M. Daniels & R.J.M.A. Triepels (2014). Auditing Data Reliability in International Logistics - An Application of Bayesian Networks. In Proceedings of the 16th International Conference on Enterprise Information Systems (pp. 707-712). Lissabon
        • L. Liu, H.A.M. Daniels & W.J. Hofman (2014). Business Intelligence for Improving Supply Chain Risk Management. In Springer Lecture Notes in Business Information Systems
        • L. Lingzhe, H.A.M. Daniels & W. Hoffmann (2013). Detecting and Explaining Business Exceptions for Risk Assessment. In Hammoudi et.al. (Ed.), Proceedings of the 15th International Conference on Enterprise Information Systems (pp. 442-447). Angers
        • L. Lingzhe & H.A.M. Daniels (2013). Analysis for Detecting and Explaining Exceptions in Business Data. In Dianne Lux Wigand et.al. (Ed.), Proceedings of the 26th e Bled Conference (pp. 349-358). Bled
        • E.A.M. Caron & H.A.M. Daniels (2012). Explanatory Analysis in Business Intelligence Systems. In proceedings of the European Conference on Information Systems ECIS (pp. 77-89). Barcelona
        • H.A.M. Daniels & E.A.M. Caron (2011). Analysis of variance in OLAP information systems. In 8th International conference on Computational Management Science (pp. 16). Neuchatel, Switzerland: University of Neuchatel
        • E.A.M. Caron & H.A.M. Daniels (2010). What-if analysis in OLAP, with a case study in supermarket sales data. In Proceedings of the 12th International Conference on Enterprise Information Systems (pp. 208-213). Fuchal
        • E.A.M. Caron & H.A.M. Daniels (2009). Business Analysis in the OLAP context. In J Cordeiro & J Filipe (Eds.), Proceedings ICEIS 2009: Artifical Intelligence and Decision Support Systems (pp. 325-330). Milan: INSTICC
        • M. Velikova & H.A.M. Daniels (2009). On testing monotonicity of datasets. In Proceeding of European Conference on Machine Learning (pp. 11-23). Bled
        • E.A.M. Caron & H.A.M. Daniels (2008). Extensions to the OLAP framework for business analysis. In B..Shishkov A. Ranchordas J. Cordeiro (Ed.), Third international conference on software and data technologies - ICSOFT 2008 (pp. 240-247). Porto: INSTICC
        • M. Velikova, H.A.M. Daniels & M. Samulski (2008). Partially monotone Networks applied to Breast Cancer Detection on Mammograms. In Neruda.R. Koutnik J. Kurkova-Pohlova V. (Ed.), Proceedings of the 18th International Conference on artificial neural networks (ECANN 2008) Vol. 5163. Lecture Notes in Computer Science (pp. 917-926). Heidelberg: Springer- Verlag
        • H.A.M. Daniels & E.A.M. Caron (2007). Explanation generation in business performance models - With a case study in competition benchmarking. In J..Cordeiro J. Filipe J. Cardoso (Ed.), Proceedings ICEIS 2007 Artificial Intelligence and Decision Support Systems (pp. 119-128). Funchal, Portugal: INSTICC
        • H.A.M. Daniels & M.T. Smits (2005). Portfolio Optimisation as a Tool for Knowledge Management. In Haasis et. al. (Ed.), Operations Research Proceedings 2005, Part 17 Managerial Accounting (pp. 633-639). Springer Verlag
        • E.A.M. Caron & H.A.M. Daniels (2004). Automated Business Diagnosis in the OLAP Context. In H. Fleuren & .P..Kort D. den Hertog (Eds.), Operations Research Proceedings 2004 (pp. 425-433). Berlin: Springer
        • H.A.M. Daniels & B. de Jonge (2003). Project Selection in Knowledge Intensive Organisations. In proceedings of the 11th European conference on Information Systems. Napels: ECIS
        • H.A.M. Daniels & M. Velikova (2003). Derivation of monotone decision models from noisy data. In Proceeding International Conference. Crete: Book of Abstracts
        • H.A.M. Daniels (2001). Fusion of Expert Decision Rules and Knowledge derived from Databases. In EURO 2001. Rotterdam
        • R.J.M.A. Triepels, R. Heijmans & H.A.M. Daniels (2017). Anomaly Detection in Real-Time Gross Payment Data. In Proceedings of the 19th International Conference on Enterprise Information Systems, (ICEIS 2017) (pp. 433-441)
        • E.A.M. Caron & H.A.M. Daniels (2004). Extending the OLAP Framework for Automated Explanatory Tasks. In Conference on Computational Economics and Finance (CEF 2004), 1 page extended abstract
        • W. Heijden, M. Homberg, M. Marijnis, M. Graaff de & H.A.M. Daniels (2018). Combining Open Data and Machine Learning to predict Food Security in Ethiopia. 5th International Conference on Technologies for Developed: Lausanne.
        • R.J.M.A. Triepels & H.A.M. Daniels (2016). A Comparison of Three Models to Predict Liquidity Flows between Banks Based on Daily Payments Transactions.
        • R.J.M.A. Triepels & H.A.M. Daniels (2015). Detecting shipping fraud in global supply chains using probabilistic trajectory classification. 17th International Conference on Enterprise Information Systems: Barcelona (2015, april 27 - 2015, april 30).
        • L. Lingzhe, H.A.M. Daniels & H. Weigand (2012). A business intelligence framework for risk assessment in business networks. European Conference on Information Systems ECIS: Barcelona.
        • L. Lingzhe & H.A.M. Daniels (2012). Towards a value model for collaborative, business intelligence-supported risk assessment. International workshop on Value Based Modelling: Vienna.
        • M. Timmermans, R. Heijmans & H.A.M. Daniels (2017). Cyclical patterns in risk indicators based on financial market infrastructure transaction data.
        • R.J.M.A. Triepels, H.A.M. Daniels & R. Heijmans (2017). Anomaly Detection in Real-Time Gross Payment Data. Financial Market Infrastructure Conference II, Contribution to conference: New Thinking in a New Area: Amsterdam, June 2017.
        • H.A.M. Daniels (2017). Agile biedt projectmanager oude stijl kansen.
        • H.A.M. Daniels & M. Bosch (2016). Trends in Data Science, interview with Future Consult.
        • H.A.M. Daniels & S. Brinkkemper (2016). Interview Business Intelligence: geen moderne flauwekul, Interviews with Daniels H.A.M. and Brinkkemper S.
      • M. Velikova, H.A.M. Daniels & A.J. Feelders (Ed.). (2006). Solving Partially Monotone Problems with Neural Networks, Transactions on Engineering Computing and Technology (12). Austria: Proceedings of ICCS'06 Vienna
      • H.A.M. Daniels, M.T. Smits, H.D. Haasis, H. Kopfer & J. Schonberger (Ed.). (2005). Portfolio Optimisation as a Tool for Knowledge Management, Operations Research Proceedings 2005 (Part 17 Managerial Accounting). Bremen: Springer Verlag
    • Explanation of Exceptional Values in Multi-dimensional Business Databases

      Emiel Caron

      Explanation of Exceptional Values in Multi-dimensional Business Databases

    • Knowledge Discovery and Monotonicity

      Viara Popova

      Knowledge Discovery and Monotonicity

  • Full Professor

    University
    Erasmus University Rotterdam
    School
    RSM - Rotterdam School of Management
    Department
    Department of Technology and Operations Management

Address

Visiting address

Burg. Oudlaan 50 3062 PA Rotterdam

Postal address

Postbus 1738 3000 DR Rotterdam