Description: Description: Description: Description: Description: F:\Homepage S&T\images\pubhead.gif

 


Journal Articles:

1.      Zhong, X., and D. Enke, “Predicting the Daily Return Direction of the Stock Market Using Hybrid Machine Learning Algorithms,” Financial Innovation, Vol. 5(1), 24 (2019): 1-20.

2.      Subhash, S., and D. Enke, “Hedge Fund Replication Using Strategy Specific Factors,” Financial Innovation, Vol. 5(1), 11 (2019): 1-19.

3.      Kim, Y.M., and D. Enke, "A Dynamic Target Volatility Strategy for Asset Allocation using Artificial Neural Networks," The Engineering Economist, Vol. 63, No. 4 (2018): 273-290.

4.      Zhong, X., and D. Enke, “A Comprehensive Cluster and Classification Mining Procedure for Daily Stock Market Return Forecasting,” Neurocomputing, Vol. 267 (2017): 152-168.

5.      Lee, S., D. Enke, and Y. Kim, “A Relative Value Trading System based on a Correlation and Rough Set Analysis for the Foreign Exchange Futures Market,” Engineering Applications of Artificial Intelligence, Vol. 61 (2017): 47-56.

6.      Kim, Y.M., W. Ahn, K.J. Oh, and D. Enke, “An Intelligent Hybrid Trading System for Discovering Trading Rules for the Futures Market using Rough Sets and Genetic Algorithms,” Applied Soft Computing, Vol. 55 (2017): 127-140.

7.      Zhong, X., and D. Enke, “Forecasting Daily Stock Market Return Using Dimensionality Reduction,” Expert Systems with Applications, Vol. 67 (2017): 126-139.

8.      Chiang, W.C., D. Enke, T. Wu, and R. Wang, “An Adaptive Stock Index Trading Decision Support System,” Expert Systems with Applications, Vol. 59 (2016): 195-207.

9.      Kim, Y.M., and D. Enke, “Developing a Rule Change Trading System for the Futures Market using Rough Set Analysis,” Expert Systems with Applications, Vol. 59 (2016): 165-173.

10.  Mehdiyev, N., and D. Enke, “Interest Rate Prediction: A Neuro-Hybrid Approach with Data Preprocessing,” International Journal of General Systems, Vol. 43, No. 5 (2014): 535-550.

11.  Vejendla, A., and D. Enke, “Performance Evaluation of Neural Networks and GARCH Models for Forecasting Volatility and Option Strike Prices in a Bull Call Spread Strategy,” Journal of Economic Policy and Research, Vol. 8, No. 2 (2013): 1-19.

12.  Enke, D., and N. Mehdiyev, “Stock Market Prediction using a Combination of Stepwise Regression Analysis, Differential Evolution-Based Fuzzy Clustering, and a Fuzzy Inference Neural Network,” Intelligent Automation and Soft Computing, Vol. 19, No. 4 (2013): 636-648.

13.  Vejendla, A., and D. Enke, “Evaluation of GARCH, RNN, and FNN Models for Forecasting Volatility in the Financial Markets,” IUP Journal of Financial Risk Management, Vol. X, No. 1 (2013): 41-49.

14.  Kilicay-Ergin, N., D. Enke, and C. Dagli, “Biased trader model and analysis of financial market dynamics,” International Journal of Knowledge-based and Intelligent Engineering Systems, Vol. 16 (2012): 99-116.

15.  Chavarnakul, T., and D. Enke, "A Hybrid Stock Trading System For Intelligent Technical Analysis-Based Equivolume Charting," Neurocomputing, Vol. 72, Issue 16-18 (2009): 3517-3528.

16.  Enke, D., and S. Amornwattana, "A Hybrid Derivative Trading System Based on Volatility and Return Forecasting," The Engineering Economist, Vol. 53, No. 3 (2008): 259-292.

17.  Ovlia, V., D. Enke, and M. Davis, "The Effects of Congressional Elections on Future Equity Market Returns," Global Journal of Business Research, Vol. 2, No. 1 (2008): 1-15.

18.  Chavarnakul, T., and D. Enke, "Intelligent Technical Analysis Based Equivolume Charting for Stock Trading using Neural Networks," Expert Systems with Applications, Vol. 34, No. 2 (2008): 1004-1017.

19.  Enke, D., C. Tirasirichai, and R. Luna, "Estimation of Earthquake Loss due to Highway Damage in the St. Louis Metropolitan Area: Part II - Indirect Loss.” ASCE Natural Hazards Review, Vol. 9, No. 1 (2008): 12-19.

20.  Tirasirichai, C. and Enke, D., “Case Study: Applying a Regional CGE Model for Estimation of the Indirect Economic Loss due to Damaged Highway Bridges,” The Engineering Economist, Vol. 52, 2007: 367-401.

21.  Morrison, G., J.C. Little, Y. Xu, M. Rao, and D. Enke, "Gas Exposure History Derived from Material-phase Concentration Profiles,” Atmospheric Environment, Vol. 41, No. 15 (2007): 3276-3286.

22.  Amornwattana, S., D. Enke, and C. Dagli, "A Hybrid Options Pricing Model Using a Neural Network for Estimating Volatility," International Journal of General Systems, Vol. 36, No. 5 (2007): 558-573.

23.  Enke, D., B. Chowdhury, G. Gelles, and E.K. Stanek, "Concepts on Market-Oriented Transmission Investment," Journal of Power and Energy Systems, Vol. 27, No. 4 (2007): 3653-3672.

24.  Lewis, N., D. Enke, and D. Spurlock, "The Staging Option and Drug Development," International Society of Pharmaceutical Engineering, Vol. 25, No. 6 (2005): 58-66, 76-78.

25.  Enke, D., and S. Thawornwong, "The Use of Data Mining and Neural Networks for Forecasting Stock Market Returns," Expert Systems with Applications, Vol. 29 (2005): 927-940.

26.  Lewis, N., D. Enke, and D. Spurlock, "Valuation for the Strategic Management of Research and Development Projects: The Deferral Option," Engineering Management Journal, Vol. 16, No. 4 (2004): 36-48.

27.  Liao, S., H. Wiebe, and D. Enke, "An Expert Advisory System for the ISO 9001 Quality System," Expert Systems with Applications, Vol. 27, No. 2 (2004): 313-322.

28.  Thawornwong, S., and D. Enke, “The Adaptive Selection of Financial and Economic Variables for Use With Artificial Neural Networks,” Neurocomputing, Vol. 56 (2003): 205-232.

29.  Thawornwong, S., D. Enke, and C. Dagli “Neural Networks as a Decision Maker for Stock Trading: A Technical Analysis Approach,” International Journal of Smart Engineering Systems Design, Vol. 5, No. 4 (2003): 313-325.

30.  Enke D., K. Ratanapan, and C. Dagli, “Large Machine-Part Family Formation Utilizing a Parallell ART1 Neural Network,” Journal of Intelligent Manufacturing, Vol. 11, No. 6 (2000): 591-604.

31.  Enke, D., K. Ratanapan, and C. Dagli, “Machine-Part Family Formation Utilizing an ART1 Neural Network Implemented on a Parallel Neuro-Computer,” International Journal of Computers Industrial Engineering, Vol. 34, No. 1 (1998): 189-205.

32.  Enke, D., and C. Dagli, “Automated Misplaced Component Inspection For Printed Circuit Boards”, Computers and Industrial Engineering, Vol. 33, No. 1-2 (1997): 373-376.

 


Edited Books:

  1. Intelligent Engineering Systems through Artificial Neural Networks, Vol. 18, Edited by C. Dagli, D. Enke, K.M. Bryden, H. Ceylan, and M. Gen, ASME Press, 2008.
  2. Intelligent Engineering Systems through Artificial Neural Networks, Vol. 17, Edited by C. Dagli, A. Buczak, M. Embrechts, D. Enke, and O. Ersoy, ASME Press, 2007.
  3. Intelligent Engineering Systems through Artificial Neural Networks, Vol. 16, Edited by C. Dagli, A. Buczak, M. Embrechts, D. Enke, and O. Ersoy, ASME Press, 2006.
  4. Intelligent Engineering Systems through Artificial Neural Networks, Vol. 15, Edited by C. Dagli, A. Buczak, M. Embrechts, D. Enke, and O. Ersoy, ASME Press, 2005.
  5. Intelligent Engineering Systems through Artificial Neural Networks, Vol. 14, Edited by C. Dagli, A. Buczak, M. Embrechts, D. Enke, and O. Ersoy, ASME Press, 2004.

       


Book Chapters:

  1. Enke, D., "Neural Network based Stock Market Return Forecasting using Data Mining for Variable Reduction", Chapter 3 in Artificial Neural Networks in Finance and Manufacturing, edited by Joarder Kamruzzaman, Rezaul Begg, and Ruhul A. Sarker (2005): 43-63.
  2. Thawornwong, S., and D. Enke, "Forecasting Stock Returns with Artificial Neural Networks", Chapter 3 in Neural Networks in Business Forecasting, edited by Peter Zhang (2003): 47-79.
  3. Enke, D., K. Ratanapan, and C. Dagli, "Machine-Part Family Formation Implemented on a Parallel Neuro-Computer Utilizing an ART1 Neural Network," Chapter 9 in Group Technology & Cellular Manufacturing: Methodologies and Applications. Edited by A. K. Kamrani and R. Logendran, Gordon & Breach Publishers, Inc. (1999): 251-283.

 


Conference Proceedings (Refereed by Paper):

1.      Mehdiyev, N., J. Lahann, A. Emrich, D. Enke, P. Fettke, and P. Loos, “Time Series Classification using Deep Learning for Process Planning: A Case from the Process Industry,” Procedia Computer Science, Vol. 114 (2017): 242-249.

2.      Kim, Y., and D. Enke, “Instance Selection Using Genetic Algorithms for an Intelligent Ensemble Trading System,” Procedia Computer Science, Vol. 114 (2017): 465-472.

3.      Mehdiyev, N., D. Enke, P. Fettke, and P. Loos, “Evaluating Forecasting Methods by Considering Different Accuracy Measures,” Procedia Computer Science, Vol. 95 (2016): 264-271.

4.      Kim, Y., and D. Enke, “Using Neural Networks to Forecast Volatility for an Asset Allocation Strategy based on the Target Volatility,” Procedia Computer Science, Vol. 95 (2016): 281-286.

5.      Wiles, P.S., and D. Enke, “Continuous Futures Contract Data for Computational Intelligence,” Proceedings of the 2016 American Society of Engineering Management conference, Concord, NC, October 2016.

6.      Mehdiyev, N., J. Krumeich, D. Enke, D. Werth, and P. Loos, “Determination of Rule Patterns in Complex Event Processing Using Machine Learning Techniques,” Procedia Computer Science, Vol. 61 (2015): 395-401.

7.      Wiles, P.S., and D. Enke, “Optimizing MACD Parameters via Genetic Algorithms for Soybean Futures,” Procedia Computer Science, Vol. 61 (2015): 85-91.

8.      Almasi Monfared, S., and D. Enke, “Noise Canceling in Volatility Forecasting Using an Adaptive Neural Network Filter,” Procedia Computer Science, Vol. 61 (2015): 80-84.

9.      Wiles, P.S., and D. Enke, “A Hybrid Neuro-Fuzzy Model to Forecast the Soybean Complex,” Proceedings of the 2015 American Society of Engineering Management conference, Indianapolis, IN, October 2015.

10.  Agarwal, S., L. Pape, C. Dagli, N. Ergin, D. Enke, A. Gosavi, R. Qin, D. Konur, R. Wang, and S. Gottapu, “Flexible and Intelligent Learning Architectures for SoS (FILA-SoS): Architectural Evolution in Systems-of-Systems”, 2015 Conference on Systems Engineering Research, Procedia Computer Science, Vol. 44 (2015): 76-85.

11.  Enke, D., and N. Mehdiyev, “A Hybrid Neuro-Fuzzy Model to Forecast Inflation,” 2014 Complex Adaptive Systems, Vol. 36 (2014): 254-260.

12.  Wiles, P.S., and D. Enke, “Nonlinear Modeling using Neural Networks for Trading the Soybean Complex,” Procedia Computer Science, Vol. 36 (2014): 234-239.

13.  Almasi Monfared, S., and D. Enke, “Volatility Forecasting using a Hybrid GJR-GARCH Neural Network Model,” Procedia Computer Science, Vol. 36 (2014): 246-253.

14.  Subhash, S., and D. Enke, “Hedge Fund Replication using Liquid ETFs and Regression Analysis”, Proceedings of the 2014 Industrial and Systems Engineering Research Conference, Y. Guan and H. Liao, editors, Montreal, Canada, 2014.

15.  Enke, D., and N. Mehdiyev, “Type-2 Fuzzy Clustering and a Type-2 Fuzzy Inference Neural Network for the Prediction of Short-Term Interest Rates,” 2013 Complex Adaptive Systems, Vol. 20 (2013): 115-120.

16.  Enke, D., and N. Mehdiyev, “Forecasting US Short-term Interest Rates using a Fuzzy Inference Neural Network,” ICAFS – 2012: Tenth International Conference on Applications of Fuzzy Systems and Soft Computing, CD-ROM Proceedings, 2012.

17.  Enke, D., and N. Mehdiyev, “A New Hybrid Approach For Forecasting Interest Rates,” 2012 Complex Adaptive Systems, Vol. 12 (2012): 259-264.

18.  Enke, D., M. Grauer, and N. Mehdiyev, “Stock Market Prediction with Multiple Regression, Fuzzy type-2 Clustering, and Neural Networks,” 2011 Complex Adaptive Systems, Vol. 6 (2011): 201-206.

19.  Wright T., and D. Enke, “Using Data Processing Algorithms and Neural Networks to Forecast One-Month Price Moves in the S&P 500 Index,” Intelligent Engineering Systems through Artificial Neural Networks, Vol. 18 (2008): 551-557.

20.  Simpson, J.J., C.H. Dagli, A. Miller, S.E. Grasman, and D.L. Enke, “Development of Abstract Relation Types for Systems and System-of-Systems Evaluation”, CD Proceedings of  CSER Conference on Systems Engineering Research, March 14-16, 2007 Hoboken, New Jersey.

21.  Meng, Y., and D. Enke, “Stock Trading Based on Neural Network Modeling and Fuzzy Technical Indicators,” Intelligent Engineering Systems through Artificial Neural Networks, Vol. 17 (2007): 255-260.

22.  Hartman, J., and D. Enke, "Financial Engineering: The Savior or End of Engineering Economy?," 2007 ASEE Annual Conference and Exposition, CD-ROM Proceedings, 2007.

23.  Kilicay, N., D. Enke, and C. Dagli, "Analysis of System Behavior through Cognitive Architectures," Proceedings of the International Conference on Artificial Intelligent (2007): 55-62.

24.  Hailin, L, C. Dagli, and D. Enke, "Short-term Stock Market Timing Prediction under Reinforcement Learning Schemes," IEEE International Symposium on Approximate Dynamic Programming and Reinforcement Learning, CD-ROM Proceedings (2007): 233-240.

25.  Singh, A., and D. Enke, “Fuzzy-Neural Decision Maker For Technical Analysis Indicators Using Genetic Optimization of Fuzzy Function,” Intelligent Engineering Systems through Artificial Neural Networks, Vol. 16 (2006): 97-102.

26.  Kilicay, N., D. Enke, S. Ramakrishnan, and C. Dagli, “Trader Behavior Under An Evolving Stock Market Environment,” Intelligent Engineering Systems through Artificial Neural Networks, Vol. 16 (2006): 773-778.

27.  Amornwattana, S., and D. Enke, “Modeling and Analysis of Derivative Trading Using Stock Return Forecasting,” Intelligent Engineering Systems through Artificial Neural Networks, Vol. 16 (2006): 779-784.

28.  Mobley, M., C. Dagli, D. Enke, “Heuristics and Genetic Algorithms,” 2006 INCOSE Conference Proceedings, Orlando, Florida, July (2006): 1793-1799.

29.  Tirasirichai, C., and D. Enke, "Indirect Earthquake Loss Estimation Methodology for the St. Louis Metropolitan Highway Network", 2006 American Society of Engineering Management Conference, CD-ROM Proceedings, 2006.

30.  Chavarnakul, T., and D. Enke, "A Neuro-fuzzy System of Volume Adjusted Moving Averages for Intelligent Trading Decisions", 2006 American Society of Engineering Management Conference, CD-ROM Proceedings, 2006.

31.  Gokhale, M., D. Myers, and D. Enke, "Decision Making and Valuation Tools for Understanding Uncertainty in New Product Development", 2006 American Society of Engineering Management Conference, CD-ROM Proceedings, 2006.

32.  Kilicay, N., D. Enke, S. Ramakrishnan, and C. Dagli, "Behavior of Technical Trading Agents in a Simulated Stock Market", 2006 IERC Conference, CD-Rom Proceedings, 2006.

33.  Chavarnakul, T., and D. Enke, S. Ramakrishnan, and C. Dagli, "Stock Trading using Neural Networks and the Ease of Movement Technical Indicator", 2006 IERC Conference, CD-Rom Proceedings, 2006.

34.  Kilicay, N., D. Enke, and C. Dagli, "Multi-Agent Architectures for Analysis of Complex Adaptive Systems", Seventh International Conference on Adaptive Computing in Design and Manufacture, The Institute for People-centered Computation, IP-CC (2006):185-190.

35.  Shil, P., D. Enke, and S. Ramakrishnan, "Forecasting Out-of-the-Money Call Option Strike Prices for Bull Option Spreading Strategies", 2005 American Society of Engineering Management Conference, CD-ROM.

36.  Amornwattana, S., and D. Enke, "Neural Network Based Return Forecasting with Volatility Estimation for Derivative Trading," Intelligent Engineering Systems through Artificial Neural Networks, Vol. 15 (2005): 681-690.

37.  Chavarnakul, T., and D. Enke, "Stock Trading using Neural Networks and Volume Adjusted Moving Averages," Intelligent Engineering Systems through Artificial Neural Networks, Vol. 15 (2005): 635-643.

38.  Li, H., C. Dagli, and D. Enke, "Optimal Asset Allocation using Reinforcement Learning: A Case Study," Intelligent Engineering Systems through Artificial Neural Networks, Vol. 15 (2005): 645-650.,

39.  Kilicay, N., C. Dagli, and D. Enke, "A Study of Artificial Financial Markets," Intelligent Engineering Systems through Artificial Neural Networks, Vol. 15 (2005): 625-634.

40.  Tirasirichai, T., and D. Enke, "Using Neural Networks to Identify the Type of Market Trend for Choosing the Proper Technical Analysis Indicator," Intelligent Engineering Systems through Artificial Neural Networks, Vol. 15 (2005): 651-659.

41.  Dong, Y., D. Enke, and C. Dagli, "A Modified Trading Strategy Model Combining Neural Networks with the Bollinger Band Technical Indicator," Intelligent Engineering Systems through Artificial Neural Networks, Vol. 15 (2005): 661-669.

42.  Shil, P., D. Enke, S. Ramakrishnan, "Forecasting the Sell Option Strike Price for a Bull Spread Stock Option Trading Strategy," Intelligent Engineering Systems through Artificial Neural Networks, Vol. 15 (2005): 671-680.

43.  Tirasirichai, C., S. Amornwattana, and D. Enke, " The Economic Aspects of Power System Design", 2005 IERC Conference Proceedings on CD-ROM, Alanta, GA, 2005.

44.  Thurau, R., D. Enke, and C. Dagli, " Development of an Integrated Facilities Management Baseline at a Federal Agency Using a Systems Engineering Approach", 2005 INCOSE International Symposium, CD-ROM Proceedings, 2005.

45.  Sampath Kumar, S.K., D. Myers, and D. Enke, "Valuation Approaches for Technology Transfer: A Review," 2004 American Society of Engineering Management (ASEM) Conference, Conference Proceedings (2004): 613-620.

46.  Mepokee, J., D. Enke, and B. Chowdhury, "Cost Allocation for Transmission Investment Using Agent-based Game Theory", 8th International Conference on Probability Methods Applied to Power Systems, 2004.

47.  Amornwattana, S., and D. Enke, "A Comparison of Methods for Derivative Trading using Stock Return Forecasting", Intelligent Engineering Systems through Artificial Neural Networks, Vol. 14 (2004): 741-746.

48.  Chavarnakul, T., D. Enke, and R. Chafin, "An Application of Neural Networks with the Bollinger Band Technical Indicator for Stock Trading", Intelligent Engineering Systems through Artificial Neural Networks, Vol. 14 (2004): 723-728.

49.  Mepokee, J., D. Enke, and B. Chowdhury, "Using Coalition Formation and Game Theory for Allocating Capital to New Transmission Investment", Intelligent Engineering Systems through Artificial Neural Networks, Vol. 14 (2004): 729-734.

50.  Mepokee, J., D. Enke, and C. Dagli, "Fuzzy Neural Network Models for Electrical Load Forecasting", Intelligent Engineering Systems through Artificial Neural Networks, Vol. 14 (2004): 955-960.

51.  Tirasirichai, C., D. Enke, and R. Chafin, "A Neural Network for Inflation Forecasting", Intelligent Engineering Systems through Artificial Neural Networks, Vol. 14 (2004): 717-722.

52.  Trinkle, D., and D. Enke, "Beating the House: A Study on Improving Bollinger Bands using Neural Networks", Intelligent Engineering Systems through Artificial Neural Networks, Vol. 14 (2004): 699-704.

53.  Ovlia, V., and D. Enke, "Financial Forecasting using a Neural Network Trained with the MACD Technical Indicator", Intelligent Engineering Systems through Artificial Neural Networks, Vol. 14 (2004): 693-698.

54.  Li, H., C. Dagli, and D. Enke, "Forecasting Series-based Stock Price Data using Direct Reinforcement Learning", Proceedings of the IEEE International Joint Conference on Neural Networks,, Budapest, Hungary, Vol. 2 (2004): 1103-1108.

55.  Murray, S., D. Enke, and S. Ramakrishnan, "Successfully Blending Distance Students into the On-Campus Classroom", 2004 ASEE Annual Conference & Exposition, Salt Lake City, June 20-23, CD-ROM Proceedings.

56.  Amornwattana, S., D. Enke, and C. Dagli, "A Hybrid Option Pricing Model Using a Neural Network for Forecasting Volatility", Intelligent Engineering Systems through Artificial Neural Networks, Vol. 13 (2003): 725-730.

57.  Varma, P., and D. Enke, "Modeling Foveal Human Image Processing for Enhanced Contrast and Edge Detection of Images used in Artificial Vision Systems", Intelligent Engineering Systems through Artificial Neural Networks, Vol. 13 (2003): 579-584.

58.  Enke, D., "Real Options for Deregulated Electricity Markets", 2003 American Society of Engineering Management (ASEM) Conference, Conference Proceedings (2003): 505-514.

59.  Enke, D., “Experiences Teaching Engineering Economy through Distance Education,” Midwest American Society of Engineering Education (ASEE) Conference, September 2003, Rolla, MO.

60.  Thawornwong, S., and D. Enke, "A Computational Approach for Selecting the Performing Stocks of the Dow", Intelligent Engineering Systems through Artificial Neural Networks, Vol. 12 (2002): 695-700.

61.  Bogullu, V.K., D. Enke, and C. Dagli, "Using Neural Networks and Technical Indicators for Generating Stock Trading Signals", Intelligent Engineering Systems through Artificial Neural Networks, Vol. 12 (2002): 721-726.

62.  Thawornwong, S., D. Enke, and C. Dagli, "Genetic Algorithms and Neural Networks for Stock Trading Prediction and Technical Signal Optimization", 33rd Annual Meeting of the Decision Sciences Institute in San Diego (2002): 776-781.

63.  Thawornwong, S., D. Enke, and C.H. Dagli, "Using Neural Networks and Technical Analysis Indicators for Predicting Stock Trends", Intelligent Engineering Systems through Artificial Neural Networks, Vol. 11 (2001): 739-744.

64.  Bogullu, V.K., D. Enke, and C. Dagli, "Intelligent Technical Stock Analysis Using Fuzzy Logic and Trading Heuristics", Intelligent Engineering Systems through Artificial Neural Networks, Vol. 11 (2001): 313-318.

65.  Vaithianathasamy, S., and D. Enke, "Comparison of Hourly and Daily Neural Network Models For Forecasting Hourly Electric Load", Intelligent Engineering Systems through Artificial Neural Networks, Vol. 11 (2001): 715-720.

66.  Hemsathapat, K., C. Dagli, D. Enke, "Neuro-Fuzzy-Genetic Architecture for Data Mining", Intelligent Engineering Systems through Artificial Neural Networks, Vol. 11 (2001): 375-380.

67.  Hemsathapat, K., C. Dagli, D. Enke, "Using a Neuro-Fuzzy-Genetic Data Mining Architecture to Determine a Marketing Strategy in a Charitable Organization's Donor Database", 2001 IEEE International Engineering Management Conference, Albany, NY, October 2001.

68.  Thawornwong, S., D. Enke, "The Use of Data Mining, Neural Network Models, and Validation Techniques for Predicting Excess Stock Returns" Second International ICSC Symposium on Advanced Computing in Financial Markets in Bangor, Wales, U.K., May, 2001

69.  Disorntetiwat, P., C.H. Dagli, D. Enke, "Multiple Generalized Regression Neural Networks with a Gating Network for Global Stock Index Forecasting " Second International ICSC Symposium on Advanced Computing in Financial Markets in Bangor, Wales, U.K., May, 2001

70.  Enke, D. and S. Vaitianathasamy, "Electric Load Forecasting Using Trend Data and a Feed Forward Neural Network," Intelligent Engineering Systems through Artificial Neural Networks, Vol. 10 (2000): 1019-1024.

71.  Enke, D., S. Vaitianathasamy, and P. Diwe, "Factorial Design for Developing Feed Forward Neural Network Architectures," Intelligent Engineering Systems through Artificial Neural Networks, Vol. 10 (2000): 109-114.

72.  Enke, D., and C. Dagli, "Modeling the Lateral Cortical Connections and Area V1 to LGN Feedback for Producing Segment Completion, Noise Reduction, and Attentional Effects," SPIE Conference, Human Vision and Electronic Imaging II (1997): 203-214.

73.  Enke, D., "A Connectionist Architecture of the Pulvinar Nucleus for Focusing Visual Attention on Salient Features," Intelligent Engineering Systems Through Artificial Neural Networks, Vol. 7 (1997): 29-35.

74.  Enke, D.L., and C.H. Dagli, "Modeling the Amacrine Cells in the Primate Retina for Edge Detection and Contrast Enhancement of Images Provided to Artificial Vision Systems," Intelligent Engineering Systems Through Artificial Neural Networks, Vol. 6 (1996): 77-82.

75.  Enke, D.L., H.C. Lee, A.M. Ozbayoglu, and A. Thammano, "An Application to Speaker Identification Using SimNet," Intelligent Engineering Systems through Artificial Neural Networks, Vol. 5 (1995): 69-76.

 


Conference Proceedings (Refereed by Abstract):

  1. Kilicay, N., C. Dagli, D. Enke, and E. Meteoglu, “Methodologies for Understanding Behavior of System of Systems,” CD Proceedings of Conference on System Engineering Research, 2007, pp. 14-16.
  2. Mepokee, J., D. Enke, and B. Chowdhury, "Cost Allocation using Intelligent Agents for New Transmission Investment under Electricity Restructuring", 2003 North American Power Conference conference, CD-ROM proceedings, Rolla, October 2003.
  3. Enke, D., "Experiences Teaching Engineering Economy through Distance Education", presented at the 2003 Midwest American Society of Engineering Education (ASEE) conference, Rolla, September 2003, CD-ROM.
  4. Mepokee, J., D. Enke, and S. Thawornwong, "Applying Portfolio Management during Electricity Deregulation", ICPR Americas Conference, November 2002, CD-ROM.
  5. Amornwattana, S., and D. Enke, "Using Real Options for Determining Scheduling Priority under Uncertainty", ICPR Americas Conference, November 2002, CD-ROM.
  6. Somanchi, S., C. Dagli, and D. Enke, "Machine Part Family Formation Utilizing the Hausdorff-Voronoi Neural Network (HAVNET)", ICPR Americas Conference, November 2002, CD-ROM.
  7. Thawornwong, S., D. Enke, C.H. Dagli, "Neural Network Models for Classifying the Direction of Excess Stock Return", 32nd Annual Meeting of the Decision Sciences Institute in San Francisco, November, 2001.
  8. Enke, D., "A Biologically Inspired Connectionist Architecture for Directing Attention to Salient Visual Field Objects," IEEE International Conference on Systems, Man, and Cybernetics, Vol. 2 (1997): 999-1004.
  9. Enke, D., and C. Dagli, "Image Noise Reduction and Segment Completion by Modeling the Neural Interactions within and Between Area V1 and the LGN," presented at the 2nd International Conference on Computational Intelligence and Neuroscience, North Carolina, March 1997.
  10. Enke, D.L., and C.H. Dagli, "Modeling Biological Visual Processes for Improved Contrast Enhancement and Edge Detection of Artificial Vision Systems," Applications and Science of Artificial Neural Networks II, SPIE Conference, Vol. 2760 (1996): 346-357.
  11. Enke, D.L., and C.H. Dagli, "Using a viewing window and the HAVNET neural network for the recognition of words within a document," Applications and Science of Artificial Neural Networks, SPIE Conference, Vol. 2 (1995): 841-848.
  12. Ozbayoglu, M.A., H.C Lee, D.L. Enke, C.H. Dagli, and F. Ercal, "SimNet: An Unsupervised Neural Network Model for Clustering," XVII National Conference on Operational Research and Industrial Engineering, Ankara, Turkey, 1995.

 


Presentations (no proceeding):

  1. “Financial Engineering Research Opportunities after the Great Recession of 2008-2009,” 2013 American Society of Engineering Management conference, Minneapolis, MN, October 2013.
  2. “Utilizing Distance Education Technology to Expand Engineering Management and Systems Engineering Education,” 2013 Innovations in Mining Engineering conference, St. Louis, MO, September 2013.
  3. “Computational Intelligence in Financial Engineering: Are there still opportunities            given the current economic climate and changes in the markets and regulatory environment?” Plenary talk given at the Artificial Neural Networks in Engineering conference, November 2010.
  4. “Forecasting Short-Term Stock Price Movement using a Supervised Learning Assisted Reinforcement Learning Architecture,” Southwest Finance Symposium, March 30, 2007, University of Tulsa, Tulsa, OK.
  5. "Cost Allocation for Transmission Investment Using Agent-based Game Theory", 8th International Conference on Probability Methods Applied to Power Systems, 2004, with J. Mepokee and B. Chowdhury.
  6. “A Biologically Inspired Connectionist Architecture of the Retina and Thalamocortical System,” Toward a Science of Consciousness 1998 – Tucson III, April, 1998, The University of Arizona, Tucson, AZ.
  7. “Modeling the Bidirectional Interactions Within and Between the LGN and Area VI Cells,” International Conference on Vision, Recognition, and Action, May, 1997, Boston, MA, with C. Dagli.

 


 

 

Description: Description: Description: Description: Description: F:\Homepage S&T\buttons\home.gif

Last Updated 8/12/19