Journal Articles:
1.
Han, Y., Kim, J., and D. Enke, "A Machine Learning Trading System for the
Stock Market Based on N-period Min-Max Labeling Using XGBoost," accepted
and in-press with the journal Expert
Systems With Applications, 2022.
2.
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.
3.
Subhash, S., and D. Enke, “Hedge Fund
Replication Using Strategy Specific Factors,” Financial Innovation, Vol. 5(1), 11 (2019): 1-19.
4.
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.
5.
Zhong, X., and D. Enke, “A Comprehensive
Cluster and Classification Mining Procedure for Daily Stock Market Return
Forecasting,” Neurocomputing,
Vol. 267 (2017): 152-168.
6.
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.
7.
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.
8.
Zhong, X., and D. Enke, “Forecasting Daily
Stock Market Return Using Dimensionality Reduction,” Expert Systems with Applications, Vol. 67 (2017): 126-139.
9.
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.
10.
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.
11.
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.
12.
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.
13.
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.
14.
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.
15.
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.
16.
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.
17.
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.
18.
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.
19.
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.
20.
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.
21.
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.
22.
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.
23.
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.
24.
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.
25.
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.
26.
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.
27.
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.
28.
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.
29.
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.
30.
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.
31.
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.
32.
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.
33.
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:
- 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.
- 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.
- 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.
- 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.
- 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:
- 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.
- 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.
- 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):
- 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.
- 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.
- 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.
- Mepokee, J., D.
Enke, and S. Thawornwong, "Applying Portfolio Management during
Electricity Deregulation", ICPR Americas Conference,
November 2002, CD-ROM.
- Amornwattana, S.,
and D. Enke, "Using Real Options for Determining Scheduling
Priority under Uncertainty", ICPR Americas Conference,
November 2002, CD-ROM.
- 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.
- 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.
- 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.
- 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.
- 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.
- 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.
- 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):
- “Financial
Engineering Research Opportunities after the Great Recession of
2008-2009,” 2013 American
Society of Engineering Management conference, Minneapolis, MN,
October 2013.
- “Utilizing Distance
Education Technology to Expand Engineering Management and Systems
Engineering Education,” 2013
Innovations in Mining Engineering conference, St. Louis, MO,
September 2013.
- “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.
- “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.
- "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.
- “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.
- “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.
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