**1**-
Amari, S., et al.:``
Asymptotic Statistical Theory of Overtraining and Cross-Validation'',
RIKEN, Japan,
**METR 95-06**(1995). **2**- Anderson, J.A.: `` An Introduction to Neural Networks'', Bradford, MIT press, (1995).
**3**-
Andrews, R., Diederich, J., Tickle, A. : ``
A survey and critique for extracting rules from trained ANN'',
on
*www.qut.edu.au*(1995). **4**-
Ankenbrand, T. and Tomassini, M.:``
Multivariate time series modeling of financial markets with artificial
neural networks'', ANN and GA, Springer Verlag, Wien,
*pp. 257-260*(1995). **5**-
Anthony, M.:``
Probabilistic Analysis of Learning in Artificial Neural Networks:
The PAC Model and its Variants'', Neural Computing Surveys, vol. 1,
*pp. 1-47*(1997). **6**- Arbib, M.A.: `` The Handbook of Brain Theory and Neural Networks'', Bradford, MIT Press, (1995).
**7**- Bengio, S., Fessant, F. and Collobert, D.: `` A Connectionist System for Medium-Term Horizon Time Series Prediction'', International Workshop on Applications of Neural Networks to Telecommunications, Stockholm, Sweden (1995).
**8**-
Bishop, C.: ``
Improving the generalization proprieties of radial basis function neural networks'',
Neural Computation, 3,
*pp. 579-588*(1991). **9**- Box, G.E.P. and Jenkins, G.M.: `` Time Series Analysis: Forecasting and Control'', Holden-Day, San Francisco, CA, (1970).
**10**-
Broomhead, D.S. and Lowe, D.:``
Multivariable functional interpolation and adaptive networks'',
Complex Systems 2,
*pp. 321-355*(1988). **11**-
Brownhill, C., Nicolau, A., Novack, S. and Polychronopoulos, C.:``
The Promis Compiler'',
**PACT97**. **12**- Cherkassky, V. et al.: `` Learning from Data: Concepts, Theory and Methods (Adaptive and Learning Systems for Signal Processing, Communications and Control Series)'', John Wiley & Sons (1998).
**13**- Cristea, A.: `` Applications of Neural Networks'', Stage Report, Technical University of Denmark, Lyngby, Institute of Information Technology (1994).
**14**- Cristea, A.: `` Aplicatii ale Retelelor Neuronale'' (Romanian language), Master thesis (Master of Engineering in Computer Science title) "Politehnica" University of Bucharest, Romania, Faculty of Computer Science (1994).
**15**- Cristea, A.: `` Boersenkurssimulieren mit Hilfe von Neuronalen Netzen'' (German language), Master thesis (Wirtischaftsingineur title (MBA)), "Politehnica" University of Bucharest, Romania, Department of Engineering Sciences, Economical Engineering (1997).
**16**-
Cristea, A., Cristea, P. and Okamoto, T. : ``
Neural Network Knowledge Extraction'',
Revue Roumaine des Sciences Technique, Serie EE (Electrotechn. et Energ.),
vol. 42, no. 4, (Oct.-Dec.),
*pp. 477-491*(1997). **17**- Cristea, A., and Okamoto, T. : `` Energy Function based on Restrictions for Supervised Learning on Feedforward Networks'', Journal IPSJ (Journal of the Information processing society of Japan), SIGMPS Transactions, vol.1, no.1 (accepted April 1998).
**18**- Cristea, A., and Okamoto, T. : `` Neural Networks for Stock Exchange prediction with a Lyapunov-based training'', Journal JIS (Journal of Intelligent Systems), Special issue on Prediction & reasoning in neural networks, Australia (accepted August 1998, to appear beginning of 1999).
**19**- Cristea, A., and Okamoto, T. : `` Parallelization methods for Neural Networks on different environments: Advantages and Disadvantages'', Journal of Information Science (IS), New Zealand, Elsevier, IS/2 Special Issue, (sent April 1998, accepted September 1998).
**20**-
Cristea, A., and Okamoto, T. : ``
A Parallelization Method for Neural Networks with Weak Connection Design'',
**ISHPC'97**, Lecture Notes in Computer Science 1336, Eds. C. Polychronopoulos et Co., Springer, vol.1336,*pp. 397-404*(1997). **21**-
Cristea, A., and Okamoto, T. : ``
Parallel Implementation Tool of NN on UNIX machines'',
**ICONIP97/ANNES97/ANZIIS97**, New Zealand, (the paper received the "Best Student Paper Award"), Progress in Connection-Based Information Systems, Eds. R. Kozma, A. Gray, R. Kilgour, B. Woodford, Univ. Otago,*pp. 21-24*(1997). **22**-
Cristea, A., and Okamoto, T. : ``
NN for Stock Exchange prediction; a Lyapunov based training'',
**ICCIMA98**, Eds. Henri Selvaraj and Brijesh Verma, World Scientific,*pp. 416-421*(1998). **23**-
Cristea, A., and Okamoto, T. : ``
Sub-Symbolic Knowledge Extraction Environment for Teaching Process Assistance'',
**KES98**, vol. 3, IEEE,*pp. 411 - 417*(1998). **24**-
Cristea, A., and Okamoto, T. : ``
Energy function construction and Implementation for Stock Exchange prediction
NNs'',
**KES98**, vol. 3, IEEE,*pp. 403-410*(1998). **25**-
Cristea, A., and Okamoto, T. : ``
Deduction of an L-based energy function for SE Prediction'',
**ICCNS'98**, Second International Conference on Cognitive and Neural Systems, Boston, USA,*pp. 119*(1998). **26**-
Cristea, A., and Okamoto, T. : ``
A L-based Energy Function for SE Prediction'',
**WIRN'98**, Vietri Sul Mare, Salerno, Italy, Perspectives in Neural Computing, Springer Verlag, Ed. John G. Taylor, ISBN 1-85233-051-1,*pp. 304-309*(to appear October 1998). **27**-
Cristea, A., and Okamoto, T. : ``
The development of a neural network knowledge extraction environment for
teaching process assistance'',
**ED-MEDIA/ED-TELECOM'98**, 10th World Conference on Educational Multimedia and Hypermedia and 10th World Conference on Educational Telecommunications, Freiburg, Germany, 20-25 June 1998, Eds. Thomas Ottmann and Ivan Tomek, organiz. AACE, vol 1,*pp. 227-232*(1998). **28**-
Cristea, A., and Okamoto, T. : ``
SEE Prediction - Construction of a L-based energy function'',
**NC'98**, International ICSC/IFAC Symposium on Neural Computation, Sept. 23-25, Vienna Univ. of Technology, Ed. M. Heiss, ICSC Academic Press, Canada/Switzerland, ISBN 3-906454-15-0,*pp. 841-847*(1998). **29**-
Cristea, A., and Okamoto, T. : ``
An Energy Function for Stock Exchange Prediction'',
**IIZUKA'98**, Methodologies for the Conception, Design and Application of Soft Computing, Iizuka, Japan, Eds. T. Yamakawa, G. Matsumoto, ISBN 981-02-3966-1,*pp. 622-625*(1998). **30**-
Cristea, A., and Okamoto, T. : ``
The Development of a Feedforward NN for Financial Time Series Forecast'',
**ICONIP'98, JNNS'98**, Kitakyuushu, Japan, Eds. S. Usui, T. Omori, ISBN 4-274-90256-0,*pp. 1024-1027*(1998). **31**-
Cristea, A., and Okamoto, T. : ``
Stock exchange Analysis as Time-Series; Forecasting with Neural Nets'',
Technical Report IEICE,
**AI-96**, Japan, vol. 96, no. 594,*pp. 9 - 16*, (1997). **32**-
Cybenko, G.: ``
Approximation by superpositions of a sigmoid function'',
Mathematics of Control, Signals and Systems, 2,
*pp. 303-314*(1989) **33**-
Dasgupta, D., and McGregor, D.R.:``
Designing Application-Specific Neural Networks using the Structured Genetic
Algorithm''.
**COGANN-92**, Eds. Whitley & Schaffer, IEEE Computer Society Press,*pp 87-96*(1992). **34**-
Dezfulian, M.H., Gray, N.A.B.: "Intelligent Interpretation of Line Diagrams",
**AI'94**, University of Wollongong, Department of Computer Science, Wollongong, NSW 2521, Australia, Eds. Chengqi Zhang, John Debenham, Dickson Lukose,*pp. 615-616*, (1994). **35**- Eberhart, R.C. and Dobbins, R.W., Neural Network PC Tools - A Practical Guide, San Diego: Academic Press (1990).
**36**- Fausett, L.: `` Fundamentals of Neural Networks. Architectures, Algorithms, and Applications'', Prentice Hall International, Inc., (1994).
**37**-
Fu, L.M. : ``
Knowledge-based connectionism for revising domain theories'',
IEEE Trans. on Systems, Man and Cybernetics, vol. 23, no.1,
*pp. 173 - 182*(1993). **38**-
Fu, L.M. : ``
Rule generation from NN '',
IEEE Transactions on Systems, Man and Cybernetics, vol. 28, no.8,
*pp. 1114 - 1124*(1994). **39**-
Gas, B. and Natowicz, R. : ``Unsupervised learning of temporal sequences
by neural networks'',
**ANN and GA**, Springer,*pp. 253-256*(1993). **40**- Gately, E.: `` Neural Networks for Financial Forecasting, Top Techniques for Designing and Applying the Latest Trading Systems'', Ed. Perry J. Kaufman, Wiley (1996).
**41**-
Geczy, P. and Usui, S. : ``
Rule Extraction from Trained Artificial Neural Networks'',
**ICONIP**, vol. 2,*pp. 835 - 838*(1997). **42**- Geist, A., Beguelin, A., Dongarra, J., Jiang, W., Manchek, R. and Sunderam, V.:`` PVM: Parallel Virtual Machine. A User's Guide and Tutorial for Networked Parallel Computing'', MIT Press, Scientific and Engineering Computation (1994).
**43**-
Giles, L., Lawrence, S. and Tsoi, A.C.:``
Rule Inference for Financial Prediction using Recurrent Neural Networks'',
**IEEE/IAFE**Conference on Computational Intelligence for Financial Engineering, Proceedings, IEEE Press,*pp. 253-259*(1997) **44**- Grossberg, S:``
Neural expectation: Cerebellar and retinal analos of cells fired by learnable
or unlearned pattern classes'', Kybernetik 10,
*pp. 49-57*(1972). **45**- Grossberg, S.:``
How does a brain build cognitive code?'', Psychological Review 87,
*pp. 1-51*(1980). **46**- Hanke, J.E. and Reitsch, A.G., Business Forecasting, 2nd Edition, Allyn and Bacon (1984).
**47**- Hassoun, M.H.: :``Fundamentals of Artificial Neural Networks'', MIT Press, Cambridge, Massachusetts, London, England (1995).
**48**-
Hayashi, Y. : ``
A neural expert system with automated extraction of fuzzy if-then rules '',
Advances in Neural Info Processing Systems, vol. 3, M. Kaufmann,
*pp. 578 - 584*(1990). **49**- Haykin, S.: "Neural Networks - A Comprehensive Foundation", Macmillan College Publishing Company, NY, USA, Ed. John Griffin (1994).
**50**- Healy, M. : ``Acquiring Rule Sets as a Product of Learning in a logical neural architecture'', IEEE Transactions on NN, vol.8, no.3 (1997).
**51**- Hebb, D.O.:`` The Organization of Behaviour'', Wiley, New York (1949).
**52**- Hopfield, J.J.:``
Neural Networks and physical systems with emergent collective computational
abilities'',
**National Academy of Science**, Proceedings, USA, vol. 79,*pp. 2554-2558*, April (1982). **53**-
Izzo, G., Pepicelli, G. and Tocchetti, G.:``
A backpropagation neural network for the study of prediction in management systems'',
**N.N.WIRN VIETRI-92**, Sixth Italian Workshop, Ed. E.R. Caianiello, Word Scientific,*pp. 386-393*(1992). **54**- Jabri, M., Tinker, E. and Leerink, L.:`` MUME - a multi-modules multi-algorithms NN. '', http: //www.sedal.usyd.edu.au/mume/mume.html
**55**- Jagielska, I.: ``The application of neural networks to business
information systems'', Proceedings of 4th Australian Conference on
Information Systems, Brisbane,
*pp. 565-574*(1993). **56**- Jarrett, J., Business Forecasting Methods, Basil Blackwell (1991).
**57**- Kanoh, S., et al. : ``Rule Extraction in Temporal Sequence
Generation from Spatially-Encoded Information by Recurrent Neural Networks'',
Progress in Connectionist-Based Information System,
**ICONIP**, vol. 2, Eds. Nikola Kasabov et al., Springer,*pp. 873-876*(1997). **58**- Kikuchi, J., Tomita, E. and Wakatsuki, M.: ``
Randomized and hybrid algorithms for approximate graph coloring'',
Technical Report of IEICE, COMP97-109,
*pp. 25-32*(1998-03). **59**- Kirkpatrick, S., Gelatt, C.D. and Vecchi, M.P.:``
Optimization by simulated annealing'', Science 220,
*pp. 671-680*(1983). **60**- Kohonen, T.:``
Correlation matrix memories'', IEEE Transactions on Computers, C-21,
*pp. 353-359*(1972). **61**- Kohonen, T.:``
Self organized formation of topologically correct feature maps'',
Biological Cybernetics 43,
*pp. 59-69*(1972). **62**-
Komo, D., Chang, C.I., and Ko, H. : ``Neural Network Technology for Stock Market
Index Prediction'',
**ISSIPNN94**, IEEE,*pp. 543-546*(1994). **63**- Krogh, A., and Hertz, J.A.:`` A Simple Weight Decay Can Improve Generalization'', Advances in Neural Information Processing Systems, vol. 4, 950-957, Moody, J., Hanson, S., Lippman, R., Eds., Morgan Kaufmann Publishers (1992).
**64**-
Lam, M.:``
Software Pipelining: An Effective Scheduling Technique for VLIW Machines'',
**ACM SIGPLAN**,*pp. 318-328*(1988). **65**-
Lenoski, D. E.:``
The Design and Analysis of Dash: A Scalable Directory-based Multiprocessor'',
*PhD Thesis*, Stanford University, CSL (1992). **66**- Levin, A.U., Leen, T.K., and Moody, J.E.:`` Fast Pruning Using Principal Components'', Advances in Neural Information Processing 6, J.Cowan, G.Tesauro, J.Alspector, Eds. Morgan Kaufmann, San Mateo, CA (1994).
**67**- Lin, F., et al.: `` Time Series Forecasting with Neural Networks'', Complexity International, vol.2, ISSN 1320-0682, Johnstone Center (1995).
**68**- Ling, C.S.: ``Choosing the right neural network model for trading'', Proceedings of First Symposium on Intelligent Systems Applications, Singapore, pp. 26-33 (1993).
**69**-
Lukowicz, P., et al.:
*Experimental Evaluation in Computer Science: A Quantitative Study*, Journal of Systems and Software, (1995). **70**- Prechelt, L.:`` Some Notes on Neural Learning Algorithm Benchmarking '', Neurocomputing (1995).
**71**- Mache, N. et al.:`` Introduction to SNNS'', University Stuttgart, http: //www.inf.tu-dresden.de/ kn3/SNNSinfo/UserManual/UserManual.html
**72**- Makridakis et al.: `` Forecasting: Methods and Applications'', New York: Wiley (1983).
**73**- Masters, T.:`` Neural, Novel & Hybrid Algorithms for Time Series Prediction'', Wiley (1995).
**74**- McCulloch, W.S., and Pitts, W.:``
A logical calculus of the ideas immanent in nervous activity'', Bulletin of Mathematical
Biophysics, 5,
*pp. 115-133*(1943). **75**- Meunier, C., and Nadal, J.P.:``
Sparsely Coded Neural Networks'',
The Handbook of Brain Theory and NN, Ed. M.A.Arbib, MIT press,
*pp. 899-901*(1995). **76**- Minsky, M. and Papert, S.:`` Perceptrons'', MIT Press, Cambridge, MA (1969).
**77**- Miyano, T., Girosi, F.:`` Forecasting Global Temperature Variations by Neural Networks'', MIT AI Laboratory and Center for Biology and Computer Learning Department of Brain and Cognitive Science, ftp: publications.ai.mit.edu (1994).
**78**- Misra, M.:``
Parallel environments for Implementing NNs'',
Neural Computing Surveys, vol.1,
*pp. 48-60*(1997). **79**-
Mori, S. et al.:``
A Distributed Shared Memory Multiprocessor: ASURA - Memory and Cache Architectures'',
**Supercomputing'93**,*pp. 740-749*(1993). **80**- Muller, U.A. et al.:`` High Performance Neural Net Simulation on a Multiprocessor System with "Intelligent" Communication'', Advances in Neural Information Processing Systems 6 (NIPS), Morgan Kaufmann publishers (1994).
**81**- Murata, N., Yoshizawa, S. and Amari, S.:`` Network Information Criterion - Determining the Number of Hidden Units for an Artificial NN Model'', Department of Mathematical Engineering and Information Physics, Faculty of Engineering, University of Tokyo,ftp-source (1995).
**82**- Myklebust, G.:`` Implementation of an unsupervised neural network model on an experimental multiprocessor system'', PhD thesis, Computer System Group, Department of Computer Science, University of Trodheim, Norway (1996).
**83**-
Myklebust, G., Solheim, J.:``
Parallel SOM for actual applications'',
**ICNN'95**, vol.2,*pp. 1024*(1996). **84**- Nelson, M.E., Furmanski, W. and Bower, J.M.:`` Simulating Neurons and Networks on Parallel Computers'', Methods in Neuronal Modeling, From Synapses to Networks, Eds. C.Koch and I.Segev, MIT, section 12 (1989).
**85**- The Neurobasic homepage, at: http://www.ife.ee.ethz.ch/ nbasic/.
**86**- Nordstroem, T., Svensson, B.:``
Using and Designing Massively parallel computers for ANNs'',
Journal of Parallel and Distributed Computing, vol.14,
*pp. 260-285*(1992). **87**- NYSE Net: About the NYSE, Chapter: About the Exchange, http://www.nyse.com/public/about/market/flowchrt.htlm
**88**- Okamoto, T.: `` The Framework and its Meanings of New Curriculum for Information Technology-Education from Primary to Senior High School in Japan'', Educational Technology Research (to appear 1998).
**89**-
Okamoto, T.: "The Current Situations and Future Directions of Intelligent CAI
Research/Development", Trans. IEICE, Vol. E77-D, No.1,
*pp. 9-18*(1994). **90**- Okamoto, T.: "Feasibility Study for a practice of ITE in Senior High School and it's evaluation", (research subject number: 07308017), year (Jap.) 7, report of scientific study founded by the Ministry of Education, (university research (A)) (1996).
**91**-
Okamoto, T.: "The Intelligent Multimedia CAI System in Distributed Learning
Environment", The Journal of the Institute of Television Engineering in Japan,
vol. 47, No.11,
*pp. 1492-1497*(1993). **92**-
Okamoto, T.: "Overview on the Studies of Intelligent CAIs/ITSs in Japan",
Education Technology Research, vol. 15,
*pp. 1-8*(1992). **93**-
Okamoto,T., Ueda,Y., Kunishige, M.: ``The Distributed Multimedia Learning Environment
Employing Gaming/Simulation Method with Expert System in the world of Macro Economics'',
Computer and Artificial Intelligence, Vol. 14, No.4,
*pp. 395-415*(1995). **94**-
Ossen, A. and Schnauss, M.:`` Practical Tools for Derivative Instruments based
on Nonlinear Series Prediction'', International Workshop on Parallel Applications in
Statistics and Economy Proceedings, Neural Network World, vol. 5,
*pp. 525-536*(1995). **95**-
Pau, L.F., and Goetzsche,T.: "Explanation Facility for Neural Networks",
Technical University of Denmark, Lyngby, Intelligent Systems, Ed. L.S. Sterling,
Plenum Press, NY,
*pp. 111-125*(1993). **96**- Petridis,V., and Kehagias, A.: `` Modular NN for MAP Classification of Time Series and the Partition Algorithm'', IEEE Transactions on Neural Networks, Vol. 7, No. 1 (January 1996).
**97**- Rao, V.B. and Rao, H.V., C++ Neural Networks and Fuzzy Logic, MIS Press (1993).
**98**-
Ripley, B.D.:``
Statistical Ideas for Selecting Network Architectures'',
**NIPS'95**Proceedings (1995). **99**- Roebel, A.:`` The Dynamic Pattern Selection Algorithm: Effective Training and Controlled Generalization of Backpropagation Neural Networks'', TU Berlin,March 4, Institut fuer Angewandte Informatik, FG Informatik in Natur- und Ingenieurwissenschaften (1994).
**100**- Rogers, R.O. and Skillicorn, D.B.:`` Strategies for Parallelizing Supervised and Unsupervised Learning in ANN using the BSP Cost Model'', Ext. Technical Report, ISSN-0836-0227-97-406 (1997).
**101**- Rosenblatt, F.:``
The perceptron: a probabilistic model for information storage and organization in the
brain'', Psychological Review, 65,
*pp. 386-408*(1958). **102**- Roychowdhury, V., Siu K.Y., and Orlitsky, A.: `` Theoretical Advances in Neural Computation and Learning'', Kluwer Academic Publishers, (1994).
**103**-
Rueger, S.M. and Ossen, A.:``
Performance Evaluation of Feedforward Networks Using Computational Methods'',
**NEURAP'95**(1995). **104**- Rumelhart, D.E., Hinton, G.E. and Williams, R.J.:``
Learning representations by back-propagating errors'', Nature, London, 323,
*pp. 533-536*(1986). **105**-
Saito, K., Nakano, R. : ``Numeric Law Discovery using Neural Networks'',
Progress in Connectionist-Based Information System,
**ICONIP**, vol. 2, Eds. Nikola Kasabov et al., Springer,*pp. 843-846*(1997). **106**- Schwert, G.W.: ``Why does Stock Volatility Change over Time'', award-winning paper, Journal of Finance (1989).
**107**- Schwert, G.W.: ``Stock Market volatility'', award-winning paper, Financial Analyst Journal (1990).
**108**- Schwert, G.W.: ``Markup Pricing in Mergers & Acquisitions'', Journal of Financial Economics (1996).
**109**- Shawn, P.D., Davenport, M.R. : ``Continuous-Time Temporal Back-Prop. with Adaptable Time Delays'', IEEE Trans. on NN, Canada (1992).
**110**- Smagt, P.: ``An introduction to Neural Networks'', from: http://www.robotic.dlr.de/Smagt/books/ (updated yearly).
**111**- Svensson, B., and Nordstroem, T.:``
Execution of NN algorithms on a array of bit-serial processors'',
10th International Conference on Pattern Recognition, Computer Architecture for Vision and Pattern Recognition, NJ, USA, vol.2,
*pp. 501-505*(1990). **112**- Swingler, K.:`` Financial Prediction, Some Pointers, Pitfalls, and Common Errors''. Center of Cognitive and Computational Neuroscience, Stirling Univ., Stirling, FK9 4LA, ftp source (1994).
**113**- Taha, I., and Ghosh, J. : ``Symbolic Interpretation of Artificial
Neural Networks'',
**ANNIE**, St. Louis (1996). **114**- Takefuji, T.:`` Neural Network parallel Computing'', Kluwer Academic Publishers, SECS 0164 (1992).
**115**- Tang, Z., and Fishwick, P.A.:`` Feedforward Neural Nets as Models for Time Series Forecasting'', TR91-008, Computer & Info Science, University of Florida (1991).
**116**- Thimm, G., and Fiesler, E.:`` A Neural Network Construction Method based on Boolean Logic'', accepted for IEEE International Conference on Tools with Artificial Intelligence proceedings, Toulose, France (1996).
**117**- Thimm, G., and Fiesler, E.:`` Neural Network Pruning and Pruning Parameters, 1st OWSC'', http://www/bioele.nuee.nagoya-u.ac.jp/wsc1, 1st Online Workshop on Soft Computing, Nagoya, Japan (1996).
**118**-
Towell, G., and Shavlik, J. : ''Extracting Refined Rules From Knowledge Based Neural
Networks``, Machine Learning, 3(1),
*pp. 71-101*(1993). **119**-
Vapnik, V.N., and Chervonenkis, A.Y.:''
On the uniform convergence of relative frequencies of events to their probabilities'',
Theory of Probability and its Applications, 16(2),
*pp. 264-280*(1971). **120**- http://www.emsl.pnl.gov:2080/proj/neuron/neural/neural.ann.html
**121**-
Wang, L.: ''
A General Design For Temporal Sequence Processing Using Any Arbitrary Associative
Neural Network '', Artificial Intelligence - Sowing the seeds to the future,
Armidale New Wales, Australia,
**AI 21-25 Nov. 1994**, Proceedings of the 7th Australian Joint Conference on Artificial Intelligence, World Scientific, Singapore (1994). **122**-
Wang, H.A. and Chan, A.K.-H.: `` A feedforward neural network model
for Hang Seng Index'', Proceedings of 4th Australian Conference on
Information Systems, Brisbane,
*pp. 575-585*(1993). **123**-
Wedding, D.K. II, and Cios, K.J.: `` Time Series forecasting by combining RBF networks,
certainty factors, and the Box-Jenkins model'',
Journal of Neurocomputing, 10,
*pp. 149-168*(1996). **124**-
White, H.: ``Economic prediction using Neural Networks: The case
of the IBM daily stock returns'', Proceedings of IEEE International
Conference on Neural Networks,
*pp. 451-458*(1988). **125**- Widrow, B., and Hoff, M.E.:``
Adaptive switching circuits'',
**IRE WESCON Convention Record**, New York, IRE,*pp. 96-104*(1960). **126**- Windsor, C.G., and Harker, A.H.: ``
Multi-variate financial index prediction - a neural network study'',
Proceedings of International Neural Network Conference, Paris, France,
*pp. 357-360*(1990). **127**- Yamada, Y., Tomita, E. and Takahashi, H.: ``
Non-Searching Algorithms for the n-Queen Problem'',
EIC, COMP90-10,
*pp. 87-92*(1990). **128**- Yong, T.P.: ``Using Neuro Forecaster for time series
forecasting'', Proceedings of First Symposium on Intelligent Systems
Applications, Singapore,
*pp. 182-189*(1993).

**List of Publications Related to the Thesis:**

[1]
__ and Okamoto, T. : ``
Energy Function based on Restrictions for Supervised Learning on Feedforward Networks'',
Journal IPSJ (Journal of the Information processing society of Japan),
SIGMPS Transactions, vol.1, no.1 (accepted April 1998).
__

__
(Chapter 4)
__

__
[2]
and Okamoto, T. : ``
Neural Networks for Stock Exchange prediction with a Lyapunov-based training'',
Journal JIS (Journal of Intelligent Systems), Special issue on
Prediction & reasoning in neural networks, Australia (accepted August 1998,
to appear beginning of 1999).
__

__
(Chapter 4)
__

__
[3]
and Okamoto, T. : ``
A L-based Energy Function for SE Prediction'', WIRN'98,
Vietri Sul Mare, Salerno, Italy, Perspectives in Neural
Computing, Springer Verlag, Ed. John G. Taylor, ISBN 1-85233-051-1,
pp. 304-309 (to appear October 1998).
__

__
(Chapter 4)
__

__
[4]
and Okamoto, T. : ``
Parallelization methods for Neural Networks on different environments:
Advantages and Disadvantages'',
Journal of Information Science (IS), New Zealand, Elsevier, IS/2 Special Issue,
(sent April 1998, accepted September 1998).
__

__
(Chapter 8)
__

__
[5]
and Okamoto, T. : ``
A Parallelization Method for Neural Networks with Weak Connection Design'',
ISHPC'97, Lecture Notes in Computer Science 1336,
Eds. C. Polychronopoulos et Co., Springer, vol.1336, pp. 397-404 (1997).
__

__
(Chapter 8)
__

__
[6]
and Okamoto, T. : ``
Parallel Implementation Tool of NN on UNIX machines'',
ICONIP97/ANNES97/ANZIIS97, New Zealand, "Best Student Paper Award",
"Progress in Connection-Based Information Systems,
Eds. R. Kozma, A. Gray, R. Kilgour, B. Woodford, Univ. Otago, pp. 21-24 (1997).
__

__
(Chapter 8)
__

__
[7]
Cristea, P. and Okamoto, T. : ``
Neural Network Knowledge Extraction'',
Journal: Revue Roumaine des Sciences Technique, Serie EE (Electrotechn. et Energ.),
vol. 42, no. 4, (Oct.-Dec.), pp. 477-491 (1997).
__

__
(Chapter 12)
__

__
[8]
and Okamoto, T. : ``
The Development of a Sub-Symbolic Knowledge Eliciting Environment
from Feedforward Networks, serving as an Education Process Assistant'',
Journal of Educational Technology Research, JET society,
(sent May, conditionally accepted October, resent November)
__

__
(Chapter 12)
__

__
[9]
and Okamoto, T. : ``
The development of a neural network knowledge extraction environment for
teaching process assistance'',
ED-MEDIA/ED-TELECOM'98, 10th World Conference on Educational
Multimedia and Hypermedia and 10th World Conference on Educational
Telecommunications, Freiburg, Germany, 20-25 June 1998, Eds.
Thomas Ottmann and Ivan Tomek, organiz. AACE, vol 1, pp. 227-232
(1998).
__

__
(Chapter 12)
__

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[10]
and Okamoto, T. : ``
Sub-Symbolic Knowledge Extraction Environment for Teaching Process Assistance'',
KES98, vol. 3, IEEE, pp.411 - 417 (1998).
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(Chapter 12)
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[11]
and Okamoto, T. : ``
NN for Stock Exchange prediction; a Lyapunov based training'',
ICCIMA98 , Eds. Henri Selvaraj and Brijesh Verma, World Scientific,
pp. 416-421 (1998).
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[12]
and Okamoto, T. : ``
Energy function construction and Implementation for Stock Exchange prediction
NNs'', KES98, vol. 3, IEEE, pp. 403-410 (1998).
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[13]
and Okamoto, T. : ``
Deduction of an L-based energy function for SE Prediction'', ICCNS'98,
Second International Conference on Cognitive and Neural Systems, Boston, USA, as abstract,
pp. 119 (1998).
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[14]
and Okamoto, T. : ``
SEE Prediction - Construction of a L-based energy function'', NC'98,
International ICSC/IFAC Symposium on Neural Computation, Sept. 23-25,
Vienna Univ. of Technology, Ed. M. Heiss, ICSC Academic Press,
Canada/Switzerland, ISBN 3-906454-15-0, pp. 841-847 (1998).
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[15]
and Okamoto, T. : ``
An Energy Function for Stock Exchange Prediction'', IIZUKA'98,
Methodologies for the Conception, Design and Application of Soft Computing,
Iizuka, Japan, Eds. T. Yamakawa, G. Matsumoto, ISBN 981-02-3966-1, pp. 622-625 (1998).
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[16]
and Okamoto, T. : ``
The Development of a Feedforward NN for Financial Time Series Forecast'', ICONIP'98, JNNS'98,
Kitakyuushu, Japan, Eds. S. Usui, T. Omori, ISBN 4-274-90256-0, pp. 1024-1027 (1998).
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[17]
and Okamoto, T. : ``
Stock exchange Analysis as Time-Series; Forecasting with Neural Nets'',
Tech. Rep. IEICE, AI-96, Japan, vol. 96, no. 594, pp.9 - 16, (1997).
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Author's Biography
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Miss Alexandra Cristea was born in Bucharest, Romania, on the 24th of August, 1971. She studied for her Master-thesis at the Technical University of Denmark, Lyngby, in 1994, sponsored by a Tempus grant, and received the Master of Eng. title in 1994 from the Faculty of Computer Science, "Politehnica" University of Bucharest, Romania. After graduation she has been employed as an assistant at the Faculty of Computer Science, giving seminars in Neural Networks, Computer Networks, Programming Languages and Artificial Intelligence. From April 1996 she has entered the Doctor course at the Laboratory of Artificial Intelligence and Knowledge Engineering, Graduate School of Information Systems, University of Electro-Communications, Japan, and has been doing her research sponsored by a grant offered by the Japanese Ministry of Education. She also received the MBA title in 1997 from the Faculty of Economical Engineering, Department of Engineering Sciences, "Politehnica" University of Bucharest, Romania, in collaboration with the Technische Hochschule Darmstadt (THD), Germany. She has been an ACE member and is a student member of IEICE (Institute of Electronics, Information and Communication Engineers), IEEE and IEEE Computer Society. She has received the "Best Student (Oral) Paper Award" at the International Conference ICONIP'97, in New Zealand. She is a member of the Romanian-Japanese cooperation project with the theme "Knowledge Extraction from Neural Networks".
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Tue Feb 9 20:20:27 JST 1999