Windows Neural Networks (WinNN) is a shareware windows
neural networks simulator. WinNN can handle multi-layered feed forward
networks and train using modified back-propagation. WinNN has a very
friendly user interface and fast computational engine to run the calculations.
WinNN can import data, train, and plot the results.
WinNN runs under on All Windows versions including 7 32 & 64
Some of the features of WinNN:
- WinNN32 is a fast 32-bit implementation that tested
to run on Windows 95/98/NT/2000/XP/Me/Vista/WIndows 7.
- Smoothly trains in the background. Supports DDE
with Excel (use NN predictions in Excel).
- Built in graphics to plot the NN architecture and
- All files are written in simple ASCII format that
can be used by other programs.
- The trained NN can easily be used from all programming
- WinNN is available since1994.
Links and references to work done using WinNN:
of Neural Networks to Determine Properties of Alkanes from their 13C-NMR
- Quantification of apoptotic and lytic cell death by video microscopy
in combination with artificial
neural networks, Cytometry, Volume 31,
Issue 1 , Pages 20 - 28, 6 Dec 1998.
- Comparison of Viral Load and Human Leukocyte Antigen
Statistical and Neural
Network Predictive Models for the Rate of HIV-1 Disease Progression
Across Two Cohorts of Homosexual Men. Journal of Acquired Immune
Deficiency Syndromes & Human Retrovirology. 20(2):129-136, February
Modeling: Advances in Open Pit Mine Design and Optimization
International Journal of Surface Mining, Reclamation and
Environment,Volume 16, Number 2 / June 2002.
- A NEURAL
NETWORK MODEL OF THE SALINITY IN THE WEST PEARL RIVER
of Sensorineural Hearing Loss with Neural
Networks versus Logistic
Regression Modeling of Distortion Product Otoacoustic
Emissions, Audiology & Neuro-Otology.
9(2):81-87, March/April 2004.
- Geometric Constraints in Image Sequence and Neural Networks for ...
Conditions & Core Inflation: An Application of Neural Networks
- CS Principles
- P. Salem (editor),"Neural Networks Applications in
Social Science Research.", Organizational communication
and change. Pp. 151-173. Cresskill, NJ: Hampton Press (1999).