NeuralCode Neural Networks Trading 1.0
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| Homepage: http://www.spreadsheetml.com | ||
| Type: Commercial | ||
| Releases: Oct 23, 2008 | ||
| Cost: $129.00US | ||
| Developer: ConnectCode Pte Ltd | ||
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NeuralCode is an industrial grade Artificial Neural Networks implementation for financial prediction. The software can take data like the Opening price, High, Low, Volume and other technical indicators for predicting or uncovering trends and patterns. It is designed to utilize Supervised Learning with Multi-Layer Perceptrons and Optimized Back Propagation for complex learning.
In mathematical theory, under suitable conditions, the iterative procedure of adjusting the weights causes the networks to converge to a set of correct weights that can be useful for predicting complex (non linearly separable problems) trends and patterns. Thus NeuralCode is a very useful tool to be used together with financial Technical Indicators like moving average, true range, relative strength index , moving average convergence and divergence.
The software is implemented entirely without external object libraries and thus will not require data to be passed out for processing. This results in extremely efficient and optimized processing. The development of the software is focused on accuracy and thus will ensure the global minimum is found instead of just a local minimum. After training, the prediction is almost instantaneous.
In mathematical theory, under suitable conditions, the iterative procedure of adjusting the weights causes the networks to converge to a set of correct weights that can be useful for predicting complex (non linearly separable problems) trends and patterns. Thus NeuralCode is a very useful tool to be used together with financial Technical Indicators like moving average, true range, relative strength index , moving average convergence and divergence.
The software is implemented entirely without external object libraries and thus will not require data to be passed out for processing. This results in extremely efficient and optimized processing. The development of the software is focused on accuracy and thus will ensure the global minimum is found instead of just a local minimum. After training, the prediction is almost instantaneous.
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