Neural network software for forecasting, data analysis and classification. It allows you improving your forecasting using the power of neural network technology. See Neural Network Trading Software Index
Alyuda's innovative patent-pending algorithms and acknowledged expertise have earned it the reputation of a trusted provider of artificial intelligence technology. The company's products are used globally in financial applications, budgeting and planning, human resource management, process control, customer retention and scientific applications.
family of tools and solutions are based upon the proprietary algorithms of automatic neural network architecture selection and data pre-processing. These are the core algorithms that can be applied to a wide range of neural network-based solutions from easy-to-use forecasting tools to corporate data analysis systems.
These new methods and algorithms are combined with the latest advances in artificial neural networks and genetic algorithms that are carefully selected and tested by Alyuda experts on a comprehensive set of real-world applications.
Why neural networks?
Neural networks are now globally recognized as the most effective and appropriate artificial intelligence technology for pattern recognition. Superior results in pattern recognition can be directly applied to business applications in forecasting, classification and data analysis. This new approach offers extra advantage in solving "real-world" problems in business and engineering.
But to bring proper results the neural networks require correct data pre-processing, correct architecture selection and correct network training. In the past, most failures in using neural networks came from improper user's skills in appropriate preparation of data and design of a neural network. Nowadays, business benefits of neural technology are highly underestimated still due to difficulties in appropriate data pre-processing and network construction.
Alyuda focus their efforts exactly on these issues that prevent many business people from using the tremendous potential of this promising technology. With automatic data pre-processing and architecture selection algorithms from Alyuda coupled with easy-to-use tools, the neural networks became easy enough for every manager to use - without expensive formal training.
What are neural networks?
Neural networks are data analysis methods and algorithms loosely based on nervous systems of humans and animals.
In general terms, an artificial neural network consists of a large number of simple processing units linked by weighted connections. By analogy, the processing units may be called neurons. Each unit receives inputs from many other units and generates a single output. The output acts as an input to other processing units.
The power of neural network comes from the combination of many units in a network. A certain network may be tuned to solve a particular problem by varying the connection topology and values of the connecting weights between units.
An artificial neural network is nonlinear in nature and thus is the exceptionally powerful method of analyzing real-world data that allows modeling extremely difficult dependencies.
Neural nets are proven to be among the best methods to detect hidden relations in a dataset (e.g. stock market data or sales data). Once a neural network has analyzed your dataset (this process is called network training), it is able to make predictions, pattern recognition and categorization based on these found hidden dependencies.
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