Key new features of IMSL™ C Numerical Library 6.0 include:

• Neural Network Engine — mimics human problem-solving processes by applying knowledge gained from historical data to new problems, which fine-tunes forecasting accuracy over time. Visual Numerics’ neural network technology features advanced data pre-processing to simplify data mining preparation and ensure optimal accuracy and performance, saving significant time over manual pre-processing. This technology is optimal for highly configurable data mining and forecasting with no limits on network size
• Dense Linear Programming Optimizer — for state-of-the-art constrained dense linear programming optimization. This version of IMSL C Numerical Library offers the world’s fastest optimizer of its kind in a general mathematical library. In 2005 tests, IMSL solved 46 example problems in one-eighth the time of a leading Linear Programming Optimizer product. Also includes MPS format readers to facilitate usage with existing users of Linear Programming and will be welcomed by capital markets customers doing portfolio optimization, trading systems and risk modeling
• Auto_ARIMA — advanced forecasting routine for time series analysis. It is highly suited to situations where data is prone to seasonality “spikes” or “outliers” such as operations management or inventory planning
• Differential Equations Package —for financial engineering and scientific computing
• New random number generator technique using Mersenne Twister algorithm
• New LAPACK (Linear Algebra PACKage) functionality

“By adding fully-tested linear programming optimization, neural network capabilities and Auto_ARIMA, we’re able to make our IMSL™ C Library a much more powerful and cost-effective option for companies who need state-of-the-art forecasting applications,” said Phil Fraher, president and CEO of Visual Numerics. “IMSL™ C Numerical Library 6.0 leverages the proven reliability and easy deployment of our industry-leading IMSL library but with added technology that make it even better for performing predictive analytics.”

Para maiores informações visite o site da Visual Numerics, Inc:   www.vni.com

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