Search Results for "genetic algorithm java"
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Showing 8 open source projects for "genetic algorithm java"
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Venice is a stock market trading programme that supports portfolio management, charting, technical analysis, paper trading and genetic programming. Venice runs in a graphical user interface with online help and has full documentation.
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Cenobi
cost estimation and management accounting, using neural networks
Cenobi is designed for management accountants, not (only) for statisticians and data mining experts. Carefully arranged default settings make sure you can concentrate on Cenobi's many accounting features rather than worrying about setting up artificial neural networks or genetic algorithms, which are the main machine learning tools under Cenobi's hood. Cenobi's main benefits are: - ease of use - Utilizing artificial neural networks to estimate cost relationships, Cenobi is able... -
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OpenForecast is a package of general purpose, forecasting models written in Java that can be applied to any data series. No knowledge of forecasting is required. Using this package, the most appropriate algorithm for your data will be selected.
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A suite of libraries and applications using genetic algorithms and AI for financial analysis and simulation. Currently the focus is to route FIX messages to an exchange simulator and use genetic algorithms to explore algorithmic trading strategies.
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This program serves to keep track of different types of accounts (technically an infinity number of different types). Currently only bank and equity accounts are supported. Data is saved on the user's computer and encrypted using the DES-algorithm.
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EvoTrader is a stock picking platform that utilizes genetic programming to evolve rules for generating stock trading signals.
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A Java library for validation of credit cards. Implements the Luhn Algorithm to ensure the card number is well formed, checks card type prefix's and length. The rules are stored in a text file allowing new cards to be added without changing the source
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A collection of portfolio management components. Sharpe Model for selection of an initial portfolio is already implemented. A genetic algorithms package, also written in java, is used for the search of the best portfolio variants.
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