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Titlebook: Economic Modeling Using Artificial Intelligence Methods; Tshilidzi Marwala Book 2013 Springer-Verlag London 2013 Artificial Intelligence.B

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楼主: 战神
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Beethoven im Gespräch: Die neun Sinfonienapplied to model inflation by training these networks using the maximum-likelihood method. The results indicated that the SVM gives the best results followed by the MLP and then the RBF. The SVM with an exponential RBF gave the best results.
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https://doi.org/10.1007/978-3-476-03589-9ncial markets are the foundation of every economy and there are many aspects that affect the direction, volume, price, and flow of traded stocks. The markets’ weakness to external and non-financial features as well as the ensuing volatility makes the development of a robust and accurate financial ma
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https://doi.org/10.1007/978-3-662-11229-8ause and effect exercise, that is, feed-forward network. An auto-associative neural network is combined with genetic algorithm and then applied to missing economic data estimation. The algorithm is used on data that contain ten economic variables. The results of the missing data imputation approach
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https://doi.org/10.1007/978-1-349-18856-7 approach is implemented using a multi-layer perceptron as a weak-learner, where this weak-learner is improved by making use of the Learn++ algorithm. In addition, the Learn++ algorithm introduces the concept of on-line incremental learning, which means that the proposed framework is able to adapt t
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https://doi.org/10.1007/978-3-319-98437-7output model is constructed using a multi-layered perceptron network and a closed loop control strategy is adopted using a genetic algorithm to control inflation through the manipulation of interest rates. Given the historical inflation rate data, a control scheme is used to determine the interest r
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