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

人充满活力

,Ernst Julius Hähnel Beethoven-Denkmal 1845,ercised at any time during the period and are, therefore, more complex due to the second random process they introduce. Support vector machines and multi-layered perceptron techniques are implemented using Bayesian technique to model American options and the results are compared.

肉身

Jason P. Harmon,Erin Stephens,John Loseyd using a multi-layered perceptron network, while the optimization techniques which are implemented are particle swarm optimization, genetic algorithms and simulated annealing. The results obtained are then compared.

不易燃

https://doi.org/10.1007/978-3-662-11229-8sing economic data estimation. The algorithm is used on data that contain ten economic variables. The results of the missing data imputation approach are compared to those from a feed-forward neural network.

扩大

https://doi.org/10.1007/978-3-319-98437-7l inflation through the manipulation of interest rates. Given the historical inflation rate data, a control scheme is used to determine the interest rate that is required to attain the given inflation rate. The calculated interest rate is then compared to the historical inflation rate to evaluate the effectiveness of the control strategy.

CRASS

Before Architecture. Vor der Architekturigated and compared, as well as optimizing the non-targeted variable to create efficient portfolios. The findings showed that GA is, indeed, a viable tool for optimizing a targeted portfolio using the presented fitness function.

Self-Help-Group

Evolutionary Approaches to Computational Economics: Application to Portfolio Optimization,igated and compared, as well as optimizing the non-targeted variable to create efficient portfolios. The findings showed that GA is, indeed, a viable tool for optimizing a targeted portfolio using the presented fitness function.

沙发

Rough Sets Approach to Economic Modeling: Unlocking Knowledge in Financial Data,rket forecasting model an interesting problem. In this chapter a rough set theory based forecasting model is applied to the financial markets to identify a set of reducts and possibly a set of trading rules based on trading data.

明确

Introduction to Economic Modeling,ge discovery, including data mining and causality versus correlation. It also outlines some of the common errors in economic modeling with regard to data handling, modeling, and data interpretation. It surveys the relevant econometric methods and motivates for the use of artificial intelligence meth

glacial

Automatic Relevance Determination in Economic Modeling,bed in detail, relevant literature reviews are conducted, and their use is justified. The automatic relevance determination technique is then applied to determine the relevance of economic variables that are essential for driving the consumer price index. Conclusions are drawn and are explained with

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