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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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發(fā)表于 2025-3-21 18:21:00 | 只看該作者 |倒序?yàn)g覽 |閱讀模式
書目名稱Economic Modeling Using Artificial Intelligence Methods
編輯Tshilidzi Marwala
視頻videohttp://file.papertrans.cn/302/301711/301711.mp4
概述Presents new insights into the modeling of economic data.Proposes a structure for evaluating economic strategies such as inflation targeting founded on artificial intelligence techniques.Addresses cau
叢書名稱Advanced Information and Knowledge Processing
圖書封面Titlebook: Economic Modeling Using Artificial Intelligence Methods;  Tshilidzi Marwala Book 2013 Springer-Verlag London 2013 Artificial Intelligence.B
描述.Economic Modeling Using Artificial Intelligence Methods. .examines the application of artificial intelligence methods to model economic data. Traditionally, economic modeling has been modeled in the linear domain where the principles of superposition are valid. The application of artificial intelligence for economic modeling allows for a flexible multi-order non-linear modeling. In addition, game theory has largely been applied in economic modeling. However, the inherent limitation of game theory when dealing with many player games encourages the use of multi-agent systems for modeling economic phenomena..The artificial intelligence techniques used to model economic data include:.multi-layer perceptron neural networks.radial basis functions.support vector machines.rough sets.genetic algorithm.particle swarm optimization.simulated annealing.multi-agent system.incremental learning.fuzzy networks.Signal processing techniques are explored to analyze economic data, and these techniques are the time domain methods, time-frequency domain methods and fractals dimension approaches. Interesting economic problems such as causality versus correlation, simulating the stock market, modeling and
出版日期Book 2013
關(guān)鍵詞Artificial Intelligence; Bayesian; Boolean Reasoning; Causality; Computational Intelligence; Decision Rul
版次1
doihttps://doi.org/10.1007/978-1-4471-5010-7
isbn_softcover978-1-4471-5919-3
isbn_ebook978-1-4471-5010-7Series ISSN 1610-3947 Series E-ISSN 2197-8441
issn_series 1610-3947
copyrightSpringer-Verlag London 2013
The information of publication is updating

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1610-3947 niques are the time domain methods, time-frequency domain methods and fractals dimension approaches. Interesting economic problems such as causality versus correlation, simulating the stock market, modeling and978-1-4471-5919-3978-1-4471-5010-7Series ISSN 1610-3947 Series E-ISSN 2197-8441
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Book 2013onally, economic modeling has been modeled in the linear domain where the principles of superposition are valid. The application of artificial intelligence for economic modeling allows for a flexible multi-order non-linear modeling. In addition, game theory has largely been applied in economic model
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Missing Data Approaches to Economic Modeling: Optimization Approach,d 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.
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1610-3947 founded on artificial intelligence techniques.Addresses cau.Economic Modeling Using Artificial Intelligence Methods. .examines the application of artificial intelligence methods to model economic data. Traditionally, economic modeling has been modeled in the linear domain where the principles of su
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