Titlebook: Natural Computing in Computational Finance; Volume 2 Anthony Brabazon,Michael O’Neill Book 2009 Springer-Verlag Berlin Heidelberg 2009 Comp

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書目名稱Natural Computing in Computational Finance影響因子(影響力)




書目名稱Natural Computing in Computational Finance影響因子(影響力)學(xué)科排名




書目名稱Natural Computing in Computational Finance網(wǎng)絡(luò)公開度




書目名稱Natural Computing in Computational Finance網(wǎng)絡(luò)公開度學(xué)科排名




書目名稱Natural Computing in Computational Finance被引頻次




書目名稱Natural Computing in Computational Finance被引頻次學(xué)科排名




書目名稱Natural Computing in Computational Finance年度引用




書目名稱Natural Computing in Computational Finance年度引用學(xué)科排名




書目名稱Natural Computing in Computational Finance讀者反饋




書目名稱Natural Computing in Computational Finance讀者反饋學(xué)科排名

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1860-949X application of Natural Computing algorithms (broadly defined in this context as computer algorithms whose design draws inspiration from phenomena in the natural world) for the purposes of financial modelling and optimisation. A related stream of work has also seen the application of learning mechani

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Income Distribution and Lottery Expenditures in Taiwan: An Analysis Based on Agent-Based Simulationncomes, based on household income data in Taiwan from 1979 to 2003. The simulation results indicated that the impact of income distribution on lottery sales is not significant. This might be due to the Taiwan economy having a minor degree of income variation which has a low effect on lottery expenditures.

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The Emergence of a Market: What Efforts Can Entrepreneurs Make?mic co-evolution at the individual level. The results indicate that the process of market creation is significantly impacted by factors including exploration tendency, alertness, and participant prior knowledge.

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Classical and Agent-Based Evolutionary Algorithms for Investment Strategies Generationried out with the use of real-life stock data. The conclusions drawn from the results of experiments are such that co-evolutionary and agent-based co-evolutionary techniques better maintain population diversity and generate more general investment strategies than evolutionary algorithms.

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