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Economia Para Principiantes: Desde la antigua Grecia hasta by Alejandro-Sanyu Garvie

By Alejandro-Sanyu Garvie

Econom?a para principiantes es una breve historia de los angeles humanidad en clave econ?mica. Ofrece una mirada comprensiva sobre el pensamiento econ?mico de los antiguos griegos, los angeles importancia del Derecho Romano, el pensamiento econ?mico de Santo Tom?s y de l. a. Iglesia Cat?lica, el orden feudal, el nacimiento del capitalismo, los angeles econom?a sovi?tica, el inicio y los angeles difficulty de los angeles globalizaci?n, las teor?as econ?micas y cosmovisiones de Adam Smith, David Ricardo, Thomas Malthus, Alfred Marshall, Carlos Marx.

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Evolving Systems: Methodology and Applications. , Hoboken (2010) 2. : An approach to online identification of Takagi-Sugeno fuzzy models. IEEE Transactions on Systems, Man, and Cybernetics – Part B: Cybernetics 4(1), 484–498 (2004) 3. : Evolving fuzzy systems from data streams in real-time. In: 2006 International Symposium on Evolving Fuzzy Systems, Ambleside, September 7-9, pp. 29–35 (2006) 4. : Surveying stock market forecasting techniques Part II: Soft computing methods. Expert Systems with Applications 36(3), 5931– 5941 (2009) 5.

Ballini Uik = k l=1 γl , i = 1, 2, . . , R; k = 2, 3, . . k − T i∗ (7) ∗ where T i denotes the time tag which indicates when a fuzzy rule is generated. 1]) [1]. This condition means that if some cluster has low utility (lower than an threshold ε), the data pattern has shifted away from the focal point of that rule, then the rule that satisfies Condition III is removed. This quality measure evaluates the importance of the fuzzy rules and assists the evolving process. 2 Participatory Learning Clustering The ePL approach joins the concept of participatory learning with the evolving fuzzy modeling idea.

A refined fussy time series model for stock market forecasting. Physica A: Statistical Mechanics and its Applications 387(12), 2857–2862 (2008) 10. : DENFIS: Dynamic evolving neural-fuzzy inference system and its application for time series prediction. IEEE Transactions on Fuzzy Systems 10(2), 144–154 (2002) 11. : Evolving and clustering fuzzy decision tree for financial time series data forecasting. Expert Systems with Applications 36(2), 3761–3773 (2009) 12. : Evolving fuzzy modeling using participatory learning.

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