Elena B Utu (3 results)
- Softcover
Seller: preigu, Osnabrück, Germanypreigu
Contact seller5-star sellerCondition: New
US$ 79.28
US$ 81.02 shippingShips from Germany to U.S.A.Quantity: 5 available
Taschenbuch. Condition: Neu. Intelligent Techniques for Data Modeling Problems | Nature inspired meta-heuristics and learning models applied to time series modeling and forecasting | Elena B utu | Taschenbuch | Englisch | LAP Lambert Academic Publishing | EAN 9783848434794 | Verantwortliche Person für die EU: preigu GmbH & Co. K…G, Lengericher Landstr. 19, 49078 Osnabrück, mail[at]preigu[dot]de | Anbieter: preigu.
- Softcover
- Print on Demand
Seller: AHA-BUCH GmbH, Einbeck, GermanyAHA-BUCH GmbH
Contact seller5-star sellerCondition: New
US$ 71.18
US$ 70.73 shippingShips from Germany to U.S.A.Quantity: 1 available
Taschenbuch. Condition: Neu. nach der Bestellung gedruckt Neuware - Printed after ordering - The importance of finding a well fitted model for hydro-meteorological time series cannot be denied, the main gain of a successful approach being the possibility to explain the past and to provide informed insight for the future. Therefo…re, we tried to present here some techniques that can be used to build a mathematical model for time series (particularly for hydro-meteorological ones), starting from statistical tests of data analysis, passing to the empirical models, nonparametric techniques, ARIMA models and heuristic methods. Since our intention was to write a book easy to read, the theory is shortly presented and is followed by applications on real data that are the results our three years research work. We hope that this material will be useful for postgraduate students, as well as for the researchers.
- Softcover
- Print on Demand
Seller: AHA-BUCH GmbH, Einbeck, GermanyAHA-BUCH GmbH
Contact seller5-star sellerCondition: New
US$ 95.31
US$ 71.47 shippingShips from Germany to U.S.A.Quantity: 2 available
Taschenbuch. Condition: Neu. nach der Bestellung gedruckt Neuware - Printed after ordering - Supervised learning deals with the problem of discovering models from data as relationships between input and output attributes. Two types of models are distinguished: regression models (for continuous output attributes) and classificati…on models (for discrete output attributes). This thesis addresses both regression and classification problems with an emphasis on new applications and on presenting improved evolutionary techniques. Such techniques include Gene Expression Programming (classical and its adaptive version), Genetic Programming, and the hypernetwork model of learning (classical and its evolutionary version). Such methods can be successfully applied to many problems from various domains. This thesis presents applications for symbolic regression for inverse problems, quantum circuit design, modeling of dynamic processes, and forecasting price movement.
