Soft Computing Techniques And Applications In Financial Engineering

Tahseen Jilani

ISBN 10: 3838372042 / ISBN 13: 9783838372044

Verlag: LAP LAMBERT Academic Publishing Jun 2010, 2010

Beschreibung

This item is printed on demand - it takes 3-4 days longer - Neuware -Soft Computing is an emerging approach which parallels the remarkable ability of the human brain to reason and learn in an environment of uncertainty and imprecision. It is one of the most emerging consortiums of methodologies including artificial neural networks (ANNs), fuzzy logic (FL) etc. They provide tractable, robust and lower cost solutions to the complex and gigantic real world-problems with the help of functional approximations and learning paradigms. It can also handle linguistic uncertainties, vagueness and imprecision involved in real life problems with reduced mathematical complexities. Soft computing techniques have outperformed the conventional approaches with lesser complexity, vagueness, tuning requirements and higher level of robustness, and tractability. On the other hand, most of the actuarial problems are stochastic in nature with soaring noises and variable volatilities, resulting in signals that are complicated to handle with conventional modeling and forecasting techniques. 132 pp. Englisch. Bestandsnummer des Verkäufers 9783838372044

Bibliografische Details

Titel: Soft Computing Techniques And Applications ...

Verlag: LAP LAMBERT Academic Publishing Jun 2010

Erscheinungsdatum: 2010

Einband: Taschenbuch

Zustand: Neu

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Inhaltsangabe:

Soft Computing is an emerging approach which parallels the remarkable ability of the human brain to reason and learn in an environment of uncertainty and imprecision. It is one of the most emerging consortiums of methodologies including artificial neural networks (ANNs), fuzzy logic (FL) etc. They provide tractable, robust and lower cost solutions to the complex and gigantic real world-problems with the help of functional approximations and learning paradigms. It can also handle linguistic uncertainties, vagueness and imprecision involved in real life problems with reduced mathematical complexities. Soft computing techniques have outperformed the conventional approaches with lesser complexity, vagueness, tuning requirements and higher level of robustness, and tractability. On the other hand, most of the actuarial problems are stochastic in nature with soaring noises and variable volatilities, resulting in signals that are complicated to handle with conventional modeling and forecasting techniques.