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Application of Neural Networks in Area of Management Decision Making
Details
Neural networks have emerged as a field of study within AI and decision-making via the collaborative efforts of engineers, physicists, mathematicians, computer scientists, and neuroscientists. Although the strands of research are many, there is a basic underlying focus on pattern recognition and pattern generation, embedded within an overall focus on network architectures. Many neural network methods can be viewed as generalizations of classical pattern-oriented techniques in statistics and decision-making systems, optimization, and numerical analysis. This research is an effort to study the implementation of statistical techniques in the area of neural networks in management decision-making. In this research various motivational theories (content) are studied. Different motivational factors from these theories are analyzed and compared within todays work envionment. An analysis is carried out to study the factors that act as motivators in today s work culture in Indian service sector.Application of neural networks is carried on regression model constructed after factor analysis of the items identified from these theories and mordern work culture.
Autorentext
Author is working with INMANTEC Ghaziabad, 'A'rated B school in India, as Associate Prof.Management having experience of 15+ yrs. Numberof research Papers have been published/presented invarious International and National conferencesincluding one at Bangkok and other at Los Angeles.Written 5 books on ENTREPRENEURSHIPDEVELOPMENT & STATISTIC.
Weitere Informationen
- Allgemeine Informationen
- GTIN 09783659317637
- Sprache Englisch
- Größe H220mm x B220mm x T150mm
- Jahr 2013
- EAN 9783659317637
- Format Kartonierter Einband (Kt)
- ISBN 978-3-659-31763-7
- Titel Application of Neural Networks in Area of Management Decision Making
- Autor Bhawna Garg , Deepak Saxena
- Untertitel In Combination with Regression Analysis
- Herausgeber LAP Lambert Academic Publishing
- Anzahl Seiten 64
- Genre Wirtschaft