ARTIFICIAL+INTELLIGENCE+AND+RESPONSIVE+Optimization

ARTIFICIAL+INTELLIGENCE+AND+RESPONSIVE+Optimization - M....

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M. Khoshnevisan, S. Bhattacharya, F. Smarandache ARTIFICIAL INTELLIGENCE AND RESPONSIVE OPTIMIZATION (second edition) Xiquan Phoenix 2003 Utility Index Function (Event Space D) y = 24.777x 2 - 29.831x + 9.1025 0.000 0.100 0.200 0.300 0.400 0.500 0.600 0.700 0.800 0.900 Expected excess equity
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1 M. Khoshnevisan, S. Bhattacharya, F. Smarandache ARTIFICIAL INTELLIGENCE AND RESPONSIVE OPTIMIZATION (second edition) Dr. Mohammad Khoshnevisan, Griffith University, School of Accounting and Finance, Queensland, Australia. Sukanto Bhattacharya, School of Information Technology, Bond University, Australia. Dr. Florentin Smarandache, Department of Mathematics, University of New Mexico, Gallup, USA. Xiquan Phoenix 2003
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2 This book can be ordered in microfilm format from: ProQuest Information & Learning (University of Microfilm International) 300 N. Zeeb Road P.O. Box 1346, Ann Arbor MI 48106-1346, USA Tel.: 1-800-521-0600 (Customer Service) http://wwwlib.umi.com/bod/ (Books on Demand) Copyright 2003 by Xiquan & Authors 510 East Townley Av., Phoenix, USA Many books can be downloaded from our E-Library of Science : http://www.gallup.unm.edu/~smarandache/eBooks-otherformats.htm This book has been peer reviewed and recommended for publication by: Dr. V. Seleacu, Department of Mathematics / Probability and Statistics, University of Craiova, Romania; Dr. Sabin Tabirca, University College Cork, Department of Computer Science and Mathematics, Ireland; Dr. W. B. Vasantha Kandasamy, Department of Mathematics, Indian Institute of Technology, Madras, Chennai – 600 036, India. The International Statistical Institute has cited this book in its "Short Book Reviews", Vol. 23, No. 2, p. 35, August 2003, Kingston, Canada. ISBN : 1-931233-77-2 Standard Address Number 297-5092 Printed in the United States of America University of New Mexico, Gallup, USA
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3 Forward The purpose of this book is to apply the Artificial Intelligence and control systems to different real models. In part 1, we have defined a fuzzy utility system, with different financial goals, different levels of risk tolerance and different personal preferences, liquid assets, etc. A fuzzy system (extendible to a neutrosophic system ) has been designed for the evaluations of the financial objectives. We have investigated the notion of fuzzy and neutrosophiness with respect to time management of money. In part 2, we have defined a computational model for a simple portfolio insurance strategy using a protective put and computationally derive the investor’s governing utility structures underlying such a strategy under alternative market scenarios. The Arrow-Pratt measure of risk aversion has been used to determine how the investors react towards risk under the different scenarios. In Part 3, it is proposed an artificial classification scheme to isolate truly benign tumors from those that initially start off as benign but subsequently show metastases. A non- parametric artificial neural network methodology has been chosen because of the analytical difficulties associated with extraction of closed-form stochastic-likelihood parameters given the extremely complicated and possibly non-linear behavior of the state
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This note was uploaded on 08/10/2011 for the course IT 331 taught by Professor Nevermind during the Spring '11 term at King Abdulaziz University.

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ARTIFICIAL+INTELLIGENCE+AND+RESPONSIVE+Optimization - M....

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