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Tuesday, February 22, 2011. Artificial Neural Network models for Forecasting and Decision making. By Tim Hill (University of Hawaii), Leorey Marquez (CSIRO), Marcus O’Connor (University of New South Wales), William Remus (University of Hawaii). Some of the advantages the paper discusses of neural networks over statistical methods:. Artificial neural networks can be universal function approximates for even non-linear functions. Artificial neural networks can estimate piece-wise approximations of functions.

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Travel AI | desmkgpro18.blogspot.com Reviews

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Tuesday, February 22, 2011. Artificial Neural Network models for Forecasting and Decision making. By Tim Hill (University of Hawaii), Leorey Marquez (CSIRO), Marcus O’Connor (University of New South Wales), William Remus (University of Hawaii). Some of the advantages the paper discusses of neural networks over statistical methods:. Artificial neural networks can be universal function approximates for even non-linear functions. Artificial neural networks can estimate piece-wise approximations of functions.

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Travel AI | desmkgpro18.blogspot.com Reviews

https://desmkgpro18.blogspot.com

Tuesday, February 22, 2011. Artificial Neural Network models for Forecasting and Decision making. By Tim Hill (University of Hawaii), Leorey Marquez (CSIRO), Marcus O’Connor (University of New South Wales), William Remus (University of Hawaii). Some of the advantages the paper discusses of neural networks over statistical methods:. Artificial neural networks can be universal function approximates for even non-linear functions. Artificial neural networks can estimate piece-wise approximations of functions.

INTERNAL PAGES

desmkgpro18.blogspot.com

1

Travel AI: Intelligent Decision Support System for Tourism Destination Choice: A Preliminary Study

http://desmkgpro18.blogspot.com/2011/02/intelligent-decision-support-system-for.html

Monday, February 7, 2011. Intelligent Decision Support System for Tourism Destination Choice: A Preliminary Study. Noor Maizura Mohamad Noor, Ily Ama lina Ahm, Fathilah Ismail. This paper describes a research and development of an intelligent decision support system for tourism destination choice based on fuzzy logic. The main focus of the paper is to identifying the procedure to be followed in building the above mentioned system. C Real task and scenario task in tourism. This phase is a period when deci...

2

Travel AI: Artificial Neural Network models for Forecasting and Decision making

http://desmkgpro18.blogspot.com/2011/04/artificial-neural-network-models-for.html

Tuesday, February 22, 2011. Artificial Neural Network models for Forecasting and Decision making. By Tim Hill (University of Hawaii), Leorey Marquez (CSIRO), Marcus O’Connor (University of New South Wales), William Remus (University of Hawaii). Some of the advantages the paper discusses of neural networks over statistical methods:. Artificial neural networks can be universal function approximates for even non-linear functions. Artificial neural networks can estimate piece-wise approximations of functions.

3

Travel AI: Using Neural Networks to Forecast Stock Market Prices

http://desmkgpro18.blogspot.com/2011/04/using-neural-networks-to-forecast-stock.html

Saturday, February 12, 2011. Using Neural Networks to Forecast Stock Market Prices. By Ramon Lawrence, Department of Computer Science, University of Manitoba. Inherent time delay , it cannot address the dynamic nature of the stock market. But as the Neural network functions parallel, consumes less time compared to expert systems and fault-tolerant. One of the best solutions would be combining both Neural networks and Expert systems. So the neural nets can be used for prediction making while expert sy...

4

Travel AI: Training intelligent agents in the semantic web era: The golf advisor agent

http://desmkgpro18.blogspot.com/2010/12/training-intelligent-agents-in-semantic.html

Sunday, December 5, 2010. Training intelligent agents in the semantic web era: The golf advisor agent. By Ioannis N. Athanasiadis. This paper investigates how data-driven rule-sets can be transcribed into ontologies (Formal representation of knowledge as a set of concepts within a domain and the relationships between those concepts) , and how semantic web technologies as OWL can be used for defining both agent resources and reasoning. Golf playing agent rule set. Subscribe to: Post Comments (Atom). There...

5

Travel AI: November 2010

http://desmkgpro18.blogspot.com/2010_11_01_archive.html

Saturday, November 27, 2010. 115 am to 3.00 pm. Conference room, Codegen International (pvt) Ltd. Thursday, November 25, 2010. A Brief History of Decision Support Systems by D. J. Power. This is a survey paper which was written on decision support systems (DSS) theory evolution and history. This paper doesn’t address a specific problem regarding decision support systems. Rather it discusses about DSS under the following topics. Decision support system origins. Knowledge system: For all knowledge a DSS has.

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desmkgpro18.blogspot.com

Travel AI

Tuesday, February 22, 2011. Artificial Neural Network models for Forecasting and Decision making. By Tim Hill (University of Hawaii), Leorey Marquez (CSIRO), Marcus O’Connor (University of New South Wales), William Remus (University of Hawaii). Some of the advantages the paper discusses of neural networks over statistical methods:. Artificial neural networks can be universal function approximates for even non-linear functions. Artificial neural networks can estimate piece-wise approximations of functions.

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