Listing 1 - 5 of 5 |
Sort by
|
Choose an application
Choose an application
Self-organizing maps (SOM) have proven to be of significant economic value in the areas of finance, economic and marketing applications. As a result, this area is rapidly becoming a non-academic technology. This book looks at near state-of-the-art SOM applications in the above areas, and is a multi-authored volume, edited by Guido Deboeck, a leading exponent in the use of computational methods in financial and economic forecasting, and by the originator of SOM, Teuvo Kohonen. The book contains chapters on applications of unsupervised neural networks using Kohonen's self-organizing map approach.
Finance --- Neural networks (Computer science) --- Self-organizing maps --- Decision making --- Data processing --- Self-organizing maps. --- Artificial intelligence. Robotics. Simulation. Graphics --- Neural networks (Computer science). --- Data processing. --- Economics, Mathematical . --- Atoms. --- Physics. --- Finance. --- Quantitative Finance. --- Atomic, Molecular, Optical and Plasma Physics. --- Finance, general. --- Funding --- Funds --- Economics --- Currency question --- Natural philosophy --- Philosophy, Natural --- Physical sciences --- Dynamics --- Chemistry, Physical and theoretical --- Matter --- Stereochemistry --- Mathematical economics --- Econometrics --- Mathematics --- Constitution --- Methodology --- Artificial neural networks --- Nets, Neural (Computer science) --- Networks, Neural (Computer science) --- Neural nets (Computer science) --- Artificial intelligence --- Natural computation --- Soft computing --- Algorithms, Kohonen --- Kohonen algorithms --- Kohonen maps --- Kohonen's maps --- Maps, Kohonen --- Maps, Self-organizing --- SOMs (Self-organizing maps) --- Self-organizing systems --- Finance - Decision making - Data processing
Choose an application
A fundamental objective of Artificial Intelligence (AI) is the creation of in telligent computer programs. In more modest terms AI is simply con cerned with expanding the repertoire of computer applications into new domains and to new levels of efficiency. The motivation for this effort comes from many sources. At a practical level there is always a demand for achieving things in more efficient ways. Equally, there is the technical challenge of building programs that allow a machine to do something a machine has never done before. Both of these desires are contained within AI and both provide the inspirational force behind its development. In terms of satisfying both of these desires there can be no better example than machine learning. Machines that can learn have an in-built effi ciency. The same software can be applied in many applications and in many circumstances. The machine can adapt its behaviour so as to meet the demands of new, or changing, environments without the need for costly re-programming. In addition, a machine that can learn can be ap plied in new domains with the genuine potential for innovation. In this sense a machine that can learn can be applied in areas where little is known about possible causal relationships, and even in circumstances where causal relationships are judged not to exist. This last aspect is of major significance when considering machine learning as applied to fi nancial forecasting.
Finance --- Time-series analysis --- Artificial intelligence --- Neural networks (Computer science) --- Genetic Algorithms --- Fuzzy logic --- Decision making --- Data processing --- Mathematical models --- Artificial intelligence. Robotics. Simulation. Graphics --- Artificial intelligence. --- Special purpose computers. --- Public finance. --- Finance. --- Artificial Intelligence. --- Special Purpose and Application-Based Systems. --- Public Economics. --- Finance, general. --- Funding --- Funds --- Economics --- Currency question --- Cameralistics --- Public finance --- Public finances --- Special purpose computers --- Computers --- AI (Artificial intelligence) --- Artificial thinking --- Electronic brains --- Intellectronics --- Intelligence, Artificial --- Intelligent machines --- Machine intelligence --- Thinking, Artificial --- Bionics --- Cognitive science --- Digital computer simulation --- Electronic data processing --- Logic machines --- Machine theory --- Self-organizing systems --- Simulation methods --- Fifth generation computers --- Neural computers --- Finance - Decision making - Data processing --- Finance - Mathematical models
Choose an application
-Neural networks (Computer science) --- -Software --- Software. --- Finance --- Neural networks (Computer science) --- 681.3*I2 --- 681.3*I2 Artificial intelligence. AI --- Artificial intelligence. AI --- Artificial neural networks --- Nets, Neural (Computer science) --- Networks, Neural (Computer science) --- Neural nets (Computer science) --- Artificial intelligence --- Natural computation --- Soft computing --- Funding --- Funds --- Economics --- Currency question --- Decision making&delete& --- Data processing --- Software --- Artificial intelligence. Robotics. Simulation. Graphics --- International finance --- Decision making --- Finances --- Réseaux neuronaux (Informatique) --- Intelligence artificielle --- Prise de décision --- Informatique --- Artificial intelligence. --- Finance - Decision making - Data processing --- Neural networks (Computer science) - Software --- Finance - Decision making - Software --- Finances - Prise de décision - Informatique --- Data processing. --- Neural networks
Choose an application
The primary goal of this book is to present to the scientific and management communities a selection of applications using recent Soft Computing (SC) and Computing with Words and Perceptions (CWP) models and techniques meant to solve some economics and financial problems that are of utmost importance. The book starts with a coverage of data mining tools and techniques that may be of use and significance for economic and financial analyses and applications. Notably, fuzzy and natural language based approaches and solutions for a more human consistent dealing with decision support, time series analysis, forecasting, clustering, etc. are discussed. The second part deals with various decision making models, particularly under probabilistic and fuzzy uncertainty, and their applications in solving a wide array of problems including portfolio optimization, option pricing, financial engineering, risk analysis etc. The selected examples could also serve as a starting point or as an opening out, in the SC and CWP techniques application to a wider range of problems in economics and finance.
Economics --- Finance --- Data mining --- Information storage and retrieval systems --- Exploration de données (Informatique) --- Systèmes d'information --- Decision making --- Data processing --- Economic aspects --- Aspect économique --- Finances --- Data mining. --- Economics -- Decision making -- Data processing. --- Finance -- Decision making -- Data processing. --- Information storage and retrieval systems -- Economic aspects. --- Information storage and retrieval systems -- Finance. --- Civil Engineering --- Economic Theory --- Applied Mathematics --- Engineering & Applied Sciences --- Business & Economics --- Civil & Environmental Engineering --- Data processing. --- Economic aspects. --- Finance. --- Automatic data storage --- Automatic information retrieval --- Automation in documentation --- Computer-based information systems --- Data processing systems --- Data storage and retrieval systems --- Discovery systems, Information --- Information discovery systems --- Information processing systems --- Information retrieval systems --- Machine data storage and retrieval --- Mechanized information storage and retrieval systems --- Algorithmic knowledge discovery --- Factual data analysis --- KDD (Information retrieval) --- Knowledge discovery in data --- Knowledge discovery in databases --- Mining, Data --- Funding --- Funds --- Economic theory --- Political economy --- Engineering. --- Artificial intelligence. --- Applied mathematics. --- Engineering mathematics. --- Appl.Mathematics/Computational Methods of Engineering. --- Artificial Intelligence (incl. Robotics). --- Engineering --- Engineering analysis --- Mathematical analysis --- AI (Artificial intelligence) --- Artificial thinking --- Electronic brains --- Intellectronics --- Intelligence, Artificial --- Intelligent machines --- Machine intelligence --- Thinking, Artificial --- Bionics --- Cognitive science --- Digital computer simulation --- Electronic data processing --- Logic machines --- Machine theory --- Self-organizing systems --- Simulation methods --- Fifth generation computers --- Neural computers --- Construction --- Industrial arts --- Technology --- Mathematics --- Computer systems --- Electronic information resources --- Data libraries --- Digital libraries --- Information organization --- Information retrieval --- Database searching --- Currency question --- Social sciences --- Economic man --- Mathematical and Computational Engineering. --- Artificial Intelligence. --- Data centers
Listing 1 - 5 of 5 |
Sort by
|