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eBay item number:306369676693
Item specifics
- Condition
- Country of Origin
- United States
- Book Title
- Inductive Learning Algorithms for Complex Systems Modeling
- Educational Level
- Adult & Further Education
- Personalized
- No
- Features
- 1st Edition, Illustrated
- ISBN
- 9780849344381
- Subject Area
- Mathematics, Computers
- Publication Name
- Inductive Learning Algorithms for Complex Systems Modeling
- Publisher
- CRC Press LLC
- Item Length
- 10 in
- Subject
- Programming / Algorithms, General, Applied
- Publication Year
- 1993
- Type
- Textbook
- Format
- Hardcover
- Language
- English
- Item Weight
- 32.1 Oz
- Item Width
- 7 in
- Number of Pages
- 384 Pages
About this product
Product Identifiers
Publisher
CRC Press LLC
ISBN-10
0849344387
ISBN-13
9780849344381
eBay Product ID (ePID)
528726
Product Key Features
Number of Pages
384 Pages
Language
English
Publication Name
Inductive Learning Algorithms for Complex Systems Modeling
Publication Year
1993
Subject
Programming / Algorithms, General, Applied
Type
Textbook
Subject Area
Mathematics, Computers
Format
Hardcover
Dimensions
Item Weight
32.1 Oz
Item Length
10 in
Item Width
7 in
Additional Product Features
Intended Audience
Scholarly & Professional
LCCN
93-024174
Illustrated
Yes
Table Of Content
Introduction: Systems and Cybernetics. Inductive Learning Algorithms: Self-Organization Method. Network Structures. Long Term Quantitative Predictions. Dialogue Language Generalization. Noise Immunity and Convergence: Analogy with Information Theory. Classification and Analysis of Criteria. Improvement of Noise Immunity. Asymptotic Properties of Criteria. Balance Criterion of Predictions. Convergence of Algorithms. Physical Fields and Modeling: Finite-Difference Pattern Schemes. Comparative Studies. Cyclic Processes. Clusterization and Recognition: Self-Organization Modeling and Clustering. Methods of Self-Organization Clustering. Objective Computer Clustering Algorithm. Levels of Discretization and Balance Criterion. Forecasting Methods of Analogues. Applications: Fields of Application. Weather Modeling. Ecological System Studies. Modeling of Economical Systems. Agricultural System Studies. Modeling of Solar Activity. Inductive and Deductive Networks: Self-Organization Mechanism in the Networks. Network Techniques. Generalization. Comparison and Simulation Results. Basic Algorithms and Program Listings: Computational Aspects of Multilayered Algorithm. Computational Aspects of Combinatorial Algorithm. Computational Aspects of Harmonical Algorithm.
Synopsis
Inductive Learning Algorithms for Complex Systems Modeling is a professional monograph that surveys new types of learning algorithms for modeling complex scientific systems in science and engineering. The book features discussions of algorithm development, structure, and behavior; comprehensive coverage of all types of algorithms useful for this subject; and applications of various modeling activities (e.g., environmental systems, noise immunity, economic systems, clusterization, and neural networks). It presents recent studies on clusterization and recognition problems, and it includes listings of algorithms in FORTRAN that can be run directly on IBM-compatible PCs. Inductive Learning Algorithms for Complex Systems Modeling will be a valuable reference for graduate students, research workers, and scientists in applied mathematics, statistics, computer science, and systems science disciplines. The book will also benefit engineers and scientists from applied fields such as environmental studies, oceanographic modeling, weather forecasting, air and water pollution studies, economics, hydrology, agriculture, fisheries, and time series evaluations.
LC Classification Number
T57.6.M313 1994
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