Inductive Learning Algorithms for Complex Systems Modeling

1. Introduction: Systems and Cybernetics  2. Inductive Learning Algorithms: Self-Organization Method  3. Network Structures  4. Long Term Quantitative Predictions  5. Dialogue Language Generalization  6. Noise Immunity and Convergence: Analogy with Information Theory  7. Classification and Analysis of Criteria. Improvement of Noise Immunity  8. Asymptotic Properties of Criteria  9. Balance Criterion of Predictions  10. Convergence of Algorithms  11. Physical Fields and Modeling: Finite-Difference Pattern Schemes  12. Comparative Studies  13. Cyclic Processes  14. Clusterization and Recognition: Self-Organization Modeling and Clustering  15. Methods of Self-Organization Clustering  16. Objective Computer Clustering Algorithm  17. Levels of Discretization and Balance Criterion  18. Forecasting Methods of Analogues  19. Applications: Fields of Application  20. Weather Modeling  21. Ecological System Studies  22. Modeling of Economical Systems  23. Agricultural System Studies  24. Modeling of Solar Activity  25. Inductive and Deductive Networks: Self-Organization Mechanism in the Networks  26. Network Techniques  27. Generalization  28. Comparison and Simulation Results  29. Basic Algorithms and Program Listings: Computational Aspects of Multilayered Algorithm  30. Computational Aspects of Combinatorial Algorithm  31. Computational Aspects of Harmonical Algorithm.