Modelling of High Complexity Systems with Applications

Chapter 1: An introduction to high complexity systems; Definition; Principles of approaching high complexity systems; Chapter 2: Structure of high complexity systems; System dimension; System complexity; System non-linearity; Uncertainty in a high complexity system; Chapter 3: The principle of uncertainty in high complexity systems; Definition of uncertainty; Statement of the principle of uncertainty; Mathematical formalism of the principle of uncertainty. Evaluation theorem of uncertainty; The concrete form of uncertainties; Application of the principle of uncertainty; Chapter 4: Simulation models; Numerical simulation models; Knowledge-based simulation models; Mathematical-heuristic simulation and control models; A methodology of simulation models; Chapter 5: Knowledge base for modelling and simulation; Sequential logic and dynamic logic; Knowledge representation; Structure of the knowledge base; Knowledge acquisition; Chapter 6: Mathematical-heuristic modelling; Methodology for mathematical-heuristic model development; Compatibility between the mathematical model and the heuristic knowledge-based and/or fuzzy one. Theorems of compatibility; Application: a models library for simulation and control in ecology and environmental protection; Concluding remarks; Chapter 7: Stability of high complexity systems; Introduction; Mathematical-heuristic model for stability analysis and evaluation; Stability of control systems, described by mathematical-heuristic models; Case study; Concluding remarks; Chapter 8: Risk analysis and assessment in high complexity systems; Introduction; The mathematical-heuristic model of risk analysis and assessment; Risk assessment in high complexity systems; Case study; Chapter 9: Simulation of high complexity systems; Introduction; Simulation using knowledge processing; Simulation of systems using a mathematical-heuristic model; Case study; Chapter 10: Control of high complexity systems; Introduction; Control knowledge base; Knowledge-based control system; Fuzzy knowledge processing-based control system; Case study; Concluding remarks; Chapter 11: Application of high complexity systems to modelling of industrial systems; Introduction; Mathematical-heuristic simulation and control model of a discrete-time industrial process; Chapter 12: Application of high complexity systems to the modelling of power systems; Preliminary remarks; Mathematical-heuristic model for simulation and control of an electrical energy distribution system; Chapter 13: Application of high complexity systems to the modelling of macroeconomic systems; Introduction; Mathematical-heuristic model for a macroeconomic system; Concluding remarks; Chapter 14: Application of high complexity systems to the modelling of aquatic ecosystems; Mathematical-heuristic model of a river delta ecosystem; Mathematical-heuristic model for the seaside ecosystem; Chapter 15: Application of high complexity systems to the modelling of terrestrial ecosystems; Simulation and control model for the soil system; Simulation and control model for an agro-ecosystem; Simulation and control model for a forest ecosystem; Chapter 16: Application of high complexity systems to the modelling of industrial chemical pollutants diffusion in urban atmosphere; Introduction; Mathematical-heuristic model for industrial chemical pollutants diffusion in urban atmosphere; Concluding remarks; Chapter 17: Facilities for the operation of mathematical-heuristic models; Models Library; Microsoft Access databases; SQL_Server database; Web Portals for modelling and simulation and search engine; Chapter 18: Remarks on the mathematical-heuristic model in simulation and control of high complexity systems; General remarks on the mathematical-heuristic model; System complexity and the mathematical-heuristic model; System exergy and the mathematical-heuristic model