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