It integrates probability theory and graph theory, it can perfectly quantizing uncertainty generally in complex system and can provide more precise result based on its probability inference, in the same time the system model based on Bayesian Networks has more intelligence.

This control system can be used for a controlled object which lacks an accurate mathematical model or for a complex system which is difficult to analyze and control with the existing control method because of time-delay and nonlinearity.

The model is suitable for fuzzy prediction and control of complex system because the recognition method of fuzzy module parameters based on the theory of neural network is adopted.

Nowadays, maintenance model is transferring from plan maintenance to condition based maintenance step by step. Since hydropower generator unit is a very complicated system that involving hydraulic, electrical and mechanical factors, such as the fault mechanism, diagnosis methods, data channel, evaluation principle of life and maintenance decision supporting system are not fully researched.

The dispersion of dynamic frequency in complicated system is one of reasons which lead the unsatisfactory performance of under frequency load shedding device.

The power system is a nonlinear complicated system, which is usually affected by many factors in the same time. The whole system’s response will be more intricate and difficult to predict after the deregulation process because the market related stochastic factors will add their influences to the operation manners of the power system.

It integrates probability theory and graph theory, it can perfectly quantizing uncertainty generally in complex system and can provide more precise result based on its probability inference, in the same time the system model based on Bayesian Networks has more intelligence.

This control system can be used for a controlled object which lacks an accurate mathematical model or for a complex system which is difficult to analyze and control with the existing control method because of time-delay and nonlinearity.

The model is suitable for fuzzy prediction and control of complex system because the recognition method of fuzzy module parameters based on the theory of neural network is adopted.

2) Considering power system is a hybrid system in nature and operates in a hierarchical mode, hybrid power system model based on Controlled General Hybrid Dynamical Systems (CGHDS) and multilayer diagnosis system based on multiagent are established.

The disquisition on qualifying subsystem demonstrates its theory basis and feasibility,and solves many problems of qualifying complex measuring system.

The feature of DGIS is huge amount of space and information data, complicated function of management and query, the requirement of system openness and the tight combination with DMS and SCADA, etc.

Decentralized adaptive robust controller design for complex system based on partition of unity

Based on the computational simulation with the vacuum environment for the fish-type-II antifreeze proteinice-solvent (water) system, the multi-complex system of the antifreeze protein-ice-water has been constructed and calculated.

The software systems with complex system characteristics are developing into the "Networked Software" with characteristics of change-on-demand and change-with-cooperation.

The core issue of software engineering is moving to the requirement engineering, which becomes the research focus of complex system software engineering.

This paper introduces the causes of global warming and summarizes its results, which both involve a series of huge and complex system issues.

The three-dimensional zone of detachment thus formed deflects the incident flow from the wall, and in front of the jet a complicated system of sharp jumps in contraction develops.

Together with the Poisson equation for electric potential, the derived relationships make a complicated system of differential equations.

We also find that a pair quadrupole defect, which has a complicated system of levels, can be replaced by an effective two-level system with temperature-dependent parameters.

Complicated system dynamics, namely transitions from regular to chaotic oscillations in response to changing the system parameters, is revealed.

To address the problems that input variables should be reduced as much as possible and explain output variables fully in building neural network model of complicated system, a variable selection method based on cluster analysis was investigated.

The prin ciples of Robust Design allow design teams to handle complex sys tem integration issues with repeatable processes.

In this paper a power system equivalent model is presented for power system transient stability studies.The original sub-system to be simplified is replaced by an equivalent machine and a simple fixed configuration network,. The values of the internal e.m.f. and the inertia time constant of the equivalent machine are each obtained from the weighted mean of those of the original subsystem machines, while the equivalent network configuration and its parameters are determined from the number of the terminal points...

In this paper a power system equivalent model is presented for power system transient stability studies.The original sub-system to be simplified is replaced by an equivalent machine and a simple fixed configuration network,. The values of the internal e.m.f. and the inertia time constant of the equivalent machine are each obtained from the weighted mean of those of the original subsystem machines, while the equivalent network configuration and its parameters are determined from the number of the terminal points and the electrical boundary conditions of the original sub-system network. In this way both steady-state and dynamic equivalent conditions are satisfied.It has been shown by simulation results that the dynamic behaviour of the simplified power system is nearly identical with the original. T his net hod will significantly reduce the computer storage and time requirments for large power system transient stability studies.

A new approach called AP method of predicting complex system Reliability is proposed in lhis paper. It requires no logic diagrams and state enumerations, is not only simple in mathematical modeling and calculating, but also superior in adaptability and accuracy, therefore is quite an ideal method for reliability prediction of complex systems.

In order to completely consider the affects of various subjective and objective factors in multi-dimensinal decision-making problem such as the optimal selection of river serial developing schemes, so that optimal decision which is economical, rational and having optimal comprehensive indices is obtained. On the basis of the actual characteristics of river serial development, this paper applies multiple-order contrast coefficient comprehensive evaluation model to the optimal selection of river serial developing...

In order to completely consider the affects of various subjective and objective factors in multi-dimensinal decision-making problem such as the optimal selection of river serial developing schemes, so that optimal decision which is economical, rational and having optimal comprehensive indices is obtained. On the basis of the actual characteristics of river serial development, this paper applies multiple-order contrast coefficient comprehensive evaluation model to the optimal selection of river serial developing schemes, gives a real example and gains a good result. The result shows that the model tallies with the actual situation and can consider the various sides of the problem. At the same time, we can easily evaluate the other complicated systems by using the model above.