complex systems 
These laws do not reflect the real microdynamics contained in the time series of dynamical variables measured to analyze the evolution of complex systems.


With everincreasing attentions being paid to complex systems such as the life system, soft matter, and nanosystems, theoretical studies of nonequilibrium nonlinear problems involved in chemical dynamics are now of general interest.


Both HACdS and HBCdS (HysCdS, Hys represents HA, HB) complex systems were established according to the dynamics of heterogeneous electrontransfer process.


By the moment method not only the regular boundary condition problem of electromagnetic field can be solved, but also some electromagnetic fields in complex systems may be solved.


Keith Sawyer: Social Emergence: Societies as Complex Systems


A neural network method for reliability optimizations of complex systems


With the growing incorporation of nanomaterials into multiphase industrial processes and consumer products, methods for predicting their behavior in complex systems are in increasing demand.


Thus, application to complex systems, like a many redundant d.o.f.


To develop an explicit dynamics model of such complex systems, the Lagrangian formulation is applied.


The obtained dynamics model is very useful for dynamics analyses, design and development of control algorithms for such complex systems.


Complex systems of paramagnetic centres existing in demineralised flame coal (71.4 wt% C), mediumrank coal (85.6 wt% C) and anthracite (94.9 wt% C) were analysed by electron paramagnetic resonance spectroscopy (EPR).


Nontrivial mixture of longrange correlations and noise is one of the characteristic features of the dynamics of complex systems.


A gametheoretic model of solving the problem of diagnosing complex systems was proposed enabling us to estimate the costs related to the system malfunction depending on the number of realizations of the diagnostics algorithm.


The basic task of work is to research possibility of using the neural networks as a metamodels for three complex systems: dispatching system (planning system of transport routes), multicommodity network and bank system with several cash registers.


A prediction control algorithm is presented based on least squares support vector machines (LSSVM) model for a class of complex systems with strong nonlinearity.


The science of complexity studies the behavior and properties of complex systems in nature and human society.


Symmetric phenomena can be found in many complex systems.


Power plants are nonlinear and uncertain complex systems.


Although highly simplified in form, the formula is convenient for practical computations on complex systems whose exact dynamics would be essentially impossible to obtain.


Analysis of EXAFS data of complex systems containing more than one phase and one type of coordination, has been discussed.

