Fuzhong Nian

Bio: Fuzhong Nian is an academic researcher from Lanzhou University of Technology. The author has contributed to research in topics: Computer science & Synchronization (computer science). The author has an hindex of 12, co-authored 52 publications receiving 614 citations. Previous affiliations of Fuzhong Nian include Dalian University of Technology & Tsinghua University.

An Adaptive Particle Swarm Optimization Algorithm Based on Directed Weighted Complex Network

Abstract: The disadvantages of particle swarm optimization (PSO) algorithm are that it is easy to fall into local optimum in high-dimensional space and has a low convergence rate in the iterative process. To deal with these problems, an adaptive particle swarm optimization algorithm based on directed weighted complex network (DWCNPSO) is proposed. Particles can be scattered uniformly over the search space by using the topology of small-world network to initialize the particles position. At the same time, an evolutionary mechanism of the directed dynamic network is employed to make the particles evolve into the scale-free network when the in-degree obeys power-law distribution. In the proposed method, not only the diversity of the algorithm was improved, but also particles’ falling into local optimum was avoided. The simulation results indicate that the proposed algorithm can effectively avoid the premature convergence problem. Compared with other algorithms, the convergence rate is faster.

Sliding mode synchronization of fractional-order complex chaotic system with parametric and external disturbances

Abstract: In this paper, the synchronization of two fractional-order complex chaotic systems with unknown parameters and external disturbances are studied Based on the Lyapunov stability theory and fractional-order integral sliding surface, a novel active sliding mode controller is proposed to synchronize fractional-order complex chaotic systems Moreover, the controller is robust to unknown parameters and external disturbances Numerical simulations are implemented Results indicate the proposed control strategy is robust and effective

Computer vision : a modern approach = 计算机视觉 : 一种现代的方法

Abstract: From the Publisher: The accessible presentation of this book gives both a general view of the entire computer vision enterprise and also offers sufficient detail to be able to build useful applications. Users learn techniques that have proven to be useful by first-hand experience and a wide range of mathematical methods. A CD-ROM with every copy of the text contains source code for programming practice, color images, and illustrative movies. Comprehensive and up-to-date, this book includes essential topics that either reflect practical significance or are of theoretical importance. Topics are discussed in substantial and increasing depth. Application surveys describe numerous important application areas such as image based rendering and digital libraries. Many important algorithms broken down and illustrated in pseudo code. Appropriate for use by engineers as a comprehensive reference to the computer vision enterprise.

Epidemic processes in complex networks

Abstract: Complex networks arise in a wide range of biological and sociotechnical systems. Epidemic spreading is central to our understanding of dynamical processes in complex networks, and is of interest to physicists, mathematicians, epidemiologists, and computer and social scientists. This review presents the main results and paradigmatic models in infectious disease modeling and generalized social contagion processes.

Interactome networks and human disease

Abstract: Complex biological systems and cellular networks may underlie most genotype to phenotype relationships. Here, we review basic concepts in network biology, discussing different types of interactome networks and the insights that can come from analyzing them. We elaborate on why interactome networks are important to consider in biology, how they can be mapped and integrated with each other, what global properties are starting to emerge from interactome network models, and how these properties may relate to human disease.