通讯机构：
[Xu, Piao-Rong] C;Cent South Univ Forestry & Technol, Coll Comp & Informat Engn, Changsha 410004, Hunan, Peoples R China.
关键词：
The European Physical Journal Applied Physics;journal;EPJ;EDP Sciences
摘要：
A numerical model of carrier saturation velocity and drain current for the monolayer graphene field effect transistors (GFETs) is proposed by considering the exponential distribution of potential fluctuations in disordered graphene system. The carrier saturation velocity of GFET is investigated by the two-region model, and it is found to be affected not only by the carrier density, but also by the graphene disorder. The numerical solutions of the carrier density and carrier saturation velocity in the disordered GFETs yield clear and physical-based results. The simulated results of the drain current model show good consistency with the reported experimental data.
作者机构：
[左志远; 谭建灿; 毛克彪] Institute of Agricultural Resources and Regional Planning, Chinese Academy of Agricultural Science, Beijing, 100081, China;[赵天杰] State Key Laboratory of Remote Sensing Science, Institute of Remote Sensing and Digital Earth Research, Chinese Academy of Sciences, Beijing, 100101, China;[谭雪兰] College of Resources and Environment, Hunan Agricultural University, Changsha, 410128, China;[李建军] College of Computer Science and Information Technology, Central South University of Forestry and Technology, Changsha, 410004, China
通讯机构：
[Mao, K.] I;Institute of Agricultural Resources and Regional Planning, China
作者机构：
[付秀丽] Information Engineering Institute, Beijing Institute of Petrochemical Technology, Beijing, 102617, China;[左志远] National Hulunber Grassland Ecosystem Observation and Research Station, Institute of Agricultural Resources and Regional Planning, Chinese Academy of Agricultural Sciences, Beijing, 100081, China;College of Information Science & Technology, Beijing University of Chemical Technology, Beijing, 100029, China;[谭雪兰] College of Resources & Environment, Hunan Agricultural University, Changsha, 410128, China;[李建军] College of Computer Science and Information Technology, Central South University of Forestry and Technology, Changsha, 410004, China
通讯机构：
[Mao, K.] N;National Hulunber Grassland Ecosystem Observation and Research Station, China
摘要：
It is hard to program a traditional forest sub-compartment management with a long programming cycle and high energy input and lack of computer technology support, such, this paper presents a visualization technology of the sub-compartment management procedure based on WF. The paper, with the programming theory of forest sub-compartment management and WF technology, abstracted traditional sub-compartment management as management measures modules(TABLE II) and implemented the sub-compartment management procedures of custom design(FIGURE II) and used MOGRE 3D Render Engine to display the results at last. The test data was from the pure forest sub-compartment of Chinese fir in Youxian Huangfengqiao forest farm, Hunan Province. The result shows the 3D scene of sub-compartment and the structure factors before and after the operation(FIGURE V and FIGURE VI), which has the intelligent and visual characteristics. In this way, it can realize the effective detection for management procedure, which sets a foundation for the future intelligent forest management schemes in forest farm level.
摘要：
As a representative method of swarm intelligence, Particle Swarm Optimization (PSO) is an algorithm for searching the global optimum in the complex space through cooperation and competition among the individuals in a population of particle. But the basic PSO has some demerits, such as relapsing into local optimum solution, slowing convergence velocity in the late evolutionary. To solve those problems, an particle swarm optimization with comprehensive learning & self-adaptive mutation(MLAMPSO) was proposed. The improved algorithm made adaptive mutation on population of particles in the iteration process, at the same time, the weight and learning factors were updated adaptively. It could enhance the ability of PSO to jump out of local optimal solution. The experiment results of some classic benchmark functions show that the improved PSO obviously improves the global search ability and can effectively avoid the problem of premature convergence.
摘要：
In this paper, a novel approach for initializing clustering centers of K-Means algorithm is presented.This method is based on the variance of dimension, which is used as keyword to make a full permutation.The results of the full permutation for the primary and secondary sequence of keyword is divided into k subsets to initialize the clustering centers.Four international datesets are used for testing datasets to test the effectiveness of this algorithm.And this algorithm is examined by numerical simulation.Experiments suggest that the initial clustering centers chosen by the optimization method proposed in this paper are very close to the clustering centers of ultimate convergence after clustering iteration.Compared with the traditional K-Means clustering algorithm, this algorithm increase the rationality of algorithm on the initial clustering center selection and improve the accuracy of clustering results, and the clustering results is more stable as well.
作者机构：
[刘素芝; 何小东] College of Computer and Information Engineering, Central South University of Forestry and Technology, Changsha 410004, China;Institute of Forest Resource Information Techniques, China Academy of Forestry, Beijing 100091, China;[李建军] College of Computer and Information Engineering, Central South University of Forestry and Technology, Changsha 410004, China, Institute of Forest Resource Information Techniques, China Academy of Forestry, Beijing 100091, China
通讯机构：
[Li, J.-J.] C;College of Computer and Information Engineering, Central South University of Forestry and Technology, Changsha 410004, China
