2015 Sixth International Conference on Intelligent Control and Information Processing (ICICIP)最新文献_第10页

On delay-dependent exponential stability of the split-step backward euler method for stochastic delay differential equations 随机时滞微分方程的分步倒推欧拉方法的时滞相关指数稳定性

2015 Sixth International Conference on Intelligent Control and Information Processing (ICICIP) Pub Date : 2015-11-01 DOI: 10.1109/ICICIP.2015.7388155

Xiaomei Qu

引用次数: 2

Compressive tracking based on random channel haar-like feature 基于随机信道haar特征的压缩跟踪

2015 Sixth International Conference on Intelligent Control and Information Processing (ICICIP) Pub Date : 2015-11-01 DOI: 10.1109/ICICIP.2015.7388160

Junyan Chen, Y. Liu, Na Li, Zhiquan Guo

引用次数: 1

The stationary distribution and extinction of the n-dimensional stochastic Lotka-Volterra predator-prey system n维随机Lotka-Volterra捕食-食饵系统的平稳分布与灭绝

2015 Sixth International Conference on Intelligent Control and Information Processing (ICICIP) Pub Date : 2015-11-01 DOI: 10.1109/ICICIP.2015.7388144

Xiaoyan Yu, Lei Liu

引用次数: 0

Rich feature hierarchies for cell detecting under phase contrast microscopy images 相衬显微镜图像下细胞检测的丰富特征层次

2015 Sixth International Conference on Intelligent Control and Information Processing (ICICIP) Pub Date : 2015-11-01 DOI: 10.1109/ICICIP.2015.7388195

Fan Deng, Haigen Hu, Shengyong Chen, Q. Guan, Yijie Zou

引用次数: 3

Research and simulation analysis of control strategies for the large-scale grid-connected photovoltaic system 大型光伏并网系统控制策略的研究与仿真分析

2015 Sixth International Conference on Intelligent Control and Information Processing (ICICIP) Pub Date : 2015-11-01 DOI: 10.1109/ICICIP.2015.7388163

Dan Xu, Chen Du, Enyan Xie

{"title":"Research and simulation analysis of control strategies for the large-scale grid-connected photovoltaic system","authors":"Dan Xu, Chen Du, Enyan Xie","doi":"10.1109/ICICIP.2015.7388163","DOIUrl":"https://doi.org/10.1109/ICICIP.2015.7388163","url":null,"abstract":"With the continuous development of new energy technologies, solar photovoltaic(PV) plays an increasingly important role in modern society. There is still no workable technology research and project implementation plan for PV power grid control about the problem of large-scale PV grid. First of all, the paper analyzed the basic principle of the solar cell power generation and introduced the equivalent circuit model of solar cell. The solar cell is a nonlinear power supply. Environmental temperature and light intensity have an important effect on its output power. To make the solar cell convert solar energy into electrical energy most efficiently, it needs to be maximum power point tracked(MPPT). Secondly, the paper studied on the control strategy for photovoltaic grid power generation system and established grid model with photovoltaic power plants, including a system circuit model and the active control model. Then in turn it analyzed automatic generation control(AGC) response of the system under the power fluctuations of new energy and under off-grid PV power plant emergency situations, the effect of photovoltaic active control mode on the grid frequency modulation(FM), the coordination control simulation of realtime scheduling and AGC. Finally it gave some research conclusions of active control strategy on the side of main station with large-scale photovoltaic grid.","PeriodicalId":265426,"journal":{"name":"2015 Sixth International Conference on Intelligent Control and Information Processing (ICICIP)","volume":"39 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2015-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"129153076","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 3

Fast, finite, accurate and optimal WASD neuronet versus slow, infinite, inaccurate and rough BP neuronet illustrated via russia population prediction 快速，有限，准确和最优的WASD神经网络与缓慢，无限，不准确和粗糙的BP神经网络通过俄罗斯人口预测说明

2015 Sixth International Conference on Intelligent Control and Information Processing (ICICIP) Pub Date : 2015-11-01 DOI: 10.1109/ICICIP.2015.7388158

Jianxi Liu, Yunong Zhang, Zhengli Xiao, Tianjian Qiao, Hongzhou Tan

{"title":"Fast, finite, accurate and optimal WASD neuronet versus slow, infinite, inaccurate and rough BP neuronet illustrated via russia population prediction","authors":"Jianxi Liu, Yunong Zhang, Zhengli Xiao, Tianjian Qiao, Hongzhou Tan","doi":"10.1109/ICICIP.2015.7388158","DOIUrl":"https://doi.org/10.1109/ICICIP.2015.7388158","url":null,"abstract":"Russia population problem attracts great concerns to the future trend of population and the development of the nation. Conventional researches on Russia population prediction are usually based on the standard cohort-component method. Such a method only allows for several factors (fertility, mortality and migration rates), and then leads to the lack of all-sidedness in the prediction results. With outstanding generalization ability, the feedforward neuronet is considered to be a more appropriate substitute. Besides, the back-propagation (BP) is of the most widely-used feedforward neuronet. As the conventional back-propagation neuronet has some inherent weaknesses, in this paper, two types of improved feedforward neuronet are constructed for the Russia population prediction. More specifically, a type of 3-layer power-activated neuronet (PAN) equipped with the BP algorithm (BP-PAN) and a type of 3-layer PAN equipped with the weights-and-structure-determination (WASD) algorithm (WASD-PAN) are built on the basis of 2013-year (from 1AD to 2013AD) historical population data for the Russia population prediction. By a lot of numerical experiments, the future declining trend of Russia population in the next decade is predicted with the highest possibility. In addition, via the Russia population prediction, the comparisons on the performance between the WASD neuronet and BP neuronet are conducted and summarized.","PeriodicalId":265426,"journal":{"name":"2015 Sixth International Conference on Intelligent Control and Information Processing (ICICIP)","volume":"23 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2015-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"121748274","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 1

Control DC bus voltage of active power filter with a novel control 用一种新颖的控制方法控制有源电力滤波器直流母线电压

2015 Sixth International Conference on Intelligent Control and Information Processing (ICICIP) Pub Date : 2015-10-01 DOI: 10.1109/ICINFA.2015.7279456

Chao Wang, X. Zong, Xingong Cheng, Lei Luo

引用次数: 0