检索结果-内蒙古大学图书馆

您好，读者！请登录

内蒙古大学图书馆

首页
概况
党建
资源
服务
科研支持
- 论文收录引用证明
- 科技查新
知识产权
档案馆
帮助

咨询与建议

建议与咨询留下您的常用邮箱和电话号码，以便我们向您反馈解决方案和替代方法

您的常用邮箱：*

您的手机号码：*

问题描述：

当前已输入0个字，您还可以输入200个字

全部搜索
期刊论文
图书
学位论文
标准
纸本馆藏
外文资源发现
数据库导航
超星发现

高级检索

时间限定

出版年份：

文献类型

图书期刊文献学位论文多媒体

馆藏选择

电子馆藏纸本馆藏

核心期刊

全部期刊 SCI 收录期刊 SSCI 收录期刊 EI 收录期刊 CSCD 收录期刊 CSSCI 收录期刊

语言

中文英文

文献类型

期刊文献图书学位论文标准纸本馆藏

帮助

文字说明：

T=题名（书名、题名），A=作者（责任者），K=主题词，P=出版物名称，PU=出版社名称，O=机构（作者单位、学位授予单位、专利申请人），L=中图分类号，C=学科分类号，U=全部字段，Y=年（出版发行年、学位年度、标准发布年）

检索规则说明：

AND代表“并且”；OR代表“或者”；NOT代表“不包含”；(注意必须大写,运算符两边需空一格)

检索范例：

范例一：(K=图书馆学 OR K=情报学) AND A=范并思 AND Y=1982-2016
范例二：P=计算机应用与软件 AND (U=C++ OR U=Basic) NOT K=Visual AND Y=2011-2016

分类表

所选分类

>> <<

限定检索结果

文献类型

163 篇 会议
108 篇 期刊文献

馆藏范围

271 篇 电子文献
0 种 纸本馆藏

日期分布

学科分类号

193 篇 工学
- 150 篇 计算机科学与技术...
- 136 篇 软件工程
- 33 篇 信息与通信工程
- 27 篇 生物医学工程（可授...
- 23 篇 生物工程
- 21 篇 控制科学与工程
- 15 篇 化学工程与技术
- 11 篇 电子科学与技术（可...
- 10 篇 机械工程
- 10 篇 光学工程
- 7 篇 电气工程
- 6 篇 建筑学
- 5 篇 仪器科学与技术
- 5 篇 土木工程
- 4 篇 交通运输工程
- 3 篇 农业工程
127 篇 理学
- 91 篇 数学
- 31 篇 生物学
- 22 篇 统计学（可授理学、...
- 18 篇 物理学
- 16 篇 化学
- 5 篇 系统科学
59 篇 管理学
- 33 篇 图书情报与档案管...
- 30 篇 管理科学与工程(可...
- 10 篇 工商管理
14 篇 医学
- 14 篇 临床医学
- 12 篇 基础医学(可授医学...
- 11 篇 药学(可授医学、理...
9 篇 农学
- 6 篇 作物学
4 篇 法学
- 4 篇 社会学
2 篇 经济学
1 篇 教育学
1 篇 军事学

主题

19 篇 data mining
18 篇 educational inst...
17 篇 computer science
16 篇 knowledge engine...
12 篇 laboratories
11 篇 educational tech...
10 篇 semantics
10 篇 ontology
9 篇 image segmentati...
9 篇 clustering algor...
8 篇 support vector m...
7 篇 genetic algorith...
7 篇 feature extracti...
6 篇 deep learning
6 篇 neural networks
6 篇 computer science...
5 篇 ant colony optim...
5 篇 hidden markov mo...
5 篇 ontologies
5 篇 convolution

机构

63 篇 college of compu...
19 篇 key laboratory o...
15 篇 key laboratory o...
13 篇 key laboratory o...
13 篇 key laboratory o...
12 篇 key laboratory o...
12 篇 key laboratory o...
12 篇 key laboratory o...
11 篇 key laboratory o...
10 篇 college of softw...
10 篇 department of co...
9 篇 key laboratory o...
9 篇 key laboratory f...
9 篇 college of compu...
8 篇 key laboratory o...
6 篇 school of artifi...
6 篇 college of compu...
6 篇 college of compu...
5 篇 institute of hig...
5 篇 key laboratory o...

作者

27 篇 liang yanchun
21 篇 yanchun liang
12 篇 zuo wanli
11 篇 li xiongfei
10 篇 wu chunguo
9 篇 yan wang
8 篇 han xiaosong
8 篇 wang yan
8 篇 li wenhui
8 篇 wanli zuo
8 篇 chunguang zhou
8 篇 liang yan-chun
7 篇 wei du
6 篇 li huiying
6 篇 shi xiaohu
6 篇 jindong zhang
6 篇 xiaosong han
6 篇 zhou you
6 篇 yan-chun liang
6 篇 guo xiaoxin

语言

256 篇 英文
15 篇 中文

检索条件"机构=Open Symbol Computation and Knowledge Engineering Laboratory"

共 271 条记录，以下是221-230 订阅

全选清除本页清除全部题录导出标记到"检索档案"

详细简洁

排序：

Support vector machine regression algorithm based on chunking incremental learning

引用

ICCS 2006: 6th International Conference on computational Science

作者： Jingqing, Jiang Chuyi, Song Chunguo, Wu Maurizio, Marchese Yangchun, Liang Key Laboratory of Symbol Computation and Knowledge Engineering Jilin University Ministry of Education Changchun 130012 China College of Mathematics and Computer Science Inner Mongolia University for Nationalities Tongliao 028043 China Key Laboratory of Information Science and Engineering Beijing Jiaotong University Railway Ministry Beijing 100044 China Italy

ISBN: (纸本)3540343792

On the basis of least squares support vector machine regression (LSSVR), an adaptive and iterative support vector machine regression algorithm based on chunking incremental learning (CISVR) is presented in this paper. CISVR is an iterative algorithm and the samples are added to the working set in batches. The inverse of the matrix of coefficients from previous iteration is used to calculate the regression parameters. Therefore, the proposed approach permits to avoid the calculation of the inverse of a large-scale matrix and improves the learning speed of the algorithm. Support vectors are selected adaptively in the iteration to maintain the sparseness. Experimental results show that the learning speed of CISVR is improved greatly compared with LSSVR for the similar training accuracy. At the same time the number of the support vectors obtained by the presented algorithm is less than that obtained by LSSVR greatly. © Springer-Verlag Berlin Heidelberg 2006.

关键词： Learning systems

来源：评论

学校读者我要写书评

暂无评论

Identification of Transcription Factor Binding Sites Using GA and PSO

Identification of Transcription Factor Binding Sites Using G...

引用

International Conference on Intelligent Systems Design and Applications (ISDA)

作者： Xiao-yu Chang Chun-guang Zhou Yan-wen Li Ping Hu College of Computer Science Key Laboratory of Symbol Computation and Knowledge Engineering of the Ministry of Education Jilin University China College of Computer Science Key Laboratory of Symbol Computation and Knowledge Engineering of the Ministry of Education department of computer science Northeast Normal University Changchun China

Identification of transcription factor binding sites from the upstream regions of genes is a highly important and unsolved problem. In this paper, we propose a novel framework for using evolutionary algorithm to solve this challenging issue. Under this framework, we use two prevalent evolutionary algorithms: genetic algorithm (GA) and particle swarm optimization (PSO) to find unknown sites in a collection of relatively long intergenic sequences that are suspected of being bound by the same factor. This paper represents binding sites motif to position weight matrix (PWM) and introduces how to code PWM to genome for GA and how to code it to particle for PSO. We apply these two algorithms to 5 different yeast saccharomyces cerevisiae transcription factor binding sites and CRP binding sites. The results on saccharomyces cerevisiae show that it can find the correct binding sites motifs, and the result on CRP shows that these two algorithms can achieve more accuracy than MEME and Gibbs sampler

关键词： Evolutionary computation Pulse width modulation Genomics Bioinformatics Genetic algorithms Particle swarm optimization Biology computing Evolution (biology) Educational institutions Computer science

来源：评论

学校读者我要写书评

暂无评论

Combining Greedy Method and Genetic Algorithm to Identify Transcription Factor Binding Sites

Combining Greedy Method and Genetic Algorithm to Identify Tr...

引用

International Conference on Hybrid Intelligent Systems (HIS)

作者： Wanyu Wang Xiaoyu Chang Chunguang Zhou College of Computer Science Key Laboratory of Symbol Computation and Knowledge Engineering of the Ministry of Education Jilin University Changchun China

Identification of Transcription Factor Binding Sites (TFBS) from the upstream region of genes remains a highly important and unsolved problem particularly in higher eukaryotic genomes. In this paper, we propose a novel approach to identify transcription factor binding sites. This approach combines greedy method and genetic algorithm (CGGA) to search conserved segment in the given sequence set. A new greedy method which can efficiently search a local optimal result is proposed. In order to solve the high complexity of this algorithm, we also give an effective improvement for this method. Then, we describe how to combine genetic algorithm with this greedy method to find the more optimal results. Greedy method is combined to the fitness function of the genetic algorithm. We apply this approach on two different TFBS sets and the results show that it can find correct result both effective and efficient, and for CRP binding sites, it get a more accurate result than Gibbs Sampler, AlignACE and MDGA.

关键词：

来源：评论

学校读者我要写书评

暂无评论

Prediction of Transcription Factor Binding Sites Using Genetic Algorithm

Prediction of Transcription Factor Binding Sites Using Genet...

引用

IEEE Conference on Industrial Electronics and Applications (ICIEA)

作者： Xiaoyu Chang Wengang Zhou Chunguang Zhou Yanchun Liang College of Computer Science and Technology Key Laboratory of Symbol Computation and Knowledge Engineering of the Ministry of Education Jilin University Changchun China

Identification of transcription factor binding sites (TFBS) from the upstream region of genes remains a highly important and unsolved problem particularly in higher eukaryotic genomes. In this paper, we propose a new approach to predict TFBS. This approach uses position weight matrix (PWM) to represent binding sites and uses genetic algorithm (GA) to search the best matrix. A new coding method so called multiple-variable coding is proposed in GA. We apply it on two transcription factors rebl and mgl. The result shows that this approach can find most of the known sites, which indicates that this method is very effective

关键词： Genetic algorithms Pulse width modulation Sequences Genomics Bioinformatics Hidden Markov models Proteins Computer science Educational technology knowledge engineering

来源：评论

学校读者我要写书评

暂无评论

Fuzzy kernel clustering based on particle swarm optimization

Fuzzy kernel clustering based on particle swarm optimization

引用

IEEE International Conference on Granular Computing (GRC)

作者： Libiao Zhang Chunguang Zhou Ming Ma Xiaohua Liu Chunxia Li Caitang Sun Miao Liu College of Computer Science and Technology Key Laboratory for Symbol Computation and Knowledge Engineering of the National Education Ministry of China Jilin University Changchun China

来源：评论

学校读者我要写书评

暂无评论

Intelligent Sub-Object Image Retrieval System

Intelligent Sub-Object Image Retrieval System

引用

World Congress on Intelligent Control and Automation (WCICA)

作者： Wenhui Li Dongfeng Han Yi Wang Xiaosuo Lu Key Laboratory of Symbol Computation and Knowledge Engineering of the Ministry of Education College of Computer Science&Technology Jilin University Changchun Jilin China

This paper describes a sub-object retrieval system based on a segmentation method. We also use dynamic partial function (DPF) and indexing by locality sensitive hashing (LSH) for improving system performance. Such a system is useful for finding a sub-object from a large image database. In order to obtain the sub-object from a sample image, we use a segmentation method to cut out the object. The system utilizes the segmentation results to capture the higher-level concept of images and gets a stable and accurate result. Experimental and comparison results, which are performed using a general purpose database containing 20,000 images, are encouraging

关键词： Image retrieval Image segmentation Image databases Vehicle dynamics Indexing Information retrieval Content based retrieval Spatial databases Humans Laboratories

来源：评论

学校读者我要写书评

暂无评论

Mutual conversion of regression and classification based on least squares support vector machines

Mutual conversion of regression and classification based on ...

引用

3rd International Symposium on Neural Networks, ISNN 2006 - Advances in Neural Networks

作者： Jiang, Jing-Qing Song, Chu-Yi Wu, Chun-Guo Liang, Yang-Chun Yang, Xiao-Wei Hao, Zhi-Feng Key Laboratory of Symbol Computation and Knowledge Engineering Jilin University Ministry of Education Changchun 130012 China College of Mathematics and Computer Science Inner Mongolia University for Nationalities Tongliao 028043 China Key Laboratory of Information Science and Engineering Beijing Jiaotong University Railway Ministry Beijing 100044 China School of Mathematical Science South China University of Technology Guangzhou 510640 China

ISBN: (纸本)354034439X

Classification and regression are most interesting problems in the fields of pattern recognition. The regression problem can be changed into binary classification problem and least squares support vector machine can be used to solve the classification problem. The optimal hyperplane is the regression function. In this paper, a one-step method is presented to deal with the multi-category problem. The proposed method converts the problem of classification into the function regression problem and is applied to solve the converted problem by least squares support vector machines. The novel method classifies the samples in all categories simultaneously only by solving a set of linear equations. Demonstrations of numerical experiments are performed and good performances are obtained. Simulation results show that the regression and classification can be converted each other based on least squares support vector machines. © Springer-Verlag Berlin Heidelberg 2006.

关键词： Learning systems

来源：评论

学校读者我要写书评

暂无评论

Fast Kernel for Calculating Structural Information Similarities

Fast Kernel for Calculating Structural Information Similarit...

引用

International IEEE Conference on Intelligent Systems, IS

作者： Jin-Mao Wei Shu-Qin Wang Jing Wang Jun-Ping You Institute of Computational Intelligence Northeast Normal University China Open Symbol Computation and Knowledge Engineering Laboratory of State Education Jilin University Changchun Jilin China School of Mathematics & Statistics Northeast Normal University Changchun Jilin China

Structural similarity computation plays a crucial role in many applications such as in searching similar documents, in comparing chemical compounds, in finding genetic similarities, etc. We propose in this paper to use structural information content (SIC) for measuring structural information, considering both the nodes and edges of trees. We utilize a binary encoding approach for assigning the weights of different layer nodes and determining if some tree is a subtree of another tree. By defining a fast kernel and recursively computing SICs, we evaluate the structural information similarities of data trees to pattern trees. In the paper, we present the algorithm for calculating SICs with computation complexity of O(n), and use simple examples to instantiate the performance of the proposed method

关键词： Kernel Chemical compounds Silicon carbide XML Genetics Encoding Clustering algorithms Intelligent systems Intelligent structures Pattern analysis

来源：评论

学校读者我要写书评

暂无评论

A hybrid discrete particle swarm algorithm for open-shop problems

引用

6th International Conference Simulated Evolution and Learning, SEAL 2006

作者： Qingyun, Yang Jigui, Sun Juyang, Zhang Chunjie, Wang College of Computer Science and Technology Jilin University Changchun 130012 China Key Laboratory for Symbolic Computation and Knowledge Engineering of Ministry of Education Jilin University Changchun 130012 China Open Laboratory for Intelligence Information Processing Fudan University Shanghai 200433 China Basic Sciences of ChangChun University of Technology ChangChun University of Technology Changchun 130012 China

ISBN: (纸本)3540473319

A hybrid discrete particle swarm algorithm is presented in this paper to solve open-shop problems. The operations are redefined in the discrete particle swarm algorithm. To improve the performance the simulated annealing algorithm is combined with discrete particle swarm. We use SA to enhance the results of local best positions instead of current positions. The experimental results show that our hybrid discrete particle swarm algorithm is effective and efficient to solve open-shop problems. © Springer-Verlag Berlin Heidelberg 2006.

关键词： open systems

来源：评论

学校读者我要写书评

暂无评论

An Efficient Method for Very Large Scale Out-of-Core Terrain Visualization

An Efficient Method for Very Large Scale Out-of-Core Terrain...

引用

International Conference on Artificial Reality and Telexistence (ICAT)

作者： Huijie Zhang Jigui Sun Haihong Yu Changsong Qi College of Computer Science Northeast Normal University China College of Computer Science and Technology Jilin University China Key Laboratory of Symbol Computation and Knowledge Engineering Ministry of Education China

Large scale terrain visualization with high- resolution has an increasing demand in many research fields. To realize the efficient rendering of terrain, this paper presents an out-of-core terrain visualization method based on multi-resolution storage techniques. In external memory, the terrain data set is subdivided from top to bottom to build a multi-resolution hierarchical structure based on a quad-tree. The hierarchical structure can decimate the elevation data that must be loaded into internal memory. Thus it can improve the efficiency of I/O access greatly. Moreover, in order to implement rapid data retrieval of the real time terrain flyover, an efficient indexing algorithm is proposed, in which those nodes in the hierarchical structure will be divided into several clusters in terms of the similarities of static error and the closed space constraint. In addition, a method for crack-free is also proposed here. The comprehensive experiment conducted on the GTOP30 data set shows that this approach outperforms the Block and the Hierarchy algorithms in the both ways of efficiency and simplification ratio.

关键词： Large-scale systems Clustering algorithms Information retrieval Educational institutions Computer science Data visualization Educational technology Costs Data structures Partitioning algorithms

来源：评论

学校读者我要写书评

暂无评论

没有更多数据了...

全选清除本页清除全部题录导出标记到“检索档案”

共28页 << < 19 20 21 22 23 24 25 26 27 28 > >>

检索报告对象比较合并检索0

隐藏清空

合并搜索

回到顶部

执行限定条件

内容：

评分：

请选择保存的检索档案：

请选择收藏分类：

订阅名称：

通借通还

温馨提示：

图书名称：

借书校区：

取书校区：

手机号码：

邮箱地址：

一卡通帐号：

电话和邮箱必须正确填写，我们会与您联系确认。

联系人：

所在院系：

联系邮箱：

联系电话：

内蒙古自治区呼和浩特市赛罕区大学西街235号邮编: 010021

建议与咨询 留下您的常用邮箱和电话号码，以便我们向您反馈解决方案和替代方法

时间限定

文献类型

馆藏选择

核心期刊

语言

文献类型

帮助

文字说明：

检索规则说明：

检索范例：

分类表

所选分类

限定检索结果

文献类型

馆藏范围

日期分布

学科分类号

主题

机构

作者

语言

请选择保存的检索档案： 新增检索档案 确定 取消

请选择收藏分类： 新增自定义分类 确定 取消

通借通还

建议与咨询留下您的常用邮箱和电话号码，以便我们向您反馈解决方案和替代方法

请选择保存的检索档案：

请选择收藏分类：