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

161 篇 期刊文献
146 篇 会议
2 篇 学位论文

馆藏范围

309 篇 电子文献
0 种 纸本馆藏

日期分布

学科分类号

282 篇 工学
- 253 篇 计算机科学与技术...
- 52 篇 电气工程
- 41 篇 软件工程
- 26 篇 控制科学与工程
- 9 篇 机械工程
- 8 篇 信息与通信工程
- 4 篇 材料科学与工程（可...
- 3 篇 力学（可授工学、理...
- 3 篇 生物医学工程（可授...
- 2 篇 仪器科学与技术
- 2 篇 化学工程与技术
- 1 篇 电子科学与技术（可...
- 1 篇 石油与天然气工程
- 1 篇 交通运输工程
- 1 篇 航空宇航科学与技...
- 1 篇 生物工程
74 篇 理学
- 51 篇 数学
- 28 篇 生物学
- 4 篇 统计学（可授理学、...
- 1 篇 物理学
- 1 篇 系统科学
55 篇 管理学
- 54 篇 管理科学与工程(可...
- 3 篇 工商管理
- 1 篇 公共管理
7 篇 农学
- 5 篇 作物学
5 篇 医学
- 4 篇 基础医学(可授医学...
- 1 篇 临床医学
4 篇 经济学
- 4 篇 应用经济学

主题

309 篇 estimation of di...
32 篇 evolutionary alg...
29 篇 genetic algorith...
25 篇 evolutionary com...
16 篇 bayesian network...
15 篇 combinatorial op...
13 篇 bayesian optimiz...
13 篇 optimization
13 篇 machine learning
12 篇 multi-objective ...
9 篇 genetic programm...
9 篇 particle swarm o...
7 篇 genetic algorith...
7 篇 efficiency enhan...
6 篇 linkage learning
6 篇 model building
5 篇 feature subset s...
5 篇 hierarchical boa
5 篇 data mining
5 篇 denoising autoen...

机构

5 篇 univ queensland ...
4 篇 univ birmingham ...
4 篇 johannes gutenbe...
3 篇 univ illinois de...
3 篇 univ politecn ma...
3 篇 chulalongkorn un...
3 篇 jiaxing univ col...
3 篇 univ kent sch co...
3 篇 tsinghua univ st...
3 篇 lanzhou univ tec...
3 篇 taiyuan univ sci...
2 篇 yuan ze univ dep...
2 篇 hokkaido univ in...
2 篇 univ adelaide op...
2 篇 aalborg univ ope...
2 篇 univ tecnol fed ...
2 篇 univ illinois il...
2 篇 univ missouri de...
2 篇 univ fed parana ...
2 篇 univ essex dept ...

作者

26 篇 santana roberto
22 篇 lozano jose a.
17 篇 mendiburu alexan...
13 篇 pelikan martin
12 篇 larranaga pedro
8 篇 sastry kumara
8 篇 rothlauf franz
8 篇 bielza concha
8 篇 goldberg david e...
6 篇 gamez jose a.
6 篇 ceberio josu
6 篇 larrañaga p
5 篇 martins marcella...
5 篇 wittenberg david
5 篇 luders ricardo
5 篇 grahl joern
5 篇 irurozki ekhine
5 篇 bosman peter a. ...
4 篇 chen shih-hsin
4 篇 shakya siddharth...

语言

300 篇 英文
7 篇 其他
1 篇 西班牙文
1 篇 中文

检索条件"主题词=Estimation of Distribution algorithms"

共 309 条记录，以下是251-260 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：

Multiobjective hBOA, clustering, and scalability 05

Multiobjective hBOA, clustering, and scalability

引用

Genetic and Evolutionary Computation Conference

作者： Pelikan, Martin Sastry, Kumara Goldberg, David E. Univ Missouri Dept Math & Comp Sci St Louis MO 63121 USA

ISBN: (纸本)1595930108

This paper describes a scalable algorithm for solving multiobjective decomposable problems by combining the hierarchical Bayesian optimization algorithm (hBOA) with the nondominated sorting genetic algorithm (NSGA-II) and clustering in the objective space. It is first argued that for good scalability, clustering or some other form of niching in the objective space is necessary and the size of each niche should be approximately equal. Multiobjective hBOA (mohBOA) is then described that combines hBOA, NSGA-II and clustering in the objective space. The algorithm mohBOA differs from the multiobjective variants of BOA and hBOA proposed in the past by including clustering in the objective space and allocating an approximately equally sized portion of the population to each cluster. The algorithm mohBOA is shown to scale up well on a number of problems on which standard multiobjective evolutionary algorithms perform poorly.

关键词： genetic algorithms estimation of distribution algorithms multiobjective optimization BOA nondominated sorting NSGA-II clustering

来源：评论

学校读者我要写书评

暂无评论

Solving Sudoku Puzzles with Node Based Coincidence Algorithm

Solving Sudoku Puzzles with Node Based Coincidence Algorithm

引用

10th International Joint Conference on Computer Science and Software Engineering (JCSSE)

作者： Waiyapara, Kiatsopon Wattanapornprom, Warin Chongstitvatana, Prabhas Chulalongkorn Univ Fac Engn Dept Compute Engn Bangkok Thailand Chulalongkorn Univ Fac Engn Dept Comp Engn Bangkok Thailand

ISBN: (纸本)9781479908066;9781479908059

In Evolutionary computation, Sudoku puzzles are categorized as hard combinatorial problems. It is almost impossible to solve these puzzles using only native operations of genetic algorithms. This article presents an application of Coincidence algorithm, which is an estimation of distribution algorithms in the class of evolutionary computation that can outperform traditional algorithms on several combinatorial problems. It makes use of both positive and negative knowledge for solving problems. The proposed method is compared with the current best known method. It significantly outperforms problem-specific GA to solve easy, medium, and hard level of Sudoku puzzles.

关键词： Coincidence Algorithm Sudoku Puzzle Multimodal Optimization estimation of distribution algorithms Genetic Algorithm

来源：评论

学校读者我要写书评

暂无评论

Convergence Phases, Variance Trajectories, and Runtime Analysis of Continuous EDAs 07

Convergence Phases, Variance Trajectories, and Runtime Analy...

引用

Annual Conference of Genetic and Evolutionary Computation Conference

作者： Grahl, Joern Bosman, Peter A. N. Minner, Stefan Univ Mannheim Dept Logist D-68131 Mannheim Germany Ctr Math & Comp Sci NL-1090 GB Amsterdam Netherlands

ISBN: (纸本)9781595936974

Considering the available body of literature oil continuous EDAs, one must state that many important questions are still unanswered, e.g.: How do continuous EDAs really work, and how can we increase their efficiency further? The first question must be answered oil the basis of formal models, but despite some recent results, the majority of contributions to the held is experimental. The second question should be answered by exploiting the insights that have been gained from formal models, We contribute, to the theoretical literature oil continuous EDAs by focussing on a simple, yet important, question: HOW Should the variances used to sample offspring front change over all EDA run? To answer this question, the convergence process is separated into three phases and it is shown that for each phase, a preferable strategy exists for setting the variances. It is highly likely that the use of variances that have been estimated with maximum likelihood is not optimal. Thus, variance modification policies are not just a nice add-on. In the light of our findings, they become an integral component of continuous EDAs, and they should consider the specific requirements of all phases of the optimization process.

关键词： Evolutionary algorithms estimation of distribution algorithms Numerical Optimization Predictive Models

来源：评论

学校读者我要写书评

暂无评论

HYBRID MUSIC RECOMMENDER USING CONTENT-BASED AND SOCIAL INFORMATION 41

HYBRID MUSIC RECOMMENDER USING CONTENT-BASED AND SOCIAL INFO...

引用

41st IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP)

作者： Chiliguano, Paulo Fazekas, Gyorgy Queen Mary Univ London Sch Elect Engn & Comp Sci Mile End Rd London E1 4NS England

ISBN: (纸本)9781479999880

Internet resources available today, including songs, albums, playlists or podcasts, that a user cannot discover if there is not a tool to filter the items that the user might consider relevant. Several recommendation techniques have been developed since the Internet explosion to achieve this filtering task. In an attempt to recommend relevant songs to users, we propose an hybrid recommender that considers real-world users information and high-level representation for audio data. We use a deep learning technique, convolutional deep neural networks, to represent an audio segment in a n-dimensional vector, whose dimensions define the probability of the segment to belong to a specific music genre. To capture the listening behavior of a user, we investigate a state-of-the-art technique, estimation of distribution algorithms. The designed hybrid music recommender outperforms the predictions compared with a traditional content-based recommender.

关键词： Deep Learning Convolutional Neural Networks estimation of distribution algorithms Recommender Systems MIR

来源：评论

学校读者我要写书评

暂无评论

Improved Runtime Bounds for the Univariate Marginal distribution Algorithm via Anti-Concentration 17

Improved Runtime Bounds for the Univariate Marginal Distribu...

引用

Genetic and Evolutionary Computation Conference (GECCO)

作者： Lehre, Per Kristian Phan Trung Hai Nguyen Univ Birmingham Sch Comp Sci Birmingham B15 2TT W Midlands England

ISBN: (纸本)9781450349208

Unlike traditional evolutionary algorithms which produce offspring via genetic operators, estimation of distribution algorithms (EDAs) sample solutions from probabilistic models which are learned from selected individuals. It is hoped that EDAs may improve optimisation performance on epistatic fitness landscapes by learning variable interactions. However, hardly any rigorous results are available to support claims about the performance of EDAs, even for fitness functions without epistasis. The expected runtime of the Univariate Marginal distribution Algorithm (UMDA) on OneMax was recently shown to be in O (n lambda log lambda) [9]. Later, Krejca and WiS proved the lower bound Omega(lambda root n + n logn) via an involved dri% analysis [16]. We prove a O (n lambda) bound, given some restrictions on the population size. Ois implies the tight bound Theta (n logn) when lambda = O (logn), matching the runtime of classical EAs. Our analysis uses the level-based theorem and anti-concentration properties of the Poisson-binomial distribution. We expect that these generic methods will facilitate further analysis of EDAs.

关键词： Runtime Analysis Level-based Analysis estimation of distribution algorithms

来源：评论

学校读者我要写书评

暂无评论

The Design of (Almost) Disjunct Matrices by Evolutionary algorithms 7th

The Design of (Almost) Disjunct Matrices by Evolutionary Alg...

引用

7th International Conference on the Theory and Practice of Natural Computing (TPNC)

作者： Knezevic, Karlo Picek, Stjepan Mariot, Luca Jakobovic, Domagoj Leporati, Alberto Univ Zagreb Fac Elect Engn & Comp Zagreb Croatia Delft Univ Technol Cyber Secur Res Grp Delft Netherlands Univ Milano Bicocca Dept Informat Syst & Commun Milan Italy

ISBN: (纸本)9783030040703;9783030040697

Disjunct Matrices (DM) are a particular kind of binary matrices which have been especially applied to solve the Non-Adaptive Group Testing (NAGT) problem, where the task is to detect any configuration of t defectives out of a population of N items. Traditionally, the methods used to construct DM leverage on error-correcting codes and other related algebraic techniques. Here, we investigate the use of Evolutionary algorithms to design DM and two of their generalizations, namely Resolvable Matrices (RM) and Almost Disjunct Matrices (ADM). After discussing the basic encoding used to represent the candidate solutions of our optimization problems, we define three fitness functions, each measuring the deviation of a generic binary matrix from being respectively a DM, an RM or an ADM. Next, we employ estimation of distribution algorithms (EDA), Genetic algorithms (GA), and Genetic Programming (GP) to optimize these fitness functions. The results show that GP achieves the best performances among the three heuristics, converging to an optimal solution on a wider range of problem instances. Although these results do not match those obtained by other state-of-the-art methods in the literature, we argue that our heuristic approach can generate solutions that are not expressible by currently known algebraic techniques, and sketch some possible ideas to further improve its performance.

关键词： Evolutionary computing Disjunct matrices Resolvable matrices Almost disjunct matrices Group testing estimation of distribution algorithms Genetic algorithms Genetic programming

来源：评论

学校读者我要写书评

暂无评论

Solving Multi-Objective Reinforcement Learning Problems by EDA-RL - Acquisition of Various Strategies

Solving Multi-Objective Reinforcement Learning Problems by E...

引用

9th International Conference on Intelligent Systems Design and Applications

作者： Handa, Hisashi Okayama Univ Grad Sch Nat Sci & Technol Okayama Japan

ISBN: (纸本)9781424447350

EDA-RL, estimation of distribution algorithms for Reinforcement Learning Problems, have been proposed by us recently. The EDA-RL can improve policies by EDA scheme: First, select better episodes. Secondly, estimate probabilistic models, i.e., policies, and finally, interact with the environment for generating new episodes. In this paper, the EDA-RL is extended for Multi-Objective Reinforcement Learning Problems, where reward is given by several criteria. By incorporating the notions in Evolutionary Multi-Objective Optimization, the proposed method is enable to acquire various strategies by a single run.

关键词： estimation of distribution algorithms Reinforcement Learning Problems Evolutionary Multi-Objective Optimisation

来源：评论

学校读者我要写书评

暂无评论

On the investigation of population sizing of genetic algorithms using optimal mixing

On the investigation of population sizing of genetic algorit...

引用

Genetic and Evolutionary Computation Conference (GECCO)

作者： Liao, Yi-Yun Hsu, Hung-Wei Juang, Yi-Lin Yu, Tian-Li Natl Taiwan Univ Taipei Taiwan

ISBN: (纸本)9781450361118

Genetic algorithms using optimal mixing have shown promising results, while lack of theoretical supports. This paper investigates population sizing from the supply aspect under the optimal mixing scenario. Specifically, more precise analyses on supply, including the expectation and the lower bound, are made. In addition, considering recombining one randomly generated chromosome with the rest of the population to achieve the global optimum, the tight bounds of the size of the population providing proper fragments chosen by restricted oracles are derived. Tight bounds on problems with ring topologies where a subfunction overlaps two other subfunctions are also derived. Finally, experiments are conducted and well match the derivations.

关键词： estimation of distribution algorithms Genetic algorithms Population Sizing

来源：评论

学校读者我要写书评

暂无评论

Multi-objective Optimization with Joint Probabilistic Modeling of Objectives and Variables

Multi-objective Optimization with Joint Probabilistic Modeli...

引用

6th International Conference on Evolutionary Multi-Criterion Optimization

作者： Karshenas, Hossein Santana, Roberto Bielza, Concha Larranaga, Pedro Tech Univ Madrid Sch Comp Sci Computat Intelligence Grp Madrid 28660 Spain

ISBN: (纸本)9783642198922

The objective values information can be incorporated into the evolutionary algorithms based on probabilistic modeling in order to capture the relationships between objectives and variables. This paper investigates the effects of joining the objective and variable information on the performance of an estimation of distribution algorithm for multi-objective optimization. A joint Gaussian Bayesian network of objectives and variables is learnt and then sampled using the information about currently best obtained objective values as evidence. The experimental results obtained on a set of multi-objective functions and in comparison to two other competitive algorithms are presented and discussed.

关键词： Multi-objective Optimization estimation of distribution algorithms Joint Probabilistic Modeling

来源：评论

学校读者我要写书评

暂无评论

Unbalanced Mallows Models for Optimizing Expensive Black-Box Permutation Problems

Unbalanced Mallows Models for Optimizing Expensive Black-Box...

引用

2nd Genetic and Evolutionary Computation Conference (GECCO)

作者： Irurozki, Ekhine Lopez-Ibanez, Manuel Telecom Paris Paris France Univ Malaga Malaga Spain

ISBN: (纸本)9781450383509

Expensive black-box combinatorial optimization problems arise in practice when the objective function is evaluated by means of a simulator or a real-world experiment. Since each fitness evaluation is expensive in terms of time or resources, the number of possible evaluations is typically several orders of magnitude smaller than in non-expensive problems. Classical optimization methods are not useful in this scenario. In this paper, we propose and analyze UMM, an estimation-of-distribution (EDA) algorithm based on a Mallows probabilistic model and unbalanced rank aggregation (uBorda). Experimental results on black-box versions of LOP and PFSP show that UMM outperforms the solutions obtained by CEGO, a Bayesian optimization algorithm for combinatorial optimization. Nevertheless, a slight modification to CEGO, based on the different interpretations for rankings and orderings, significantly improves its performance, thus producing solutions that are slightly better than those of UMM and dramatically better than the original version. Another benefit of UMM is that its computational complexity increases linearly with both the number of function evaluations and the permutation size, which results in computation times an order of magnitude shorter than CEGO, making it specially useful when both computation time and number of evaluations are limited.

关键词： Combinatorial optimization Bayesian optimization Expensive blackbox optimization estimation of distribution 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31页 << < 22 23 24 25 26 27 28 29 30 31 > >>

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：