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

198 篇 期刊文献
121 篇 会议
1 篇 学位论文

馆藏范围

320 篇 电子文献
0 种 纸本馆藏

日期分布

学科分类号

295 篇 工学
- 224 篇 计算机科学与技术...
- 62 篇 电气工程
- 29 篇 软件工程
- 20 篇 控制科学与工程
- 13 篇 机械工程
- 13 篇 信息与通信工程
- 11 篇 动力工程及工程热...
- 11 篇 石油与天然气工程
- 9 篇 水利工程
- 7 篇 环境科学与工程（可...
- 5 篇 力学（可授工学、理...
- 5 篇 航空宇航科学与技...
- 4 篇 生物医学工程（可授...
- 3 篇 土木工程
- 2 篇 仪器科学与技术
- 2 篇 材料科学与工程（可...
- 2 篇 电子科学与技术（可...
- 2 篇 化学工程与技术
- 2 篇 交通运输工程
- 2 篇 船舶与海洋工程
62 篇 管理学
- 60 篇 管理科学与工程(可...
- 2 篇 工商管理
61 篇 理学
- 33 篇 数学
- 17 篇 生物学
- 4 篇 物理学
- 3 篇 地球物理学
- 3 篇 统计学（可授理学、...
- 2 篇 化学
- 2 篇 系统科学
3 篇 农学
3 篇 医学
2 篇 经济学
- 2 篇 应用经济学

主题

320 篇 multi-objective ...
26 篇 multi-objective ...
15 篇 genetic algorith...
11 篇 evolutionary alg...
11 篇 nsga-ii
10 篇 many-objective o...
8 篇 optimization
8 篇 evolutionary com...
7 篇 fuzzy rule-based...
7 篇 search-based sof...
7 篇 pareto front
7 篇 differential evo...
6 篇 combinatorial op...
6 篇 scheduling
5 篇 neural architect...
5 篇 parallel and dis...
5 篇 moea/d
5 篇 feature selectio...
4 篇 multi-criteria d...
4 篇 accuracy-interpr...

机构

5 篇 hosei univ fac c...
4 篇 univ pisa dipart...
4 篇 tokai univ sch i...
3 篇 hosei univ grad ...
3 篇 univ zaragoza de...
3 篇 univ cordoba dep...
3 篇 univ granada dep...
2 篇 amirkabir univ t...
2 篇 ort braude coll ...
2 篇 univ south austr...
2 篇 hunan univ sch c...
2 篇 univ jaen dept c...
2 篇 cyber dyne srl v...
2 篇 xidian univ sch ...
2 篇 royal univ bhuta...
2 篇 delft univ techn...
2 篇 basque res & tec...
2 篇 univ basque coun...
2 篇 nanjing univ sta...
2 篇 east china univ ...

作者

10 篇 marcelloni franc...
8 篇 lazzerini beatri...
6 篇 jimenez fernando
6 篇 sato yuji
6 篇 sanchez gracia
5 篇 qian chao
5 篇 ducange pietro
5 篇 coello coello ca...
5 篇 dufo-lopez rodol...
4 篇 yao xin
4 篇 liu dan-xuan
4 篇 gastelum chavira...
4 篇 guo jianmei
4 篇 zapotecas-martin...
4 篇 antonelli michel...
4 篇 leyva lopez juan...
4 篇 marquez-vega lui...
4 篇 palma jose
4 篇 miyakawa minami
4 篇 shi kai

语言

305 篇 英文
15 篇 其他

检索条件"主题词=multi-objective evolutionary algorithms"

共 320 条记录，以下是271-280 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：

Biased Pareto Optimization for Subset Selection with Dynamic Cost Constraints 18th

Biased Pareto Optimization for Subset Selection with Dynamic...

引用

18th International Conference on Parallel Problem Solving from Nature (PPSN)

作者： Liu, Dan-Xuan Qian, Chao Nanjing Univ Natl Key Lab Novel Software Technol Nanjing Peoples R China Nanjing Univ Sch Artificial Intelligence Nanjing Peoples R China

ISBN: (纸本)9783031700842;9783031700859

Subset selection with cost constraints aims to select a subset from a ground set to maximize a monotone objective function without exceeding a given budget, which has various applications such as influence maximization and maximum coverage. In real-world scenarios, the budget, representing available resources, may change over time, which requires that algorithms must adapt quickly to new budgets. However, in this dynamic environment, previous algorithms either lack theoretical guarantees or require a long running time. The state-of-the-art algorithm, POMC, is a Pareto optimization approach designed for static problems, lacking consideration for dynamic problems. In this paper, we propose BPODC, enhancing POMC with biased selection and warm-up strategies tailored for dynamic environments. We focus on the ability of BPODC to leverage existing computational results while adapting to budget changes. We prove that BPODC can maintain the best known (alpha(f) /2)(1 - e-(alpha f))-approximation guarantee when the budget changes. Experiments on influence maximization and maximum coverage show that BPODC adapts more effectively and rapidly to budget changes, with a running time that is less than that of the static greedy algorithm.

关键词： Subset selection Dynamic cost constraints Pareto optimization multi-objective evolutionary algorithms

来源：评论

学校读者我要写书评

暂无评论

Improving the Urban Accessibility of Older Pedestrians using multi-objective Optimization

Improving the Urban Accessibility of Older Pedestrians using...

引用

IEEE Congress on evolutionary Computation (CEC)

作者： Delgado-Enales, Inigo Molina-Costa, Patricia Osaba, Eneko Urra-Uriarte, Silvia Del Ser, Javier Basque Res & Technol Alliance BRTA TECNALIA Derio 48160 Bizkaia Spain Univ Basque Country UPV EHU Bilbao 48013 Bizkaia Spain

ISBN: (数字)9781665467087

ISBN: (纸本)9781665467087

Many countries around the world have witnessed the progressive ageing of their population, giving rise to a global concern to respond to the needs that this process will create. Besides the changes in the productive schemes and the evolution of the healthcare resources to new models, the accessibility of pedestrians belonging to this age range is grasping an increasing interest in urban planning processes. This work presents preliminary results of a framework that combines graph modeling and meta-heuristic optimization to inform decision makers in urban planning when deciding how to regenerate urban spaces taking into account pedestrian accessibility for the older people in urban areas with difficult orography. The goal of the framework is to decide where to deploy urban elements (mechanical ramps, escalators and lifts), so that an indirect measure of accessibility is improved while also accounting for the economical investment of the installation. We exploit the versatility of multi-objective evolutionary algorithms to tackle the underlying optimization problem. Experimental results of a case study located in the city of Santander (Spain) show that the proposed framework can support urban planners when making decisions regarding the accessibility of the public space.

关键词： Urban planning pedestrian accessibility combinatorial optimization multi-objective evolutionary algorithms

来源：评论

学校读者我要写书评

暂无评论

multi-objective Optimization of Gate Location and Processing Conditions in Injection Molding Using MOEAs: Experimental Assessment 8

Multi-Objective Optimization of Gate Location and Processing...

引用

8th International Conference on evolutionary multi-Criterion Optimization (EMO)

作者： Fernandes, Celio Pontes, Antonio J. Viana, Julio C. Gaspar-Cunha, Antonio Univ Minho Dept Polymer Engn Inst Polymer & Composites I3N Braga Portugal

ISBN: (纸本)9783319158921;9783319158914

The definition of the gate location in injection molding is one of the most important factors in achieving dimensionally accuracy of the parts. This paper presents an optimization methodology for addressing this problem based on a multi-objective evolutionary Algorithm (MOEA). The algorithm adopted here is named Reduced Pareto Set Genetic Algorithm (RPSGA) and was used to create a balanced filling pattern using weld line characterization. The optimization approach proposed in this paper is an integration of evolutionary algorithms with Computer-Aided Engineering (CAE) software (Autodesk Moldflow Plastics software). The performance of the proposed optimization methodology was illustrated with an example consisting in the injection of a rectangular part with a non-symmetrical hole. The numerical results were experimentally assessed. Physical meaning was obtained which guaranteed a successful process optimization.

关键词： multi-objective evolutionary algorithms Gate Location Moldflow

来源：评论

学校读者我要写书评

暂无评论

Constraint Handling within MOEA/D Through an Additional Scalarizing Function

Constraint Handling within MOEA/D Through an Additional Scal...

引用

Genetic and evolutionary Computation Conference (GECCO)

作者： Zapotecas-Martinez, Saul Ponsich, Antonin UAM Cuajimalpa Mexico City DF Mexico UAM Azcapotzalco Mexico City DF Mexico

ISBN: (纸本)9781450371285

The multi-objective evolutionary Algorithm based on Decomposition (MOEA/D) has shown high-performance levels when solving complicated multi-objective optimization problems. However, its adaptation for dealing with constrained multi-objective optimization problems (cMOPs) keeps being under the scope of recent investigations. This paper introduces a novel selection mechanism inspired by the epsilon-constraint method, which builds a bi-objective problem considering the scalarizing function (used into the decomposition approach of MOEA/D) and the constraint violation degree as an objective function. During the selection step of MOEA/D, the scalarizing function is considered to choose the best solutions to the cMOP. Preliminary results obtained over a set of complicated test problems drawn from the CF test suite indicate that the proposed algorithm is highly competitive regarding state-of-the-art MOEAs adopted in our comparative study.

关键词： Constrained handling techniques multi-objective evolutionary algorithms decomposition approach scalarizing functions

来源：评论

学校读者我要写书评

暂无评论

A class of pareto archived evolution strategy algorithms using immune inspired operators for ab-initio protein structure prediction

引用

EvoWorkshops 2005

作者： Cutello, V Narzisi, G Nicosia, G Univ Catania Dept Math & Comp Sci I-95125 Catania Italy Univ Kent Comp Lab Canterbury CT2 7NF Kent England

ISBN: (纸本)3540253963

In this work we investigate the applicability of a multiobjective formulation of the Ab-Initio Protein Structure Prediction (PSP) to medium size protein sequences (46-70 residues). In particular, we introduce a modified version of Pareto Archived Evolution Strategy (PAES) which makes use of immune inspired computing principles and which we will denote by "I-PAES". Experimental results on the test bed of five proteins from PDB show that PAES, (1+1)-PAES and its modified version I-PAES, are optimal multiobjective optimization algorithms and the introduced mutation operators, mut(1) and mut(2), are effective for the PSP problem. The proposed I-PAES is comparable with other evolutionary algorithms proposed in literature, both in terms of best solution found and computational cost.

关键词： protein structure tertiary fold prediction multi-objective evolutionary algorithms genetic algorithms clonal selection principle hypermutation operators

来源：评论

学校读者我要写书评

暂无评论

Visualizing the Optimization Process for multi-objective Optimization Problems 17th

Visualizing the Optimization Process for Multi-objective Opt...

引用

17th International Conference on Artificial Intelligence and Soft Computing (ICAISC)

作者： Chakuma, Bayanda Helbig, Marde Univ Pretoria Dept Comp Sci Pretoria South Africa

ISBN: (纸本)9783319912530;9783319912523

Visualization techniques used to visualize the optimization process of multi-objective evolutionary algorithms (MOEAs) have been discussed in the literature, predominantly in the context of aiding domain experts in decision making and in improving the effectiveness of the design optimization process. These techniques provide the decision maker with the ability to directly observe the performance of individual solutions, as well as their distribution in the approximated Pareto-optimal front. In this paper a visualization technique to study the mechanics of a MOEA, as it is solving multi-objective optimization problems (MOOPs), is discussed. The visualization technique uses a scatterplot animation to visualize the evolutionary process of the algorithms search, focusing on the changes in the population of non-dominated solutions obtained for each generation. The ability to visualize the optimization process of the algorithm provides the means to evaluate the performance of the algorithm, as well as visually observing the trade-offs between objectives.

关键词： Visualization Scatterplot multi-objective optimization multi-objective evolutionary algorithms

来源：评论

学校读者我要写书评

暂无评论

A Feature-Driven Crossover Operator for Product Line Architecture Design Optimization 38

A Feature-Driven Crossover Operator for Product Line Archite...

引用

IEEE 38th Annual International Computers, Software and Applications Conference (COMPSAC)

作者： Colanzi, Thelma Elita Vergilio, Silvia Regina Univ Fed Parana Dept Comp Sci BR-19031970 Curitiba Parana Brazil Univ Estadual Maringa Dept Comp Sci BR-87020900 Maringa Parana Brazil

ISBN: (纸本)9781479935741

The Product Line Architecture (PLA) design is a multi-objective optimization problem that can be properly solved in the Search Based Software Engineering (SBSE) field. However, the PLA design has specific characteristics. For example, the PLA is designed in terms of features and a highly modular PLA is necessary to enable the growth of a software product line. However, existing search based design approaches do not consider such needs. To overcome this limitation, this paper introduces a feature-driven crossover operator that aims at improving feature modularization. The proposed operator was applied in an empirical study using the multi-objective evolutionary algorithm named NSGAII. In comparison with another version of NSGAII that uses only mutation operators, the feature-driven crossover version found a greater diversity of solutions (potential PLA designs), with higher feature-based cohesion, and less feature scattering and tangling.

关键词： Product Line Architecture Design multi-objective evolutionary algorithms Crossover Operator

来源：评论

学校读者我要写书评

暂无评论

A NOVEL DYNAMIC CROWDING DISTANCE BASED DIVERSITY MAINTENANCE STRATEGY FOR MOEAS 16

A NOVEL DYNAMIC CROWDING DISTANCE BASED DIVERSITY MAINTENANC...

引用

International Conference on Machine Learning and Cybernetics (ICMLC)

作者： Yang, Ling Guan, Yuyang Sheng, Weiguo Zhejiang Univ Technol Sch Comp Sci & Technol Hangzhou 310023 Zhejiang Peoples R China Hangzhou Normal Univ Dept Comp Sci Hangzhou 310036 Zhejiang Peoples R China

ISBN: (纸本)9781538604083

Preserving population diversity is crucial for the performance of multi-objective evolutionary algorithms (MOEAs). In this paper, we propose a novel dynamic crowding distance based diversity preserving strategy for MOEAs. In the proposed strategy, the crowding distance is calculated based on the degree of deviation of each individual to its adjacent neighbors, thus appropriately adjusting the individual's density according to its position. Further, a multi-individual deletion mechanism is introduced to improve the efficiency of the strategy. For evaluation purpose, we incorporate the proposed strategy into NSGA-II and test it on ten functions. Our results show that the proposed strategy is able to improve the performance of NSGA-II and the resulting algorithm outperforms related methods to be compared.

关键词： multi-objective evolutionary algorithms Diversity preserve Dynamic crowding distance

来源：评论

学校读者我要写书评

暂无评论

Adaptive Bi-objective Genetic Programming for Data-Driven System Modeling

Adaptive Bi-objective Genetic Programming for Data-Driven Sy...

引用

12th International Conference on Intelligent Computing (ICIC)

作者： Bevilacqua, Vitoantonio Nuzzolese, Nicola Mininno, Ernesto Iacca, Giovanni Politecn Bari Dipartimento Ingn Elettr & Informaz Via Orabona 4 I-70125 Bari Italy Cyber Dyne Srl Via Scipione Crisanzio 119 I-70123 Bari Italy

ISBN: (纸本)9783319422978;9783319422961

We propose in this paper a modification of one of the modern state-of-the-art genetic programming algorithms used for data-driven modeling, namely the Bi-objective Genetic Programming (BioGP). The original method is based on a concurrent minimization of both the training error and complexity of multiple candidate models encoded as Genetic Programming trees. Also, BioGP is empowered by a predator-prey co-evolutionary model where virtual predators are used to suppress solutions (preys) characterized by a poor trade-off error vs complexity. In this work, we incorporate in the original BioGP an adaptive mechanism that automatically tunes the mutation rate, based on a characterization of the current population (in terms of entropy) and on the information that can be extracted from it. We show through numerical experiments on two different datasets from the energy domain that the proposed method, named BioAGP (where "A" stands for "Adaptive"), performs better than the original BioGP, allowing the search to maintain a good diversity level in the population, without affecting the convergence rate.

关键词： multi-objective evolutionary algorithms Adaptive genetic programming Machine learning Home automation Energy efficiency

来源：评论

学校读者我要写书评

暂无评论

multi-objective Optimization for Automated Business Process Discovery 11

Multi-Objective Optimization for Automated Business Process ...

引用

11th International Joint Conference on Knowledge Discovery, Knowledge Engineering and Knowledge Management (IC3K) / 11th International Conference on Knowledge Discovery and Information Retrieval (KDIR)

作者： Ghazal, Mohamed A. Ghoniemy, Samy Salama, Mostafa A. British Univ Egypt Dept Comp Sci Cairo Egypt

ISBN: (纸本)9789897583827

Process Mining is a research field that aims to develop new techniques to discover, monitor and improve real processes by extracting knowledge from event logs. This relatively young research discipline has evidenced efficacy in various applications, especially in application domains where a dynamic behavior needs to be related to process models. Process Model Discovery is presumably the most important task in Process Mining since the discovered models can be used as an objective starting points for any further process analysis to be conducted. There are various quality dimensions the model should consider during discovery such as Replay-Fitness, Precision, Generalization, and Simplicity. It becomes evident that Process Model Discovery, with its current given settings, is a multi-objective Optimization Problem. However, most existing techniques does not approach the problem as a multi-objective Optimization Problem. Therefore, in this work we propose the use of one of the most robust and widely used multi-objective Optimizers in Process Model Discovery, the NSGA-II algorithm. Experimental results on a real life event log shows that the proposed technique outperforms existing techniques in various aspects. Also this work tries to establish a benchmarking system for comparing results of multi-objective Optimization based Process Model Discovery techniques.

关键词： multi-objective Optimization Process Mining multi-objective evolutionary algorithms Process Model Discovery Non-dominated Sorting Genetic Algorithm II

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32页 << < 23 24 25 26 27 28 29 30 31 32 > >>

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：