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

300 篇 期刊文献
176 篇 会议
6 篇 学位论文

馆藏范围

482 篇 电子文献
0 种 纸本馆藏

日期分布

学科分类号

439 篇 工学
- 171 篇 计算机科学与技术...
- 134 篇 电气工程
- 73 篇 石油与天然气工程
- 57 篇 机械工程
- 54 篇 动力工程及工程热...
- 44 篇 材料科学与工程（可...
- 43 篇 信息与通信工程
- 39 篇 控制科学与工程
- 33 篇 化学工程与技术
- 25 篇 力学（可授工学、理...
- 22 篇 土木工程
- 17 篇 环境科学与工程（可...
- 15 篇 软件工程
- 14 篇 仪器科学与技术
- 10 篇 建筑学
- 8 篇 电子科学与技术（可...
- 8 篇 交通运输工程
- 4 篇 冶金工程
- 4 篇 水利工程
- 4 篇 船舶与海洋工程
66 篇 理学
- 25 篇 数学
- 18 篇 物理学
- 15 篇 化学
- 8 篇 生物学
63 篇 管理学
- 59 篇 管理科学与工程(可...
- 3 篇 图书情报与档案管...
5 篇 经济学
- 2 篇 理论经济学
5 篇 医学
3 篇 教育学
1 篇 文学
1 篇 艺术学

主题

482 篇 multi objective ...
61 篇 genetic algorith...
16 篇 evolutionary alg...
13 篇 genetic algorith...
12 篇 nsga-ii
11 篇 particle swarm o...
10 篇 ant colony optim...
8 篇 optimization
7 篇 fuzzy logic
7 篇 pareto front
7 篇 evolutionary alg...
7 篇 artificial neura...
7 篇 energy efficienc...
6 篇 reliability
6 篇 distributed gene...
6 篇 response surface...
6 篇 surface roughnes...
6 篇 grey relational ...
6 篇 cloud computing
6 篇 topsis

机构

3 篇 politecn milan d...
2 篇 natl inst techno...
2 篇 nanyang technol ...
2 篇 vali e asr univ ...
2 篇 xerox corp wilso...
2 篇 leju shenzhen ro...
2 篇 natl univ def te...
2 篇 univ malaya fac ...
2 篇 sharif univ tech...
2 篇 chukwuemeka odum...
2 篇 iran univ sci & ...
2 篇 florida atlantic...
2 篇 guangxi univ sci...
2 篇 king khalid univ...
2 篇 tsinghua univ de...
2 篇 collaborat innov...
2 篇 univ minho sch e...
2 篇 st josephs coll ...
2 篇 iran univ sci & ...
2 篇 arak univ fac en...

作者

4 篇 chakraborty ajoy...
4 篇 bhowmik arup rat...
4 篇 nwobi-okoye chid...
4 篇 rinaldi fabio
4 篇 najafi behzad
4 篇 perera a. t. d.
4 篇 hajabdollahi has...
4 篇 mamaghani alirez...
3 篇 perera k. k. c. ...
3 篇 srikanth r.
3 篇 casalegno andrea
3 篇 attalage r. a.
3 篇 marechal francoi...
3 篇 balaji c.
3 篇 farrokhi-asl ham...
3 篇 safikhani hamed
2 篇 waghmare atul c.
2 篇 deng hai
2 篇 kim jinkoo
2 篇 lv junshuai

语言

443 篇 英文
28 篇 其他
9 篇 中文
2 篇 土耳其文

检索条件"主题词=multi objective optimization"

共 482 条记录，以下是81-90 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：

On the performance of MATLAB's inbuilt genetic algorithm on single and multi-objective unconstrained optimization problems

On the performance of MATLAB's inbuilt genetic algorithm on ...

引用

International Conference on Electrical, Electronics, and optimization Techniques (ICEEOT)

作者： Punnathanam, Varun Sivadurgaprasad, Chinta Kotecha, Prakash Indian Inst Technol Dept Chem Engn Gauhati India

ISBN: (纸本)9781467399395

Genetic Algorithm (GA) is a very popular evolutionary technique that has been used for single and multi objective optimization problems. MATLAB, a widely used technical computing language, has its own variant of these algorithms included along with its optimization toolbox. Since this allows for easy implementation, it has been widely used to solve various engineering problems. The performances of the inbuilt single and multi-objective algorithms of GA at default settings are studied on a total of 29 benchmark functions. The single objective ga is tested on a set of fourteen popularly used single objective benchmark functions whereas the multi-objective gamultiobj is tested on five of the Zitzler-Deb-Thiele's (ZDT) problems and the ten unconstrained problems from the CEC2009 algorithm competition.

关键词： Genetic Algorithm multi objective optimization MATLAB Performance Evaluation

来源：评论

学校读者我要写书评

暂无评论

A Solution to the multi-objective optimization Problem with FACTS Devices using NSHCSA Including Practical Constraints

A Solution to the Multi-Objective Optimization Problem with ...

引用

IEEE International Conference on Power, Control, Signals and Instrumentation Engineering (IEEE ICPCSI)

作者： Balasubbareddy, M. Chaitanya Bharathi Inst Technol Elect & Elect Engn Hyderabad India

ISBN: (纸本)9781538608142

Optimal Power Flow (OPF) with FACTS devices place a vital role in power systems. In this paper, a proposed Non-dominated Sorting Hybrid Cuckoo Search Algorithm (NSHCSA) for multi objective optimal power flow problem with series FACTS devices namely Static Synchronous Series Compensator (SSSC) and Interline Power Flow Controller (IPFC) with different objective functions including the practical constraints, operating constraints and the installation cost of FACTS devices are considered for this analysis. Some heuristic rules are suggested for the optimal location of FACTS devices to reduce the number of possible locations. Cuckoo Search Algorithm (CSA) and Genetic Algorithm (GA) are combined to form the proposed Hybrid Cuckoo Search Algorithm (HCSA). The fuzzy decision making tool is used to select optimal Pareto front solution for multi objectives. The effectiveness of the proposed method is tested on IEEE-30 bus test system with FACTS devices. The results are analyzed and compared with existing methods.

关键词： Hybrid cuckoo search algorithm multi objective optimization Pareto solution Location of FACTS device Device installation cost Non-dominated Sorting power system severity

来源：评论

学校读者我要写书评

暂无评论

multi-objective optimization Algorithm for Efficient Pin-constrained Droplet Routing Technique in Digital Microfluidic Biochip

Multi-objective Optimization Algorithm for Efficient Pin-con...

引用

14th International Symposium on Quality Electronic Design (ISQED)

作者： Chatterjee, Soumyajit Rahaman, Hafizur Samanta, Tuhina Bengal Engn & Sci Univ Sibpur Howrah India

ISBN: (纸本)9781467349529;9781467349512

Design automation for digital microfluidic biochip comprises of many combinatorial optimization problems, which are NP-complete in nature. Efficient optimization algorithms to solve them is in dearth till date. In this paper, we propose a muIti-objective optimization algorithm that simuItaneously minimizes several resources during bioassay operations in a digital microfluidic biochip. We design the progressive droplet routing as a constrained multi-objective optimization problem considering three objective functions to be optimized, named (i) electrode usages, (ii) routing completion time, or latest arrival time, and (iii) control pin allocation. A composite objective function is constructed by a weighted sum of the first two objective functions. This composite function is minimized pertaining to an upper bound on the third objective function, control pin allocation. A fractional constant weight factor (A) is chosen to confer upon the necessary weightage on the two factors involved in the composite objective function for accurate optimization procedure. We perform experimentations with several existing benchmarks, and experimental resuIts are quite encouraging.

关键词： Digital Microfluidic Biochip multi objective optimization Droplet Routing Pin Assignment Algorithm

来源：评论

学校读者我要写书评

暂无评论

multi-objective optimization on Inlet Pipe of a Vertical Inline Pump Based on Genetic Algorithm and Artificial Neural Network 5

Multi-objective Optimization on Inlet Pipe of a Vertical Inl...

引用

ASME Fluids Engineering Division Summer Meeting (FEDSM2018)

作者： Gan, Xingcheng Pei, Ji Yuan, Shouqi Wang, Wenjie Tang, Yajing Jiangsu Univ Natl Res Ctr Pumps Zhenjiang Jiangsu Peoples R China

ISBN: (纸本)9780791851555

In order to save the space for installation, a bent pipe is adopted for inlet of vertical inline pump. In this paper, to improve the performance of inlet pipe, a multi-objective optimization on the inlet pipe is proposed based on Genetic Algorithm (GA) and Artificial Neural Network (ANN) model. A 5th-order Bezier curve is applied to fit the mean line of the inlet pipe and 3rdorder Bezier curves are used for depicting the variation trend of shape of sections. As the outlet of inlet pipe is fixed, 11 design variables are utilized for optimization, and the three optimization objectives are efficiency, head and standard deviation of velocity at the outlet of inlet pipe. To get the surrogate model, 149 different models obtained from Latin hypercube sampling are solved with numerical simulation. The results showed the numerical simulation has a great agreement with the experiment. Artificial neural network can accurately fit the target functions and design variables. The deviation of efficiency, head and standard deviation of velocity between predicted value and actual value were 0.26%, 0.05m and-0.27m/s, respectively. After optimization, an improvement on flow condition and a decrease of standard deviation of velocity before impeller were obtained. The efficiency and head were improved by 1.16% and 0.2m, respectively.

关键词： Vertical inline pump A bent pipe multi objective optimization Genetic Algorithm

来源：评论

学校读者我要写书评

暂无评论

multi-objective optimization Of Hard Turning: A Genetic Algorithm Approach

Multi-Objective Optimization Of Hard Turning: A Genetic Algo...

引用

International Conference on Materials Manufacturing and Modelling (ICMMM)

作者： Manav, Omkar Chinchanikar, Satish VIIT Pune 411048 Maharashtra India

Obtaining the process parameters to optimize machining performance is vital in machining execution since they significantly affect the productivity rate, cost and quality of machining operation. Although, process parameter optimization has been widely investigated for conventional machining operations, very limited work reported on optimization of hard turning using evolutionary algorithms such as genetic algorithm. In this work, multi-objective optimization of hard turning is attempted using a genetic algorithm during turning of hardened AISI 4340 steel at different levels of hardness with experimental-based multi regression models as objective function. The multi objective formulation involves minimum cutting forces, minimum surface roughness, minimum cutting temperature and maximum tool life. The process variables are cutting speed, depth of cut and feed with appropriate constraints. Finally, the optimal process parameters and optimized responses obtained through genetic algorithm are compared with the optimization results obtained using response surface methodology technique. It has been observed that a genetic algorithm gives encouraging results and could be used to to optimize multi-objective responses. (C) 2017 Elsevier Ltd. All rights reserved.

关键词： multi objective optimization hard turning Genetic Algorithm

来源：评论

学校读者我要写书评

暂无评论

On the use of multi-objective optimization Algorithms for solving the Impairment Aware-RWA problem

On the use of Multi-Objective Optimization Algorithms for so...

引用

IEEE International Conference on Communications (ICC 2009)

作者： Monoyios, Demetris Vlachos, Kyriakos Aggelou, Marianna Tomkos, Ioannis Univ Patras Comp Engn & Informat Dept Res Acad Comp Technol Inst Rion Greece Athens Informat Technol AIT Ctr Athens 19002 Greece

ISBN: (纸本)9781424434343

In future transparent optical networks, it is important to consider the impact of physical impairments in the routing and wavelengths assignment process, to achieve efficient connection provisioning. In this paper, we use classical multi-objective optimization (MOO) strategies and particularly genetic algorithms to jointly solve the impairment aware RWA (IA-RWA) problem. Fiber impairments are indirectly considered through the insertion of the path length and the number of common hops in the optimization process. It is shown that blocking is greatly improved, while the obtained solutions truly converge towards the Pareto front that constitutes the set of global optimum solutions. We have evaluated our findings, using an Q estimator tool, that calculates the signal quality of each path analytically.

关键词： RWA Genetic Algorithm All-Optical Networks multi objective optimization

来源：评论

学校读者我要写书评

暂无评论

A New Formulation and Solving of Protective Relays Setting and Coordination Problem Using multi-objective optimization and Fuzzy Logic 8

A New Formulation and Solving of Protective Relays Setting a...

引用

8th International Conference on Modelling, Identification and Control (ICMIC)

作者： Benahid, Rahah CRNB Dept Elect Engn Djelfa Algeria

ISBN: (纸本)9780956715777

This paper presents a new formulation of the overcurrent relays setting and coordination problem using the combinatory constrained multi-objective optimization. Two objective functions are selected to be minimized simultaneously namely: the minimization of the primary relays operation time as well as the minimization of the backup relays operation time. Both real and integer decision variables are considered;where the real variables are the time dial setting (TDS), as well as the pickup current (Ip), and the integer variables are the relay characteristics. To solve this constrained non linear multi objective problem, the original algorithm of Strength Pareto Evolutionary Algorithm 2 (SPEA 2) is enhanced in order to manage both real and integer decision variables as well as to handle the constraints violation during the optimization process. A fuzzy-based mechanism is employed to aid the decision maker to choose the best compromise solution from the Pareto front. The obtained results show the efficiency of the proposed SPEA2 to solve the multi-objective optimization of overcurrent relays and capture the Pareto front. Furthermore, the proposed method is able to find values of the real (Ip, and TDS) and integer (relays characteristics) decision variables that ensure a good coordination of the relays with the satisfaction of the constraints.

关键词： power systems electrical protection overcurrent relays setting and coordination short circuit analysis multi objective optimization Pareto front Fuzzy logic best compromise solution SPEA2 decision making

来源：评论

学校读者我要写书评

暂无评论

M-RS: A Systematic Literature Review on multi-objective optimization along with Recommendation System 7

M-RS: A Systematic Literature Review on Multi-Objective Opti...

引用

7th International Conference on Engineering and Emerging Technologies (ICEET)

作者： Bin Muzammil, Muteeb Ajmal, Sahar Javed, Shahzeb Tariq, Arsalan Iqbal, Umer Riphah Int Univ Coll Comp Fasialabad Campus Fasialabad 38000 Pakistan

ISBN: (纸本)9781665427142

Recommendation systems (RS) are used for extracting data on the basis of rating and interest provided by the users on a particular item. In the current era, the world is relying more on RS to get the relevant data. To increase the efficiency of RS, multi-objective optimization (MOO) is integrated with it. MOO is a branch of a multi-criteria decision-making scheme. MOO considers different conflicting objectives to optimize the results. The combination of MOO and RS will enhance the reliability of recommendations because the recommendations are provided by using different intentions of users with diverse requirements. This paper performs a Systematic Literature Review (SLR) on the articles that use MOO and RS with each other. The SLR is performed on 26 studies that are extracted from the study selection procedure. These 26 articles are then analyzed through different perspectives such as their domains, the method they have used, and evaluation techniques adopted, and the overall research trend of M-RS. The result shows that the application of MOO in field of RS is most popular among generic RS rather than specific RS. Furthermore, the results reflect that the MovieLens dataset has the highest popularity as 13 studies used it for the evaluation of their techniques. In the future, more research questions will be proposed to have a more in-depth insight into this field.

关键词： Recommendation systems multi objective optimization Systematic Literature Review MOO RS

来源：评论

学校读者我要写书评

暂无评论

GeDEA-II: A Novel Evolutionary Algorithm for multi-objective optimization Problems Based on the Simplex Crossover and The Shrink Mutation

GeDEA-II: A Novel Evolutionary Algorithm for Multi-Objective...

引用

World Congress on Engineering and Computer Science

作者： Da Ronco, Claudio Comis Benini, Ernesto HIT09 Srl Galleria Stor 8 I-35131 Padua Italy Univ Padua Dept Ind Engn I-35131 Padua Italy

ISBN: (纸本)9789881925244

The key issue for an efficient and reliable multi objective evolutionary algorithm is the ability to converge to the True Pareto Front with the least number of objective function evaluations, while covering it as much as possible. To this purpose, in a previous paper performance comparisons showed that the Genetic Diversity Evolutionary Algorithm (GeDEA) was at the same level of the best state-of-the-art MOEAs due to it intrinsic ability to properly conjugate exploitation of current non-dominated solutions and the exploration of the search space. In this paper, an improved version, namely the GeDEA-II, is proposed which features a novel crossover operator, the Simplex-Crossover, and a novel mutation operator, the Shrink Mutation. GeDEM operator was left unchanged and completed using the non-dominated-sorting based on crowding distance. The comparison among GeDEA-II and GeDEA, as well as with three other modern elitist methods, on different extremely multidimensional test problems, clearly indicates that the performance of GeDEA-II is, at least in these cases, superior. In addition, authors aimed at putting in evidence the very good performance of GeDEA-II even in extremely multidimensional landscapes. To do this, four test problems were considered, and the GeDEA-II performance tested as the number of decision variables was increased. In particular, ZDT test functions featured a number of decision variables ranging from the original proposed number up to 1000, whereas on DTLZ the decision variables were increased up to 100 times the original proposed number. Results obtained contribute to demonstrate further the GeDEA-II breakthrough performance.

关键词： Evolutionary algorithms Simplex Crossover Shrink Mutation Pareto optimality multi objective optimization Empirical - Comparison

来源：评论

学校读者我要写书评

暂无评论

Smart Home Appliances Usage Recommendation Using multi-objective optimization 19th

Smart Home Appliances Usage Recommendation Using Multi-objec...

引用

19th EPIA Conference on Artificial Intelligence (EPIA)

作者： Feitosa, Allan Lacerda, Henrique Silva-Filho, Abel Univ Fed Penambuco Recife PE Brazil

ISBN: (纸本)9783030302412;9783030302405

The household appliances are becoming each time more connected to the others and to the internet. Beyond the necessity of improving and increasing the clean and renewable power sources, there is the urge for using the available power sources in more efficient manners. When the concepts of Internet of Things and Computational Intelligence converge, it is enabled a whole field of technologies aiming Smart Home functionality as dweller's comfort, tasks automation and energy saving. This work proposes a Smart Home appliances usage recommendation concept, based on multi-objective optimization to generate balanced recommendations regarding energy usage reduction and dweller's comfort. Those recommendations are also segmented according to the comfort priority of the dwellers in the room. In order to evaluate the priorities, it was implemented a Markov Chain to generate new dweller's presence data from the data set. It was also studied the potential of power saving of the Binary multi objective Particle Swarm optimization over contexts extracted from the data. Results showed that the recommendations have an average power saving potential of 9,76% as well as the possibility of deliver recommendations with different comfort levels according to the priority of the dwellers present in the room.

关键词： Binary Particle Swarm optimization Energy usage profiles Energy saving multi objective optimization Recommendation Smart Home Smart Home dweller comfort

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49页 << < 5 6 7 8 9 10 11 12 13 14 > >>

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：