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

36 篇 期刊文献
29 篇 会议
3 篇 学位论文

馆藏范围

68 篇 电子文献
0 种 纸本馆藏

日期分布

学科分类号

59 篇 工学
- 45 篇 计算机科学与技术...
- 19 篇 电气工程
- 9 篇 控制科学与工程
- 5 篇 信息与通信工程
- 3 篇 软件工程
- 2 篇 机械工程
- 2 篇 仪器科学与技术
- 2 篇 电子科学与技术（可...
- 2 篇 测绘科学与技术
- 1 篇 力学（可授工学、理...
- 1 篇 材料科学与工程（可...
- 1 篇 航空宇航科学与技...
- 1 篇 生物医学工程（可授...
12 篇 理学
- 4 篇 物理学
- 4 篇 生物学
- 3 篇 数学
- 2 篇 化学
- 1 篇 地理学
10 篇 管理学
- 10 篇 管理科学与工程(可...
- 1 篇 工商管理
2 篇 经济学
- 1 篇 理论经济学
2 篇 医学
- 2 篇 临床医学
1 篇 农学

主题

68 篇 swarm algorithms
10 篇 optimization
7 篇 bio-inspired alg...
6 篇 particle swarm o...
5 篇 evolutionary alg...
4 篇 constrained opti...
4 篇 bat algorithm
4 篇 genetic algorith...
3 篇 performance
3 篇 bison algorithm
3 篇 global optimizat...
3 篇 swarm intelligen...
3 篇 multiobjective o...
2 篇 global optimisat...
2 篇 time delay syste...
2 篇 metaheuristics
2 篇 algorithms
2 篇 parametric optim...
2 篇 path planning
2 篇 soma

机构

3 篇 brno university ...
2 篇 michigan state u...
2 篇 tomas bata univ ...
2 篇 univ delhi dyal ...
2 篇 mansoura univ fa...
2 篇 tomas bata univ ...
2 篇 zagazig univ fac...
2 篇 univ delhi dept ...
2 篇 univ delhi dept ...
2 篇 univ delhi dyal ...
1 篇 sakarya univ sak...
1 篇 ton duc thang un...
1 篇 telkom univ sch ...
1 篇 doon university ...
1 篇 sakarya univ fac...
1 篇 ain shams univ d...
1 篇 indian stat inst...
1 篇 anits dept comp ...
1 篇 silesian tech un...
1 篇 univ newcastle s...

作者

6 篇 senkerik roman
5 篇 pluhacek michal
5 篇 kazikova anezka
4 篇 viktorin adam
4 篇 banati hema
4 篇 chaudhary reshu
3 篇 zelinka ivan
3 篇 cuevas erik
3 篇 kadavy tomas
2 篇 abouhawwash moha...
2 篇 krohling renato ...
2 篇 cienfuegos migue...
2 篇 mohamed reda
2 篇 jameel mohammed
2 篇 perez-cisneros m...
2 篇 vega-rodriguez m...
2 篇 arsuaga-rios mar...
2 篇 tomaszek lukas
2 篇 oplatkova zuzana...
2 篇 abdel-basset moh...

语言

63 篇 英文
5 篇 其他

检索条件"主题词=Swarm Algorithms"

共 68 条记录，以下是41-50 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：

New Running Technique for the Bison Algorithm 17th

New Running Technique for the Bison Algorithm

引用

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

作者： Kazikova, Anezka Pluhacek, Michal Viktorin, Adam Senkerik, Roman Tomas Bata Univ Zlin Fac Appl TG Masaryka 5555 Zlin 76001 Czech Republic

ISBN: (纸本)9783319912530;9783319912523

This paper examines the performance of the Bison Algorithm with a new running technique. The Bison Algorithm was inspired by the typical behavior of bison herds: the swarming movement of endangered bison as the exploitation factor and the running as the exploration phase of the optimization. While the original running procedure allowed the running group to scatter throughout the search space, the new approach proposed in this paper preserves the initial formation of the running group throughout the optimization process. At the beginning of the paper, we introduce the Bison Algorithm and explain the new running technique procedure. Later the performance of the adjusted algorithm is tested and compared to the Particle swarm Optimization and the Cuckoo Search algorithm on the IEEE CEC 2017 benchmark set, consisting of 30 functions. Finally, we evaluate the meaning of the experiment outcomes for future research.

关键词： Bison Algorithm Running technique swarm algorithms

来源：评论

学校读者我要写书评

暂无评论

Maximizing Efficiency: A Comparative Study of SOMA Variants and Constraint Handling Methods for Time Delay System Optimization

Maximizing Efficiency: A Comparative Study of SOMA Variants ...

引用

Genetic and Evolutionary Computation Conference (GECCO)

作者： Senkerik, Roman Kadavy, Tomas Janku, Peter Pluhacek, Michal Guzowski, Hubert Pekar, Libor Matusu, Radek Viktorin, Adam Smolka, Maciej Byrski, Aleksander Oplatkova, Zuzana Kominkova Tomas Bata Univ Zlin Zlin Czech Republic AGH Univ Sci & Technol Krakow Poland

ISBN: (纸本)9798400701207

This paper presents an experimental study that compares four adaptive variants of the self-organizing migrating algorithm (SOMA). Each variant uses three different constraint handling methods for the optimization of a time delay system model. The paper emphasizes the importance of metaheuristic algorithms in control engineering for time-delayed systems to develop more effective and efficient control strategies and precise model identifications. The study includes a detailed description of the selected variants of the SOMA and the adaptive mechanisms used. A complex workflow of experiments is described, and the results and discussion are presented. The experimental results highlight the effectiveness of the SOMA variants with specific constraint handling methods for time delay system optimization. Overall, this study contributes to the understanding of the challenges and advantages of using metaheuristic algorithms in control engineering for time delay systems. The results provide valuable insights into the performance of the SOMA variants and can help guide the selection of appropriate constraint handling methods and the adaptive mechanisms of metaheuristics.

关键词： SOMA swarm algorithms parametric optimization time delay system

来源：评论

学校读者我要写书评

暂无评论

Leveraging Large Language Models for the Generation of Novel Metaheuristic Optimization algorithms

Leveraging Large Language Models for the Generation of Novel...

引用

Genetic and Evolutionary Computation Conference (GECCO)

作者： Pluhacek, Michal Kazikova, Anezka Kadavy, Tomas Viktorin, Adam Senkerik, Roman Tomas Bata Univ Zlin Zlin Czech Republic

ISBN: (纸本)9798400701207

In this paper, we investigate the potential of using Large Language Models (LLMs) such as GPT-4 to generate novel hybrid swarm intelligence optimization algorithms. We use the LLM to identify and decompose six well-performing swarm algorithms for continuous optimization: Particle swarm Optimization (PSO), Cuckoo Search (CS), Artificial Bee Colony (ABC), Grey Wolf Optimizer (GWO), Self-Organizing Migrating Algorithm (SOMA), and Whale Optimization Algorithm (WOA). We leverage GPT-4 to propose a hybrid algorithm that combines the strengths of these techniques for two distinct use-case scenarios. Our focus is on the process itself and various challenges that emerge during the use of GPT-4 to fulfill a series of set tasks. Furthermore, we discuss the potential impact of LLM-generated algorithms in the metaheuristics domain and explore future research directions.

关键词： Large Language Models Metaheuristic Optimization swarm algorithms Algorithm Generation Decomposition and Construction GPT-4

来源：评论

学校读者我要写书评

暂无评论

Biologically Inspired Optimization for Antenna Impedance Matching

Biologically Inspired Optimization for Antenna Impedance Mat...

引用

IEEE SoutheastCon Conference

作者： Homsup, Nuttaka Homsup, Nathawut Kasetsart Univ Elect Engn Dept Bangkok 10900 Thailand Penn State Univ Dept Elect Engn University Pk PA 16802 USA

ISBN: (纸本)9781538661338

Antenna design solutions and algorithms have been developed in order to satisfy the increasing needs from the technology advancement of communication system. One of the promising approaches is the biologically inspired optimization algorithm. Examples of these algorithms are Genetic Algorithm (GA), Particle swarm Optimization (PSO), Ant Colony Optimization (ACO), and Firefly Algorithm (FA). Although GA and PSO have been used as the solution for antenna design problems for decades, ACO and FA are relatively new algorithms for this field of problems. In this paper, these optimization methods were tested to tackle one of the electromagnetic problems, the antenna impedance matching problem.

关键词： Impedance matching swarm algorithms Biologically inspired optimization

来源：评论

学校读者我要写书评

暂无评论

Reducing swarming theory to practice for UAV control

Reducing swarming theory to practice for UAV control

引用

IEEE Aerospace Conference

作者： Hart, DM Craig-Hart, PA Cyberneut Inc Reston VA 20190 USA

ISBN: (纸本)0780381556

The introduction or increasingly sophisticated unmanned aerial vehicles (UAVs) into the U.S. force structure has shown that the cognitive operator burden increases with the technical complexity of the robot. It takes more humans to control advanced UAVs than simple ones, and this burden is bound to increase when there are more UAVs to control. One promising approach for reducing the ratio of operators to UAVs can be found in a robotic theory that mimics emerging systems found in nature - swarming. An examination of the state-of-the art in swarm intelligence applications in the academic, commercial, and military research community indicates that this approach to robotic control may be achieving the critical mass necessary to exit the laboratory, but, despite its promise, swarm robotic control software is technically far behind its target hardware. This paper explores opportunities for reducing robotic swarming theory to practice for UAVs by identifying candidate swarm algorithms, examples of their utility to military robotics, and the challenges associated with swarm programming. We conclude with a systematic, theory-driven approach to metrics for gaining an accurate picture of man/machine team performance.

关键词： military computing military aircraft remotely operated vehicles aircraft control telerobotics man-machine systems multi-robot systems mobile robots cooperative systems swarming theory UAV control unmanned aerial vehicles US force structure robotic theory swarm intelligence swarm robotic control software swarm algorithms military robotics swarm programming military computing Aircraft control Man-Machine Systems Unmanned vehicles Telerobots multi-robot systems Particle swarm optimization military aircraft cooperative systems Mobile robots Robot control swarming

来源：评论

学校读者我要写书评

暂无评论

Directed Artificial Bat Algorithm (DABA) A New Bio-Inspired Algorithm

Directed Artificial Bat Algorithm (DABA) A New Bio-Inspired ...

引用

2nd International Conference on Advances in Computing, Communications and Informatics (ICACCI)

作者： Rekaby, Amr ERSIL Cairo Egypt

ISBN: (纸本)9781479924325;9781479926596

Bio-inspired artificial algorithms topic is a relatively modern part of metaheuristic track in artificial intelligence field. All these algorithms are inspired from natural biological animals' behaviors like ants, bees, and others. The importance of these algorithms is increased by time due to the complex scientific applications, and other optimization problems demand. In this paper, we introduce a new innovative algorithm. It is titled as "Directed Artificial Bat Algorithm" (DABA) which is inspired from bats' echo system and how they use it in prey finding. Previous initial contributions related to bat behaviors are mentioned in this paper, but they are truly abstract trials. That is why the comparisons are done versus artificial bee colony algorithm due to its maturity. According to the comparisons, proposed DABA achieves better results than ABC with efficiency enhancements between 5% and 10%.

关键词： Bat Algorithm Directed Artificial Bat Algorithm swarm algorithms Bio-inspired algorithms

来源：评论

学校读者我要写书评

暂无评论

A controllable sensor management algorithm capable of learning

A controllable sensor management algorithm capable of learni...

引用

Conference on Multisensor, Multisource Information Fusion

作者： Osadciw, L Veeramacheneni, K Syracuse Univ Syracuse NY 13244 USA

ISBN: (纸本)0819457981

Sensor management technology progress is challenged by the geographic space it spans, the heterogeneity of the sensors, and the real-time timeframes within which plans controlling the assets are executed. This paper presents a new sensor management paradigm and demonstrates its application in a sensor management algorithm designed for a biometric access control system. This approach consists of an artificial intelligence (AI) algorithm focused on uncertainty measures, which makes the high level decisions to reduce uncertainties and interfaces with the user, integrated cohesively with a bottom up evolutionary algorithm, which optimizes the sensor network's operation as deter-mined by the AI algorithm. The sensor management algorithm presented is composed of a Bayesian network, the AI algorithm component, and a swarm optimization algorithm, the evolutionary algorithm. Thus, the algorithm can change its own performance goals in real-time and will modify its own decisions based on observed measures within the sensor network. The definition of the measures as well as the Bayesian network determine the robustness of the algorithm and its utility in reacting dynamically to changes in the global system.

关键词： sensor networks sensor management data fusion swarm algorithms Bayesian networks

来源：评论

学校读者我要写书评

暂无评论

Robust and Scalable swarming of Quadruped Robots for Chemical, Biological, Radiological, and Nuclear Source Localisation 10

Robust and Scalable Swarming of Quadruped Robots for Chemica...

引用

10th International Conference on Mechatronics and Robotics Engineering (ICMRE)

作者： Islam, Rafiqul Anavatti, Sreenatha Kasmarik, Kathryn Garratt, Matt UNSW Canberra SET Canberra Australia

ISBN: (纸本)9798350394283;9798350394276

In this paper, a robust and scalable method for the localisation of Chemical, Biological, Radiological, and Nuclear (CBRN) sources is introduced using a swarm of quadruped robots. A cornerstone of this work is the development of an advanced simulation environment built on the Robot Operating System 2 (ROS2) and compatible with Gazebo. This environment features a sophisticated physics engine and supports a wide array of sensors, offering unprecedented scalability for a swarm of quadruped robot simulations. Following this, we present a novel swarming algorithm designed to exploit quadruped robots' unique kinematics. This algorithm is an enhanced extension of traditional Particle swarm Optimisation (PSO) and incorporates features such as obstacle avoidance, separation policies, velocity clamping and boundary constraints to optimise the CBRN source localisation process. To rigorously assess the robustness and efficacy of the proposed method, extensive experiments are conducted in three different environmental setups. The results reveal a remarkable convergence and success rate in CBRN source localisation, thereby substantiating the effectiveness of the proposed method.

关键词： CBRN Source Localisation swarm algorithms Autonomous Quadruped Navigation Multi-Robot Coordination

来源：评论

学校读者我要写书评

暂无评论

Why Bee colony is the most suitable with multi-query optimization? 5

Why Bee colony is the most suitable with multi-query optimiz...

引用

5th International Conference on Computing and Informatics (IEEE ICCI)

作者： AbdelGaber, Sayed Abdel-Fattah, Manal A. Nasr, S. A. Helwan Univ Fac Comp & Artificial Intelligence Postgrad Studies Cairo Egypt Helwan Univ Fac Comp & Artificial Intelligence Student Educ Cairo Egypt

ISBN: (纸本)9781665499736;9781665499729

This paper presents the comparison results on the performance of the swarm algorithms with Multi-Query Optimization (MQO). First the paper discusses query optimization process and the challenges appear when applied on multi query. Then the paper tackles swarm algorithms and how did they confront these challenges and achieve good results. Finally, proved that Artificial Bee Colony (ABC) algorithm achieves the best results in time and performance.

关键词： Multi Query optimization swarm algorithms Query optimization

来源：评论

学校读者我要写书评

暂无评论

Selected Topics of Artificial Intelligence in Robotics 7

Selected Topics of Artificial Intelligence in Robotics

引用

7th International Conference on Mechanical Engineering and Robotics Research (ICMERR)

作者： Kwiecien, Joanna AGH Univ Sci & Technol Dept Automat Control & Robot Al Mickiewicza 30 PL-30059 Krakow Poland

ISBN: (纸本)9781665490511

The paper is focused on the selected area of artificial intelligence (AI) applications, and presents only two examples relating to robotics and robotic systems. It is particularly interested in swarm intelligence method applied to path planning problems, and machine and deep learning approaches to anomaly detection. Based on existing methods of AI, we discuss important aspects for the application of AI technologies to view some research problems from robotics perspective.

关键词： path planning mobile robots anomaly detection artificial intelligence swarm 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7页 << < 1 2 3 4 5 6 7 > >>

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：