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

152 篇 会议
26 篇 期刊文献

馆藏范围

178 篇 电子文献
0 种 纸本馆藏

日期分布

学科分类号

105 篇 工学
- 80 篇 计算机科学与技术...
- 63 篇 软件工程
- 33 篇 信息与通信工程
- 27 篇 电气工程
- 24 篇 动力工程及工程热...
- 22 篇 控制科学与工程
- 20 篇 电子科学与技术（可...
- 16 篇 交通运输工程
- 14 篇 机械工程
- 10 篇 光学工程
- 10 篇 生物工程
- 9 篇 化学工程与技术
- 8 篇 安全科学与工程
- 7 篇 力学（可授工学、理...
- 5 篇 仪器科学与技术
- 4 篇 生物医学工程（可授...
- 3 篇 水利工程
- 3 篇 农业工程
67 篇 理学
- 52 篇 数学
- 13 篇 物理学
- 11 篇 化学
- 11 篇 统计学（可授理学、...
- 9 篇 生物学
- 3 篇 系统科学
- 2 篇 海洋科学
23 篇 管理学
- 14 篇 管理科学与工程(可...
- 9 篇 图书情报与档案管...
- 5 篇 工商管理
5 篇 农学
- 5 篇 作物学
2 篇 经济学
- 2 篇 应用经济学
2 篇 医学
1 篇 法学

主题

25 篇 genetic algorith...
11 篇 vehicles
10 篇 image segmentati...
10 篇 optimization
8 篇 fuzzy logic
8 篇 wireless sensor ...
7 篇 computational mo...
7 篇 network coding
6 篇 clustering algor...
6 篇 mathematical mod...
5 篇 simulation
5 篇 target tracking
5 篇 biological cells
5 篇 adaptation model...
4 篇 base stations
4 篇 ant colony optim...
4 篇 traffic control
4 篇 wireless communi...
4 篇 neural networks
4 篇 protocols

机构

37 篇 modelling simula...
24 篇 modelling simula...
20 篇 universiti malay...
13 篇 modelling simula...
12 篇 universiti malay...
12 篇 modelling simula...
8 篇 modelling simula...
7 篇 school of electr...
7 篇 modelling simula...
7 篇 wuyi university ...
6 篇 faculty of medic...
5 篇 faculty of engin...
5 篇 faculty of compu...
4 篇 school of automo...
4 篇 universiti malay...
4 篇 modelling simula...
3 篇 faculty of the i...
3 篇 fujian polytechn...
3 篇 department of el...
3 篇 modelling simula...

作者

59 篇 teo kenneth tze ...
53 篇 kenneth tze kin ...
52 篇 tan min keng
39 篇 lim kit guan
29 篇 min keng tan
23 篇 kin teo kenneth ...
21 篇 kit guan lim
13 篇 ee chuo helen si...
13 篇 chin renee ka yi...
11 篇 teo k.t.k.
11 篇 angeline lorita
11 篇 zhan wei siew
10 篇 k.t.k. teo
10 篇 yang soo siang
10 篇 renee ka yin chi...
9 篇 chua bih lii
9 篇 yit kwong chin
9 篇 helen sin ee chu...
9 篇 siew zhan wei
8 篇 liau chung fan

语言

163 篇 英文
15 篇 其他

检索条件"机构=Modelling Simulation and Computing Laboratory"

共 178 条记录，以下是61-70 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：

Autonomous Path Optimization in Unfamiliar Map Through Deep Reinforcement Learning

Autonomous Path Optimization in Unfamiliar Map Through Deep ...

引用

IEEE International Conference on Artificial Intelligence in Engineering and Technology (IICAIET)

作者： Longxin Wei Kit Guan Lim Min Keng Tan Chung Fan Liau Tianlei Wang Kenneth Tze Kin Teo Modelling Simulation & Computing Laboratory Faculty of Engineering Universiti Malaysia Sabah Kota Kinabalu Malaysia Faculty of The Internet of Things and Artificial Intelligence Fujian Polytechnic of Information Technology Fuzhou China Faculty of Intelligent Manufacturing Wuyi University Jiangmen China

The application of mobile robot's path planning and navigation in known map scenarios has been well-established. However, with the absence of a known map, the challenge lies in how a robot can effectively navigate through an unfamiliar environment and generate a sensible path towards its destination. This paper delves into the path planning quandary that mobile robot encountered in unknown environments. It employs a deep reinforcement learning (DRL) algorithm within a simulated environment, where the robot explores its objective. Additionally, an enhanced reward selection strategy is introduced through a performance-based comparison. This strategy tackles issues such as robot freezing and high collision rates during the exploration of uncharted territory. The outcome of this study is an enhancement in search performance and learning efficiency within path planning. The integration of this algorithm into the Robot Operating System (ROS) robot simulation platform, coupled with testing within the Gazebo simulation environment, demonstrates that the proposed strategy effectively diminishes obstacle collisions and boosts the success rate of reaching the intended destination.

关键词：

来源：评论

学校读者我要写书评

暂无评论

Improved Q-Learning Algorithm for Path Planning of an Automated Guided Vehicle (AGV)

Improved Q-Learning Algorithm for Path Planning of an Automa...

引用

IEEE International Conference on Artificial Intelligence in Engineering and Technology (IICAIET)

作者： Hao Guo Min Keng Tan Kit Guan Lim Helen Sin Ee Chuo Baojian Yang Kenneth Tze Kin Teo Modelling Simulation & Computing Laboratory Faculty of Engineering Universiti Malaysia Sabah Kota Kinabalu Malaysia Department of Automation Baotou Light Industry Vocational and Technical College Baotou City China Department of Intelligent Manufacturing Wuyi University Jiangmen China

With the development of modern industry 4.0, intelligent path planning is an essential research direction of schedule systems for an automated guided vehicle (AGV), which has been widely used in logistics distribution centers of enterprises. This work implements the improved Q-learning algorithm to solve the typical obstacle avoidance problems in path planning. Specifically, the conventional Q-learning algorithm has shortcomings including low operational efficiency and slow learning speed. The improved Q-learning algorithm is successively proposed by adding a learning process based on the original Q-learning algorithm, which enables AGV to find obstacles and target locations within the shortest time, thus improving the efficiency of path planning. Finally, the simulation experiments are carried out in the grid environment with MATLAB. In comparison to the conventional Q-learning algorithm, the improved Q-learning algorithm has faster convergence and higher learning efficiency, improved by 20%.

关键词：

来源：评论

学校读者我要写书评

暂无评论

Advancing Weed Detection in Agricultural Landscapes Using Computer Vision

Advancing Weed Detection in Agricultural Landscapes Using Co...

引用

IEEE International Conference on Artificial Intelligence in Engineering and Technology (IICAIET)

作者： Bei Ren Tan Ervin Moung Muhd. Nur Afnan Uda Kenneth Tze Kin Teo Lorita Angeline School of Computer Science Taylor's University Subang Jaya Malaysia Faculty of Computing and Informatics Universiti Malaysia Sabah Kota Kinabalu Malaysia Faculty of Engineering Universiti Malaysia Sabah Kota Kinabalu Malaysia Modelling Simulation & Computing Laboratory Faculty of Engineering Universiti Malaysia Sabah Kota Kinabalu Malaysia

This paper explores the need for weed detection in agricultural landscapes, where weed infestations pose significant crop productivity challenges. To address this matter, computer vision techniques are utilised to create a weed detection algorithm that accurately detects weed patches inside agricultural field images. To ensure reliable model evaluation, the dataset is split into training and testing subsets before being fed into the YOLOv3 model. The YOLOv3 model performs well in terms of precision, with an average precision of 66.4 % for crop regions and a notable precision of 92.5% for detecting weeds. These results highlight the potential of artificial intelligence-driven weed detection techniques to optimize crop management practices and foster sustainable agriculture in the modern era. This research advances precision agriculture by effectively addressing weed infestations, paving the way for more efficient and targeted weed control strategies, which ultimately lead to increased crop yield and improved agricultural sustainability.

关键词：

来源：评论

学校读者我要写书评

暂无评论

Safe Following Distance Analysis for Traffic Cellular Automata modelling 6

Safe Following Distance Analysis for Traffic Cellular Automa...

引用

6th IEEE International Conference on Engineering, Technologies and Applied Sciences, ICETAS 2019

作者： Angeline, Lorita Choong, Mei Yeen Tan, Min Keng Liau, Chung Fan Chin, Renee Ka Yin Teo, Kenneth Tze Kin Modelling Simulation Computing Laboratory Artificial Intelligence Research Unit Faculty of Engineering Universiti Malaysia Sabah Kota Kinabalu Malaysia

ISBN: (数字)9781728140827

ISBN: (纸本)9781728140827

Following another vehicle too close is known as tailgating. Tailgater may not have enough space and time to avoid a collision. Thus there is a need for a fundamental understanding on factors affecting safe distance between vehicles. This paper aims to study such factors and to adopt certain rules and principles into the proposed traffic cellular automata model. Rule of seconds is applied and some deductions are made to attain a realistic traffic model. The simulation also entail human reaction time in perceiving safe distance with the leading vehicle and the simulation results are as expected. However there is a trade off between reaction time and an optimum safe following distance. Hence ideal reaction time of 0.75s is selected to emulate real life traffic flow without deteriorating traffic stability. © 2019 IEEE.

关键词： Cellular automata

来源：评论

学校读者我要写书评

暂无评论

Adapting Perturbation Voltage in PV Array with Power Point Tracking and Differential Evolution 6

Adapting Perturbation Voltage in PV Array with Power Point T...

引用

6th IEEE International Conference on Engineering, Technologies and Applied Sciences, ICETAS 2019

作者： Kamaruddin, Nurul Izyan Haron, Ahmad Razani Tan, Min Keng Yang, Soo Siang Goh, Hui Hwang Teo, Kenneth Tze Kin Modelling Simulation Computing Laboratory Artificial Intelligence Research Unit Faculty of Engineering Universiti Malaysia Sabah Kota Kinabalu Malaysia School of Electrical Engineering Guangxi University Nanning China

ISBN: (纸本)9781728140827

The power output of photovoltaic array may reduce as the photovoltaic panels' connection close to each other and lead to the occurrence of partials shading. Under partial shading condition, the unshaded modules of PV array receive solar irradiation at higher level, while the shaded module of PV array receives lower irradiation. Thus, multiple maximum power point also will occur under the partial shading condition. The proposed modelling in this paper is 4×4 PV array and tested two different conditions in partial shading condition (PSC) where there are random irradiance values that had been set. Therefore, this paper aim to model more than one PV array and the platform modelling for this paper is 4×4 PV array. Besides that, explore the conventional method which is Perturb and Observe (PO) based MPPT controller in optimizing the efficiency of the PV array. Unfortunately, the conventional method only can trap the power at the local maximum power under partial shading conditions. Thus, the proposed algorithm that used to track the maximum power is differential evolution (DE) in order to improve the power output of the PV array. The simulation results shows the proposed DE able to track the global MPP. © 2019 IEEE.

关键词： Maximum power point trackers

来源：评论

学校读者我要写书评

暂无评论

Improvement of Particle Swarm Optimization in Multi-Robot Trajectory Motion Coordination 6

Improvement of Particle Swarm Optimization in Multi-Robot Tr...

引用

6th IEEE International Conference on Engineering, Technologies and Applied Sciences, ICETAS 2019

作者： Tang, Nyiak Tien Lee, Jun Wei Lim, Kit Guan Tan, Min Keng Wang, Tianlei Teo, Kenneth Tze Kin Modelling Simulation Computing Laboratory Artificial Intelligence Research Unit Faculty of Engineering Universiti Malaysia Sabah Kota Kinabalu Malaysia Wuyi University Department of Intelligent Manufacturing Jiangmen China

ISBN: (纸本)9781728140827

In swarm robotics, motion coordination is being viewed as a whole system consists of multiple robots each with different velocity and path being optimized. This research focus on improve an optimization process called Particle Swarm Optimization (PSO) by altering the fitness function from static to dynamic. PSO has tendency to being trapped in local optima. By employing dynamic acceleration coefficient, the position of particles will be less dependent on the global best position if the global best fitness is found to be saturated in the region and hence release the swarm to another region for searching in other unexplored region. Nominal, dynamic and extreme scenarios were employed to test the performance between PSO and dynamic coefficient PSO. The different on expected optimization time between DCPSO and PSO for nominal condition is DCPSO lead only 0.26 second. While in dynamic condition the different is DCPSO lead 1.09 second. For extreme condition, the different become significant, which DCPSO lead 3.58 second. © 2019 IEEE.

关键词： Swarm intelligence

来源：评论

学校读者我要写书评

暂无评论

Comparative Study of Temperature Control using Metaheuristic and Non-metaheuristic Controllers 6

Comparative Study of Temperature Control using Metaheuristic...

引用

6th IEEE International Conference on Engineering, Technologies and Applied Sciences, ICETAS 2019

作者： Tan, Min Keng Yeo, Kiam Beng Tham, Heng Jin Yang, Soo Siang Hussain, Mohamed Azlan Teo, Kenneth Tze Kin Modelling Simulation Computing Laboratory Artificial Intelligence Research Unit Faculty of Engineering Universiti Malaysia Sabah Kota Kinabalu Malaysia Faculty of Medicine and Health Sciences Universiti Malaysia Sabah Kota Kinabalu Malaysia

ISBN: (纸本)9781728140827

This paper presents a metaheuristic-based temperature controller for an exothermic batch process. Developing a suitable temperature controller for an exothermic process is a challenging task because large amount of heat is released rapidly during the process. The exothermic behavior will further increase the reaction rate and cause more heat to be liberated. As the result, the improper temperature control might cause the reaction becomes unstable and consequently poses safety concern to the plant personnel and equipment. The conventional non-metaheuristic-based controller, such as fuzzy logic requires empirical data or knowledge about the total amount heat released while developing its fuzzy rules and membership functions for precision control. However, the detailed kinetic model of the heat released is unable to be obtained since there are several unobservable parameters during the process, such as the energy held in the reactor and jacket walls. Therefore, particle swarm optimization algorithm (PSO) is proposed as the controller to maintain the reactor temperature at the desired trajectory by manipulating the inlet jacket fluid temperature and flow rate. The simulation results show the proposed PSO produces better performances in terms of minimizing fluctuation in control actions and overshooting as compared with the conventional fuzzy logic controller. © 2019 IEEE.

关键词： Temperature control

来源：评论

学校读者我要写书评

暂无评论

Genetic Algorithm based Chain Leader Election in Wireless Sensor Network for Precision Farming

Genetic Algorithm based Chain Leader Election in Wireless Se...

引用

2020 IEEE International Conference on Artificial Intelligence in Engineering and Technology, IICAIET 2020

作者： Hamzah, Hamzarul Alif Tuah, Norah Lim, Kit Guan Tan, Min Keng Saad, Ismail Teo, Kenneth Tze Kin Modelling Simulation Computing Laboratory Universiti Malaysia Sabah Faculty of Engineering Kota Kinabalu Malaysia Universiti Teknologi Mara Faculty of Computer and Mathematical Sciences Kota Kinabalu Malaysia Universiti Malaysia Sabah Faculty of Engineering Kota Kinabalu Malaysia

ISBN: (纸本)9781728169460

Wireless Sensor Network (WSN) is one of the commonly used technologies in Precision Farming (PF). It provides farmers with accurate real-time information on their farms. In practice, WSN consists of numerous wireless sensor nodes, where each node relies on limited energy sources such as battery to maintain its operation. The energy management issue in WSN has gained attention of scholars, leading to new protocols or schemes developed over the years. Conventionally, PEGASIS protocol selects chain leader without considering the distance and residual energy level of each sensor node. As such, it might increase the energy consumption rate to transmit collected data from sensor node to sink. Inadequate energy management leads to rapid energy drain and eventually shorten the lifespan of WSN. Therefore, this study aims to prolong the lifespan of WSN while minimizing the energy consumption. Genetic Algorithm (GA) is proposed to enhance the chain leader selection scheme of the conventional PEGASIS. The proposed GA will select optimum chain leader by considering the energy consumption rate of each node. As such, the proposed algorithm is able to increase node's transmission as well as improve the lifespan of WSN by 50% as compared to the conventional approach. © 2020 IEEE.

关键词： Genetic algorithms

来源：评论

学校读者我要写书评

暂无评论

Metaheuristic Multi-Hop Clustering Optimization for Energy-Efficient Wireless Sensor Network

Metaheuristic Multi-Hop Clustering Optimization for Energy-E...

引用

2020 IEEE International Conference on Artificial Intelligence in Engineering and Technology, IICAIET 2020

作者： Chung, Vincent Tuah, Norah Lim, Kit Guan Tan, Min Keng Saad, Ismail Kin Teo, Kenneth Tze Modelling Simulation Computing Laboratory Universiti Malaysia Sabah Faculty of Engineering Kota Kinabalu Malaysia Universiti Teknologi Mara Faculty of Computer and Mathematical Sciences Kota Kinabalu Malaysia Universiti Malaysia Sabah Faculty of Engineering Kota Kinabalu Malaysia

ISBN: (纸本)9781728169460

Energy-efficient optimization algorithm in wireless sensor network (WSN) is often based on solely cluster routing or multi-hop routing. The cluster optimization algorithm will form a cluster network by dividing the sensor nodes into few clusters where each cluster has a cluster head (CH) for data collection. On the other hand, multi-hop optimization algorithm will form a multi-hop network by transmitting data to base station (BS) through data multi-hopping between sensor nodes. However, cluster optimization algorithm suffers from the overburdens of CH nodes, while multi-hop optimization algorithm suffers from the overburdens of nodes which are near to the BS. Therefore, Genetic Algorithm-Cuckoo Search (GACS) is proposed and developed based on the multi-hop clustering model in this paper. GACS optimizes both intra-cluster and inter-cluster communications to enhance energy efficiency in WSN, extending the network lifetime. Based on the performance evaluation, GACS outperforms both Genetic Algorithm (GA)-based cluster optimization algorithm and Cuckoo Search (CS)-based multi-hop optimization algorithm. © 2020 IEEE.

关键词： Genetic algorithms

来源：评论

学校读者我要写书评

暂无评论

Impact of Genetic Operators on Energy-Efficient Wireless Sensor Network 6

Impact of Genetic Operators on Energy-Efficient Wireless Sen...

引用

6th IEEE International Conference on Engineering, Technologies and Applied Sciences, ICETAS 2019

作者： Chung, Vincent Tuah, Norah Lim, Kit Guan Tan, Min Keng Huang, Hui Teo, Kenneth Tze Kin Modelling Simulation Computing Laboratory Artificial Intelligence Research Unit Faculty of Engineering Universiti Malaysia Sabah Kota Kinabalu Malaysia Faculty of Computer and Mathematical Sciences Universiti Teknologi Mara Kota Kinabalu Malaysia Wuyi University Department of Intelligent Manufacturing Jiangmen China

ISBN: (纸本)9781728140827

The metaheuristic genetic algorithm is an evolutionary algorithm which means that it will always evolve to get an optimum solution. Due to this intrinsic characteristic, the conventional genetic algorithm might be trapped at local optimum when dealing with a global optimization problem that consists of several maximum points. As such, this paper aims to explore the potential of improving the genetic algorithm by manipulating its operators. With different procedures in selection and replacement operators, the genetic algorithm is be able to compute more efficiently. This mechanism is introduced to prevent the proposed algorithm to be trapped at the local optimum point with shorter computation time. The robustness of the proposed algorithm is tested in optimizing a wireless sensor network (WSN) because the WSN will exhibit multiple peaks with different network configuration. The existence of multiple peaks will lead to additional difficulties for the conventional routing protocol algorithm in tracking the global optimum network configuration or known as global optima. The simulation results show the effect of proposed genetic algorithm with different combinations of operators. © 2019 IEEE.

关键词： Wireless sensor networks

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18页 << < 3 4 5 6 7 8 9 10 11 12 > >>

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：