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

211 篇 会议
134 篇 期刊文献

馆藏范围

345 篇 电子文献
0 种 纸本馆藏

日期分布

学科分类号

218 篇 工学
- 113 篇 计算机科学与技术...
- 95 篇 软件工程
- 52 篇 电气工程
- 47 篇 动力工程及工程热...
- 44 篇 信息与通信工程
- 43 篇 电子科学与技术（可...
- 37 篇 控制科学与工程
- 35 篇 化学工程与技术
- 32 篇 力学（可授工学、理...
- 31 篇 材料科学与工程（可...
- 26 篇 机械工程
- 24 篇 光学工程
- 17 篇 交通运输工程
- 16 篇 土木工程
- 15 篇 冶金工程
- 15 篇 生物医学工程（可授...
- 15 篇 生物工程
- 13 篇 仪器科学与技术
- 11 篇 环境科学与工程（可...
- 8 篇 安全科学与工程
185 篇 理学
- 93 篇 物理学
- 89 篇 数学
- 29 篇 化学
- 21 篇 统计学（可授理学、...
- 15 篇 生物学
- 13 篇 系统科学
36 篇 管理学
- 21 篇 管理科学与工程(可...
- 15 篇 图书情报与档案管...
- 10 篇 工商管理
8 篇 农学
- 8 篇 作物学
8 篇 医学
4 篇 法学
2 篇 经济学
1 篇 教育学

主题

24 篇 genetic algorith...
12 篇 image segmentati...
11 篇 optimization
9 篇 mathematical mod...
8 篇 computational mo...
8 篇 vehicles
7 篇 fuzzy logic
6 篇 wireless sensor ...
6 篇 feature extracti...
5 篇 simulation
5 篇 computational fl...
5 篇 neural networks
5 篇 clustering algor...
5 篇 image color anal...
5 篇 accuracy
5 篇 shape
5 篇 adaptation model...
4 篇 ant colony optim...
4 篇 target tracking
4 篇 mobile robots

机构

37 篇 modelling simula...
24 篇 modelling simula...
20 篇 universiti malay...
13 篇 modelling simula...
9 篇 laboratory for s...
9 篇 jiangxi provinci...
8 篇 the modelling & ...
8 篇 modelling simula...
7 篇 school of electr...
7 篇 modelling simula...
7 篇 laboratory for s...
7 篇 international in...
7 篇 wuyi university ...
6 篇 department of ch...
5 篇 faculty of medic...
5 篇 faculty of engin...
5 篇 faculty of compu...
5 篇 universiti malay...
4 篇 school of automo...
4 篇 arc research hub...

作者

57 篇 teo kenneth tze ...
51 篇 tan min keng
40 篇 kenneth tze kin ...
38 篇 lim kit guan
28 篇 min keng tan
23 篇 kin teo kenneth ...
20 篇 kit guan lim
13 篇 ee chuo helen si...
12 篇 chin renee ka yi...
11 篇 teo k.t.k.
11 篇 angeline lorita
10 篇 k.t.k. teo
10 篇 yang soo siang
9 篇 aibing yu
9 篇 moldovanu simona
9 篇 siew zhan wei
8 篇 liau chung fan
8 篇 chua bih lii
8 篇 moraru luminita
8 篇 yu aibing

语言

334 篇 英文
7 篇 其他
3 篇 中文

检索条件"机构=Laboratory of Modelling and Simulation in Engineering"

共 345 条记录，以下是31-40 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：

Optimization of Photovoltaic Energy Harvesting Using Clonal Selection Algorithm

Optimization of Photovoltaic Energy Harvesting Using Clonal ...

引用

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

作者： Min Keng Tan Grace Butiza Joponi Kit Guan Lim Ahmad Razani Haron Chang-Yii Chai Kenneth Tze Kin Teo Modelling Simulation & Computing Laboratory Faculty of Engineering Universiti Malaysia Sabah Kota Kinabalu Malaysia

The rising demand for renewable energy sources has fueled extensive research in photovoltaic (PV) systems. However, conventional Maximum Power Point Tracking (MPPT) algorithms often encounter challenges when tracking the global maximum power point under non-uniform irradiance conditions. To address this issue, the Clonal Selection Algorithm (CSA) is proposed as an effective approach to enhance MPPT algorithm performance. The CSA dynamically adjusts the voltage perturbation size based on instant ambient irradiance and temperature, leading to improved global maximum power point tracking and enhanced efficiency in PV systems. Experimental results demonstrate the superiority of the proposed CSA over conventional MPPT algorithms, especially in scenarios with varying solar irradiance. The CSA's adaptability allows PV systems to operate closer to their optimal efficiency, maximizing energy harvest from available solar resources. Overall, this research contributes valuable insights into sustainable and efficient energy solutions by leveraging the capabilities of the CSA. Successfully integrating the CSA in PV systems plays a critical role in establishing an eco-friendly and resilient renewable energy infrastructure, for a greener future.

关键词：

来源：评论

学校读者我要写书评

暂无评论

simulation and Batch modelling of Microbial Biosurfactant Production

Simulation and Batch Modelling of Microbial Biosurfactant Pr...

引用

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

作者： Helen Sin Ee Chuo Andy Raymond Ramlan Kit Guan Lim Min Keng Tan Hou Pin Yoong Kenneth Tze Kin Teo Modelling Simulation & Computing Laboratory Faculty of Engineering Universiti Malaysia Sabah Kota Kinabalu Malaysia

This project concentrates on simulating the batch microbial biosurfactant production in crude oil and its interfacial tension response. Bacterial metabolism has been widely studied for its significant role in bioremediation of oil spill, which is proven capable of reducing the interfacial tension between oil and water. Therefore, this simulation is integrated to observe the metabolic behaviour of the bacteria of interest upon its uptake of carbon source from crude oil., biosurfactant production and the system's interfacial tension which are some of the outputs mainly being discussed within the culture system. The metabolic process in the crude oil batch is first modelled, then simulated in MATLAB software, and the results are verified through literature and process theories, while the model was validated using the experimental data. The simulation will use a step size of $\mathbf{1/60 \mathrm{h}\ .}$ equivalent to 60 seconds, set to a total of 11520 iterations for a running time of 8 days. Different crude oil substrate concentrations are set to $\mathbf{1.5 \mathrm{g}/\mathrm{L}, 2.0\mathrm{g}/\mathrm{L}, 2.5\mathrm{g}/\mathrm{L}, 3.0\mathrm{g}/\mathrm{L}}$ and $\mathbf{3.5 \mathrm{g}/\mathrm{L}}$ for parameter testing and the initial concentrations of biosurfactant and cell concentration are $\mathbf{0.02 \mathrm{g}/\mathrm{L}}$ and $\mathbf{0.02 \mathrm{g}/\mathrm{L}}$ respectively, while the initial interfacial tension is set at 70.8933 $\text{mN}/\mathrm{m}$ . The simulation outcome in this study signifies that the final concentrations of biosurfactant and bacteria cell increases with the increase in substrate concentration as crude oil degrades completely quicker with substrate concentration increase among culture batches obtained from the parameter testing. Additionally, the simulated interfacial tension profile plotted against biosurfactant from experimental research., showed similar profiles across batch cultures with an increasing substrate conce

关键词：

来源：评论

学校读者我要写书评

暂无评论

Advanced Fault Detection in DC Microgrid System using Reinforcement Learning 3

Advanced Fault Detection in DC Microgrid System using Reinfo...

引用

3rd IEEE International Conference on Artificial Intelligence in engineering and Technology, IICAIET 2021

作者： Tan, Min Keng Lee, Kar Leong Lim, Kit Guan Haron, Ahmad Razani Ibrahim, Pungut Teo, Kenneth Tze Kin Modelling Simulation Computing Laboratory Universiti Malaysia Sabah Faculty of Engineering Kota Kinabalu Malaysia

ISBN: (纸本)9781665428996

As technologies are expanding, the demand for power supply also increases. This causes the demand for power is difficult to be fulfilled as non-renewable sources are reducing. Therefore, the microgrid concept is introduced, where it is constructed with renewable energy sources, energy storage devices and loads. There are two types of microgrid, which are alternating current (AC) microgrid and direct current (DC) microgrid. Various research show that DC microgrid has more advantages over AC microgrid. However, DC microgrid is not widely used due to the lack of studies on it compared to AC microgrid. Besides, DC microgrid has one significant problem not fixed, which is the fault in the DC microgrid. Whenever a fault occurs, the whole DC microgrid will be affected rapidly. Therefore, this project aims to design a fault detector based on artificial intelligence to detect the fault and isolate the fault effectively. A fault detector based artificial intelligence should be implemented into the DC microgrid system to protect it. Two techniques in Artificial Immune System are being compared. The results showed that the improved Negative Selection Algorithm with variable sized detector has better performance than the general Negative Selection Algorithm with constant sized radius in detecting fault in DC microgrid system. © 2021 IEEE.

关键词： Reinforcement learning

来源：评论

学校读者我要写书评

暂无评论

Adaptive Traffic Signal Control using Genetic Algorithm for a 2×2 Traffic Network

Adaptive Traffic Signal Control using Genetic Algorithm for ...

引用

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

作者： Min Keng Tan Shun Quan Chai Helen Sin Ee Chuo Kit Guan Lim Hui Hwang Goh Kenneth Tze Kin Teo Modelling Simulation & Computing Laboratory Faculty of Engineering Universiti Malaysia Sabah Kota Kinabalu Malaysia School of Electrical Engineering Guangxi University Nanning China

ISBN: (数字)9798350389692

ISBN: (纸本)9798350389708

This paper proposes an adaptive traffic signal control (ATSC) system optimized using genetic algorithm (GA) to reduce travel delays at multiple intersections. The growing urban population has caused significant traffic congestion, leading to wasted time, higher costs, and fuel waste. The main aim is to enhance traffic optimization performance by improving ATSC signal timings at multiple intersections, optimized using GA. A $2\times 2$ grid traffic network is developed to represent the multi-agent network, and the GA-based traffic optimizer is formulated to optimize traffic signals based on the traffic inflow rate. The performance of the GA-based signal optimizer is evaluated and compared with pretimed traffic control based on the average delay and queue length of vehicles passing through the intersections in undersaturated and saturated traffic. The simulations results show a decrease of 4.7 % (1.7 s) in delay and 6.8 % (0.6 pcu) in queue length for GA-based traffic control during undersaturated traffic scenarios, and a decrease of 18.7 % (8.4 s) in delay and 14.1 % (1.8 pcu) in queue length during saturated traffic scenarios. These results highlight the effectiveness of the GA-based signal optimizer in managing traffic flow in a multi-agent-based signalized traffic network. This paper provided a valuable contribution to the field of traffic signal optimization, particularly in urban settings where congestion is a significant issue.

关键词： Adaptive systems simulation Traffic control Delays Fuels Artificial intelligence Optimization Traffic congestion Genetic algorithms Testing

来源：评论

学校读者我要写书评

暂无评论

Optimization of Yeast Fermentation Process using Genetic Algorithm 3

Optimization of Yeast Fermentation Process using Genetic Alg...

引用

3rd IEEE International Conference on Artificial Intelligence in engineering and Technology, IICAIET 2021

作者： Chuo, Helen Sin Ee Lo, Christine Yuh King Tan, Min Keng Tham, Heng Jin Kumaresan, Sivakumar Teo, Kenneth Tze Kin Modelling Simulation Computing Laboratory Universiti Malaysia Sabah Faculty of Engineering Kota Kinabalu Malaysia

ISBN: (纸本)9781665428996

This paper proposes genetic algorithm (GA) to optimize the productivity of yeast fermentation process. The proposed optimizer aims to maximize yeast productivity while minimizing the by-product of ethanol. Various initial glucose concentrations will affect yeast productivity and influence the performance of yeast fermentation. Yeast has relatively high ethanol production as compared with other microorganisms. Since the excessive ethanol formation in the yeast fermentation process will have a negative impact on quality of the product, it is needed to optimize glucose feeding rate at optimal level for maximizing the yeast productivity. The conventional open-loop feeding system is inadequate to minimize the growth of byproduct as the system will not regulate the glucose feeding rate based on the instant needs. Thus, GA is proposed to optimize the glucose feeding profile based on the instant concentration of yeast, glucose, oxygen and ethanol inside the fermentation tank. The results show the proposed GA can obtain a higher yield production of 95.3% as compared to the conventional open-loop system with 92.5% yield production. The results reveal that the optimal glucose feeding rate using GA is achieved satisfyingly and successfully. © 2021 IEEE.

关键词： Genetic algorithms

来源：评论

学校读者我要写书评

暂无评论

Enhanced Multi-Hop Mechanism in Vehicular Communication System using Swarm Algorithm 3

Enhanced Multi-Hop Mechanism in Vehicular Communication Syst...

引用

3rd IEEE International Conference on Artificial Intelligence in engineering and Technology, IICAIET 2021

作者： Lim, Kit Guan Teh, Ke Wen Tan, Min Keng Lago, Herwansyah Yang, Soo Siang Kin Teo, Kenneth Tze Modelling Simulation Computing Laboratory Universiti Malaysia Sabah Faculty of Engineering Kota Kinabalu Malaysia

ISBN: (纸本)9781665428996

As on-road vehicles are increasing every year, safety on the road has become one of the major concerns. Therefore, Vehicular Ad Hoc Network (VANET) becomes as an important role on the road. In VANET, communication occurs between vehicles and the infrastructures. During broadcasting, an emergency message is transferred to the surrounding vehicles to alert other vehicles in the area. However, blind flooding in wireless network might result in redundant rebroadcast, contentions and collision with the neighbouring nodes. This situation is named as broadcast storm. Broadcast storm might lead to the losses of the information or lead to the wrong information being transmitted to the neighbouring nodes. The paper aims to design a broadcast control system which is able to optimize the broadcast process in VANET. Vehicular network is modelled in simulation of Urban Mobility (SUMO) and the algorithm is formulated in MATLAB. Data is extracted from SUMO through Traffic Control Interface for MATLAB (TraCI4Matlab). The broadcast protocol and Particle Swarm Optimization (PSO) algorithm are formulated in this paper. At the same time PSO is modified for the broadcast enhancement. Results showed that after parameters tuning the modified PSO is able to broadcast into a larger coverage area at a faster rate. © 2021 IEEE.

关键词： Vehicular ad hoc networks

来源：评论

学校读者我要写书评

暂无评论

Optimization of Photovoltaic Energy Harvesting using Artificial Neural Network 3

Optimization of Photovoltaic Energy Harvesting using Artific...

引用

3rd IEEE International Conference on Artificial Intelligence in engineering and Technology, IICAIET 2021

作者： Tan, Min Keng Lim, Norman Kamaruddin, Nurul Izyan Lim, Kit Guan Yang, Soo Siang Teo, Kenneth Tze Kin Modelling Simulation Computing Laboratory Universiti Malaysia Sabah Faculty of Engineering Kota Kinabalu Malaysia

ISBN: (纸本)9781665428996

This paper proposes artificial neural network (ANN) based maximum power point tracking (MPPT) controller to maximize the energy harvested by a grid-connected photovoltaic (PV) system under various environmental conditions. Due to the non-linear characteristics, PV system will exhibit multiple peaks when the PV array receives non-uniform irradiance. As such, the conventional perturb and observe (PO) MPPT controller will be trapped at local maximum power point (MPP). Therefore, this paper aims to integrate ANN into MPPT controller to improve the effectiveness of the MPPT controller in tracking the global MPP. The effectiveness of the proposed method is tested under uniform and non-uniform irradiance conditions, and the performances are compared with the conventional PO. The simulation results show the proposed method able to track the global MPP even the PV system exhibits multiple peaks under non-uniform condition, whereas the conventional PO is trapped at local MPP. Thus, the proposed algorithm is able to harvest much energy as compared to the conventional method. © 2021 IEEE.

关键词： Neural networks

来源：评论

学校读者我要写书评

暂无评论

Optimization of Signalized Traffic Network using Swarm Intelligence 3

Optimization of Signalized Traffic Network using Swarm Intel...

引用

3rd IEEE International Conference on Artificial Intelligence in engineering and Technology, IICAIET 2021

作者： Tan, Min Keng Ladillah, Mohd.Riezman Chuo, Helen Sin Ee Lim, Kit Guan Chin, Renee Ka Yin Teo, Kenneth Tze Kin Modelling Simulation Computing Laboratory Universiti Malaysia Sabah Faculty of Engineering Kota Kinabalu Malaysia

ISBN: (纸本)9781665428996

Traffic lights are the signaling devices located at a road intersection for granting right-of-way movement to road users. Thus, optimization of traffic signalization is essential to improve road service as it is the cost-effective way. Commonly, the signal optimization aims to minimize the average travel delay by manipulating the green signal timing. Besides to optimize the signal timing, the local intersection controller needs to collaborate with neighboring intersection controllers for minimizing the average delay for whole network as the congestion will be propagated to the downstream intersection. However, the current fixed-time signal controller is inadequate to manage the high growing demands of traffic as it is tuned offline using the nominal traffic flow data. Thus, this work aims to explore the potential of using Particle Swarm Optimization (PSO) to optimize the traffic signal timing for the traffic network. The proposed algorithm is texted using a benchmarked 1x2 traffic model and its performances are compared with the classical Genetic Algorithm (GA). The simulated results show the proposed PSO has improved the performances in minimizing average travel delay by 3.94 %. © 2021 IEEE.

关键词： Controllers

来源：评论

学校读者我要写书评

暂无评论

Texture Analysis of Breast US Images Using Morphological Transforms, Hausdorff Dimension and Bagging Ensemble Method 32

Texture Analysis of Breast US Images Using Morphological Tra...

引用

32nd Mediterranean Conference on Control and Automation, MED 2024

作者： Tabacaru, Gigi Moldovanu, Simona Barbu, Marian 'Dunarea de Jos' University of Galati Faculty of Automation Computers Electrical Engineering and Electronics Department of Automatic Control and Electrical Engineering Romania 'Dunarea de Jos' University of Galati Computer Science and Information Technology Faculty of Automation Computers Electrical Engineering and Electronics Romania Dunarea de Jos University of Galati The Modelling & Simulation Laboratory Galati800008 Romania

ISBN: (纸本)9798350395440

In this work, an attempt is made for the first time to use the measurement pattern generated by morphological transformation quantified by Hausdorff fractal dimension (HFD) and classified with ensemble learning based on bagging. The proposed work uses three morphological transformations for image preprocessing: hit-and-miss transform (HMT), white (WHT), and black top-hat (BHT). The pattern texture of US breast images is described by extracting the HFD from the regions of interest (ROI) after the ultrasound (US) images have been preprocessed. The main objective of this study was achieved by comparatively analyzing the classification performance of features using the Random Forest (RF), Extra Trees (ET) classifier, and bagging ensemble method based on XGBoot classifier. In presented study, the XGBoost classifier and BHT image processing method give an accuracy of 89.8% in a binary classification, benign versus malignant breast cancer. © 2024 IEEE.

关键词： Fractal dimension

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) 5

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

引用

5th IEEE International Conference on Artificial Intelligence in engineering and Technology, IICAIET 2023

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

ISBN: (纸本)9798350304152

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%. © 2023 IEEE.

关键词： Motion planning

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35页 << < 1 2 3 4 5 6 7 8 9 10 > >>

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：