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
133 篇 期刊文献

馆藏范围

344 篇 电子文献
0 种 纸本馆藏

日期分布

学科分类号

217 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
- 34 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

333 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 344 条记录，以下是1-10 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：

Improve Accuracy of VGG-16 Neural Network Based Face Detection with Data Augmentation 6

Improve Accuracy of VGG-16 Neural Network Based Face Detecti...

引用

6th IEEE International Conference on Artificial Intelligence in engineering and Technology, IICAIET 2024

作者： Tan, Min Keng Chin, Jun Shen Chin, Renee Ka Yin Angeline, Lorita Liau, Chung Fan Teo, Kenneth Tze Kin Universiti Malaysia Sabah Modelling Simulation & Computing Laboratory Faculty of Engineering Kota Kinabalu Malaysia

ISBN: (纸本)9798350389692

A face detection model can be used to detect the presence of a face in real time detection with great accuracy. However, the face detection model can only perform well under a very optimum condition and situation which makes it unreliable and unrealistic as it should be able to perform detection under normal conditions. Geometric transformation, color transformation and even kernel filters will affect the face detection model and will cause the detection model to not function and cause misclassification. A convolutional neural network (CNN) of Visual Geometry Group 16 (VGG-16) will be utilized to train the dataset and optimize the face detection model. The objective of this work is to mitigate the high loss and misclassification by performing image augmentations towards the data and analyze which augmentations parameters are ideal for the face detection model. The mixed augmentation selection method was proposed to solve the problem of not being able to detect face under different conditions. The result of different parameters and augmentations selections have been analyzed and compared and upon fine-tuning of parameters, the accuracy can be increase to 96.4% from the initial 74.4%. © 2024 IEEE.

关键词： Convolutional neural networks

来源：评论

学校读者我要写书评

暂无评论

Optimization of Photovoltaic Energy Harvesting Using Clonal Selection Algorithm 5

Optimization of Photovoltaic Energy Harvesting Using Clonal ...

引用

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

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

ISBN: (纸本)9798350304152

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. © 2023 IEEE.

关键词： Renewable energy resources

来源：评论

学校读者我要写书评

暂无评论

Multi-Area Load Frequency Control Using Particle Swarm Optimization 5

Multi-Area Load Frequency Control Using Particle Swarm Optim...

引用

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

作者： Tan, Min Keng Lim, Wei Han Lim, Kit Guan Kow, Wei Yeang Ng, Min Sian Kin Teo, Kenneth Tze Universiti Malaysia Sabah Modelling Simulation & Computing Laboratory Faculty of Engineering Kota Kinabalu Malaysia

ISBN: (纸本)9798350304152

Load Frequency Control is indeed important in any country that operates an interconnected power grid for regulating system frequency by adjusting the generation to match the load demand. To maintain the power system stability and improve efficiency in scheduling, this paper proposes Two-area Load Frequency Control (LFC) Optimization with Particle Swarm Optimization. The design process begins with understanding the fundamental concepts, starting from Automotive Generation Control in a single-area power system design and progressing to LFC design in a two-area power system. The two-area power system consists of Tie-line Bias Control (TLBC) for maintaining zero tie-line power and Area Control Error (ACE) for stabilizing system frequency. To achieve fitness results in simulations, this paper presents three modeling designs: conventional design, controller design, and controller design with PSO. The controller system with PSO leads an evaluation of 53.4 % time schedule in system frequency performance and an evaluation of 76.9% time schedule in generation power deviation with respect to the conventional model. In addition, the controller system lags an evaluation of 70.0% time schedule in system frequency performance and an evaluation of a 78.7% time schedule in generation power deviation with respect to the conventional model. © 2023 IEEE.

关键词： Controllers

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 5

Simulation and Batch Modelling of Microbial Biosurfactant Pr...

引用

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

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

ISBN: (纸本)9798350304152

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 1/60 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 1.5 g/L, 2.0g/L, 2.5g/L, 3.0g/L and 3.5 g/L for parameter testing and the initial concentrations of biosurfactant and cell concentration are 0.02 g/L and 0.02 g/L respectively, while the initial interfacial tension is set at 70.8933 mN/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 concentration where IFT is reduced from 70 ± 0.5 mN/m to 38 ± mN/m, but exhibited decreasing value of biosurfactant concentration defined at 0.5 micelle concentration (based on experimental value). © 2023 IEEE.

关键词： Bioremediation

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 6

Adaptive Traffic Signal Control using Genetic Algorithm for ...

引用

6th IEEE International Conference on Artificial Intelligence in engineering and Technology, IICAIET 2024

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

ISBN: (纸本)9798350389692

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× 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. © 2024 IEEE.

关键词： Genetic algorithms

来源：评论

学校读者我要写书评

暂无评论

AloT-Driven Machine Learning for Anomaly Detection in Structural Health Monitoring 6

AloT-Driven Machine Learning for Anomaly Detection in Struct...

引用

6th IEEE International Conference on Artificial Intelligence in engineering and Technology, IICAIET 2024

作者： Angeline, Lorita Lim, Kit Guan Tan, Min Keng Uda, Muhd. Nur Afnan Jenarun, Joaquim Abel Teo, Kenneth Tze Kin Universiti Malaysia Sabah Modelling Simulation & Computing Laboratory Faculty of Engineering Kota Kinabalu Malaysia Universiti Malaysia Sabah Faculty of Engineering Kota Kinabalu Malaysia

ISBN: (纸本)9798350389692

Structural health monitoring (SHM) is crucial for real-time assessment of structures to preemptively detect anomalies that may lead to failures. This study explores the integration of Artificial Intelligence of Things (AIoT) principles to enhance anomaly detection using acceleration and gyroscopic sensor data. The study involved setting up hardware comprising acceleration and gyroscopic sensors, integrated with a web server for real-time data monitoring. Issues with the raw dataset, including noise and variability, were addressed through preprocessing techniques. Four machine learning models, Support Vector Machine (SVM), Random Forest, Gradient Boosting, and Neural Network were evaluated on preprocessed data, focusing on recall as critical for anomaly detection in SHM. Models trained on reduced datasets showed varied performance compared to those using large, raw datasets, which, while computationally intensive, exhibited similar performance. SMOTE significantly improved recall, achieving 93.94% in Random Forest after correcting class imbalance and reducing dataset size. The findings underscore the potential of AIoT-driven machine learning approaches, to significantly enhance SHM modelling. By leveraging these technologies, infrastructure management can be fortified with more reliable anomaly detection capabilities, ensuring heightened safety and resilience in the AIoT era. © 2024 IEEE.

关键词： Gyroscopes

来源：评论

学校读者我要写书评

暂无评论

Effect of Cooling Channel Structure on Permanent Magnet Synchronous Motor 6

Effect of Cooling Channel Structure on Permanent Magnet Sync...

引用

6th IEEE International Conference on Artificial Intelligence in engineering and Technology, IICAIET 2024

作者： Huang, Zhencai Chen, Hui Lim, Kit Guan Tan, Min Keng Chua, Bih Lii Teo, Kenneth Tze Kin Universiti Malaysia Sabah Modelling Simulation & Computing Laboratory Faculty of Engineering Kota Kinabalu Malaysia School of Automotive Engineering Liuzhou Polytechnic University Liu Zhou China

ISBN: (纸本)9798350389692

Taking the 135kW magnet synchronous motor as the research object, the CFD simulation was used to analyze the influence of spiral-type runner, single-channel circumferential Z-type runner, and axial Z-type runner on the heat dissipation performance of the motor. The maximum temperature of the inner wall of the shell is 358.93K, compared with the single-channel circumferential Z-type runner and axial Z-type runner decreased by 1.69K, 10.65K and 46.47K, respectively. The velocity uniformity and pressure loss of the helical runner is optimal, and the coefficient of velocity uniformity and the difference between import and export pressure are 0.948 and 14.78kpa, respectively;the runner structure of the PM synchronous motor can be preferred to consider the use of the helical runner form. © 2024 IEEE.

关键词： Permanent magnets

来源：评论

学校读者我要写书评

暂无评论

Impact of Helical Channel Number on Synchronous Motor Cooling Performance 6

Impact of Helical Channel Number on Synchronous Motor Coolin...

引用

6th IEEE International Conference on Artificial Intelligence in engineering and Technology, IICAIET 2024

作者： Meng, Xiang Lei Chen, Hui Tan, Min Keng Lim, Kit Guan Chua, Bih Lii Te, Kenneth Tze Kin Universiti Malaysia Sabah Modelling Simulation & Computing Laboratory Faculty of Engineering Kota Kinabalu Malaysia School of Automotive Engineering Liuzhou Polytechnic University Liu Zhou China

ISBN: (纸本)9798350389692

In order to deeply explore the specific influence of the number of helical channels on the cooling performance of a motor, we carefully constructed a three-dimensional fluid-solid coupling calculation model of the flow channel with the help of CFD simulation technology. For the helical flow channels of the 135-k water-cooled permanent magnet synchronous motor shell, we conducted detailed numerical simulation calculations of the temperature field, velocity field, and pressure field. The results show that the number of helical channels has a direct impact on the cooling performance of the motor. Specifically, when the number of channels increases from 3 to 7, the maximum temperature on the inner wall of the shell decreases significantly by 94.41-k, and the velocity uniformity coefficient also increases by 0.05. However, this change also leads to an increase in the flow resistance within the channels, resulting in an increase in the pressure difference between the inlet and outlet of the channels by 4.73-kpa. These findings provide powerful data support for us to further optimize motor design and improve cooling performance. © 2024 IEEE.

关键词： Permanent magnets

来源：评论

学校读者我要写书评

暂无评论

Yield Optimization for Exothermic Batch Process Using Particle Swarm Optimization 6

Yield Optimization for Exothermic Batch Process Using Partic...

引用

6th IEEE International Conference on Artificial Intelligence in engineering and Technology, IICAIET 2024

作者： Tan, Min Keng Bansing, Matthew Laurentius Xu, Huiyi Chuo, Helen Sin Ee Tham, Heng Jin Teo, Kenneth Tze Kin Universiti Malaysia Sabah Modelling Simulation & Computing Laboratory Faculty of Engineering Kota Kinabalu Malaysia School of Marine Science and Engineering Hainan Tropical Ocean University Hainan China

ISBN: (纸本)9798350389692

Modern advancements in optimizing processes have been explored by various researchers, particularly for exothermic batch processes, which are prolific in the chemical and pharmaceutical industries. This paper proposes using artificial intelligence, specifically particle swarm optimization (PSO), to enhance these exothermic batch processes. Given that most exothermic batch processes utilize generic model control (GMC), the PSO algorithm will primarily focus on optimizing the control of the GMC within the process. The precise control of the controllers will aim to maintain the reactor temperature during the processes, ensuring stability and efficiency. This approach leverages AI to improve process performance, highlighting the potential of PSO in industrial applications. The proposed algorithm is shown to be able to produce a result of an increase of 4.5% of production of the desired product, while decreasing by-product production of 97%. The time it takes for the production of the desired product is also improved by 11.8%. This shows an efficiency increase of the entire exothermic batch processes, The results show that an improvement of the efficiency of the process makes the proposed algorithm a great method to improve the controller of the processes. © 2024 IEEE.

关键词： Particle swarm optimization (PSO)

来源：评论

学校读者我要写书评

暂无评论

Adaptive Exponential Feeding Control for a Fedbatch Yeast Fermentation Process Using Reinforcement Learning 6

Adaptive Exponential Feeding Control for a Fedbatch Yeast Fe...

引用

6th IEEE International Conference on Artificial Intelligence in engineering and Technology, IICAIET 2024

作者： Sodiwal, Khairul Aznizam Chai, Wan Ying Tan, Min Keng Kin Teo, Kenneth Tze Tham, Heng Jin Chemical Engineering Programme Faculty of Engineering Universiti Malaysia Sabah Kota Kinabalu88400 Malaysia Universiti Malaysia Sabah Modelling Simulation & Computing Laboratory Faculty of Engineering Kota Kinabalu Malaysia

ISBN: (纸本)9798350389692

The fermentation process is complex and nonlinear because the growth pattern of microorganisms is sensitive to environmental conditions. Exponential feeding (EF) is a common and simple control strategy for regulating substrate feed flow rates using a pre-determined calculation based on growth kinetics. However, this method does not adapt to changes in the fermentation process. Reinforcement Learning (RL) is a subset of Artificial Intelligence (AI) that focuses on teaching optimal behaviors through interaction with an environment using rewards or penalties. This work explores an Adaptive Exponential Feeding (AEF) control using RL to determine the gain value of the feeding rate, aimed at maximizing yeast concentration and minimizing the by-product formation in a fed-batch baker's yeast fermentation. The kinetic and dynamic behavior of the fermentation process was modeled and simulated using MATLAB. The AEF approach uses an RL agent to optimize the feeding rate by interacting with the fermentation environment and selecting actions based on yeast concentration, glucose levels, and ethanol changes. The gain value ranges from 0 to 2.5 with a 0.1 interval. After iterations, the optimal policy is obtained. simulations with four different initial yeast and substrate concentrations showed that AEF significantly improved the fermentation performance, yielding a higher yeast concentration of 64.86 g/L compared to 44.68 g/L with EF, a 45.17 % increase, and reducing ethanol formation by 0.15 g/L. This adaptive approach demonstrates potential for enhanced efficiency and productivity in industrial fermentation processes. © 2024 IEEE.

关键词： Reinforcement learning

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：