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

4,456 篇 会议
296 篇 期刊文献
22 册 图书
17 篇 学位论文

馆藏范围

4,791 篇 电子文献
0 种 纸本馆藏

日期分布

学科分类号

2,855 篇 工学
- 1,391 篇 计算机科学与技术...
- 851 篇 控制科学与工程
- 721 篇 软件工程
- 572 篇 电气工程
- 403 篇 机械工程
- 225 篇 信息与通信工程
- 204 篇 化学工程与技术
- 194 篇 仪器科学与技术
- 187 篇 材料科学与工程（可...
- 149 篇 石油与天然气工程
- 148 篇 动力工程及工程热...
- 128 篇 力学（可授工学、理...
- 112 篇 电子科学与技术（可...
- 102 篇 土木工程
- 97 篇 航空宇航科学与技...
- 93 篇 交通运输工程
- 93 篇 安全科学与工程
- 92 篇 环境科学与工程（可...
- 80 篇 生物医学工程（可授...
- 68 篇 建筑学
1,066 篇 理学
- 501 篇 数学
- 391 篇 物理学
- 225 篇 统计学（可授理学、...
- 146 篇 化学
- 132 篇 系统科学
- 77 篇 生物学
549 篇 管理学
- 477 篇 管理科学与工程(可...
- 148 篇 工商管理
- 95 篇 图书情报与档案管...
124 篇 医学
- 93 篇 临床医学
58 篇 经济学
46 篇 法学
41 篇 农学
26 篇 教育学
13 篇 文学
11 篇 军事学
3 篇 艺术学

主题

466 篇 process control
458 篇 computational mo...
416 篇 data models
305 篇 analytical model...
223 篇 predictive model...
175 篇 mathematical mod...
145 篇 control systems
138 篇 data mining
112 篇 modeling
110 篇 monitoring
100 篇 data analysis
98 篇 biological syste...
96 篇 stability analys...
95 篇 principal compon...
88 篇 optimization
87 篇 training
86 篇 accuracy
84 篇 time series anal...
83 篇 neural networks
81 篇 solid modeling

机构

8 篇 college of infor...
7 篇 beijing univ tec...
7 篇 school of contro...
6 篇 anhui vocational...
6 篇 natl inst stand ...
6 篇 state key labora...
5 篇 china electric p...
5 篇 school of inform...
5 篇 georgia inst tec...
5 篇 faculty of infor...
5 篇 lipetsk state te...
5 篇 univ calif berke...
5 篇 beijing jiaotong...
4 篇 beijing lab smar...
4 篇 college of contr...
4 篇 ufa state aviati...
4 篇 nankai univ coll...
4 篇 university of ca...
4 篇 school of electr...
4 篇 east china univ ...

作者

9 篇 wang wei
9 篇 wei wang
8 篇 zhihuan song
8 篇 chunhui zhao
7 篇 tang jian
6 篇 zhao chunhui
6 篇 jian tang
5 篇 li xin
5 篇 liu tao
5 篇 spanos cj
5 篇 belangour abdess...
5 篇 zhiqiang ge
5 篇 s. joe qin
5 篇 qin s. joe
4 篇 weske mathias
4 篇 li yang
4 篇 may gary s.
4 篇 fuli wang
4 篇 biswas gautam
4 篇 hong chen

语言

4,494 篇 英文
256 篇 其他
47 篇 中文
3 篇 俄文
1 篇 西班牙文

检索条件"任意字段=Conference on Data Analysis and Modeling for Process Control II"

共 4791 条记录，以下是461-470 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：

Uncertainty Estimation in Machine Learning

Uncertainty Estimation in Machine Learning

引用

2023 International Russian Smart Industry conference, SmartIndustryCon 2023

作者： Arkov, V. Ufa University of Science and Technology Automated Control and Management Dept. Ufa Russia

ISBN: (纸本)9781665464291

Most machine learning techniques are based upon statistical learning theory, often simplified for the sake of computing speed. This paper is focused on the uncertainty aspect of mathematical modeling in machine learning. Regression analysis is chosen to further investigate the evaluation aspect of uncertainty in model coefficients and, more importantly, in the output feature value predictions. A survey demonstrates major stages in the conventional least squares approach to the creation of the regression model, along with its uncertainty estimation. On the other hand, it is shown that in machine learning the model complexity and severe nonlinearity become serious obstacles to uncertainty evaluation. Furthermore, the process of machine model training demands high computing power, not available at the level of personal computers. This is why so-called pre-Trained models are widely used in such areas of machine learning as natural language processing. The latest example of a pre-Trained model is the Generative Pre-Trained Transformer 3 with hundreds of billions of parameters and a half-Terabyte training dataset. Similarly, mathematical models built from real data are growing in complexity which is accompanied by the growing amount of training data. However, when machine models and their predictions are used in decision-making, one needs to estimate uncertainty and evaluate accompanying risks. This problem could be resolved with non-parametric techniques at the expense of greater demand for computing power, which can be offered by modern supercomputers available, including those utilizing graphical and tensor processing units along with the conventional central processors. © 2023 IEEE.

关键词： Forecasting

来源：评论

学校读者我要写书评

暂无评论

Discrete Events based Simulated Trading and Research System 18

Discrete Events based Simulated Trading and Research System

引用

18th International conference on the European Energy Market (EEM)

作者： Feng, Zejian Zhu, Shouzhen Bai, Xiaomin Tsinghua Univ Dept Elect Engn Beijing 100084 Peoples R China Beijing SmartChina Energy Co Ltd Beijing 100084 Peoples R China China Elect Power Res Inst Beijing 100192 Peoples R China

ISBN: (数字)9781665408967

ISBN: (纸本)9781665408967

High penetration of variable renewable generation burdens Transmission System Operators (TSO) with operational and market challenges, such as electricity price spikes, negative electricity prices, and even branch outages. It is imperative for market players to acquire knowledge about the impacts and influences of their behaviors and unexpected events on electricity markets through simulated trading and predictions of price fluctuation trends and possible outages. TSOs have published their market data to benefit market players for their studies on market trends. However, a further step for TSOs to take is more meaningful to promote market efficiencies, which is designing and operating a Simulated Trading and Research System (STRS). We propose a Discrete Event Dynamic System (DEDS) based modeling and simulation approach to design STRS. STRS can process such events as fluctuations of high penetration variable renewable, market players' expectations, weather and temperatures, sporting events, etc. The predictions that STRS simulates include impacts on electricity prices, electricity volumes, market powers, social welfare distributions, etc. caused by the above events. STRS implements reinforce learning architecture as a critical component. By looking ahead predictions of electricity market states, STRS helps the electricity market adapt to a forward observable closed-loop system by feeding a Model Predictive control (MPC) actor component. As a sensitivity analysis framework, STRS connects history market data with electricity market efficiency. A case study shows the pathways of promotion of electricity market efficiency by using STRS to achieve the prediction and perturbation analysis of event-driven price and volume levels, Pareto efficiencies and social welfares.

关键词： Discrete Event Dynamic System Perturbation analysis Electricity Market Efficiency Reinforce Learning Forecasting and Simulation

来源：评论

学校读者我要写书评

暂无评论

Review of VSG for industrial process data regression modeling 40

Review of VSG for industrial process data regression modelin...

引用

40th Chinese control conference (CCC)

作者： Wang, Dandan Tang, Jian Qiao, Junfei Beijing Univ Technol Fac Informat Technol Beijing 100124 Peoples R China Beijing Key Lab Computat Intelligence & Intellige Beijing 100124 Peoples R China Beijing Lab Smart Environm Protect Beijing 100124 Peoples R China

ISBN: (纸本)9789881563804

In complex industrial processes, accurate prediction of difficult-to-detect parameters such as product quality and environmental indicators based on data-driven modeling is helpful for the realization of intelligent detection, parameter optimization and intelligent control. However, the acquisition of the truth value of the difficult-to-detect parameters is limited by detection technology, labor cost and economic cost. Therefore, the modeling samples have problems such as insufficient feature information, large information gap and unbalanced distribution. That leads to the poor generalization performance of the difficult-to-detect parameter prediction model. The method of generating virtual samples by filling the information gap between small samples can expand the number of samples, thereby improving the accuracy of model prediction. In view of this, virtual sample generation (VSG) for industrial process data regression modeling is reviewed in this paper. Firstly, the definition of VSG, characteristics of small-sample data of industrial processes and their causes are described. Then, VSG methods are reviewed from three perspectives, i.e., small-sample distribution, interpolation and optimization. Next, through the comparative analysis of the existing VSG methods, the corresponding research difficulties are put forward. Finally, we summarize the existing problems and look forward to the future research direction.

关键词： Industrial process data-driven modeling Regression modeling Sample distribution Sample interpolation Virtual sample generation

来源：评论

学校读者我要写书评

暂无评论

A Gap analysis of Current CCDC Standard Contract Documents and Provisions for Successful BIM-Enabled Projects in Canada

A Gap Analysis of Current CCDC Standard Contract Documents a...

引用

Annual conference of the Canadian Society of Civil Engineering, CSCE 2021

作者： Mahbod, S. Iordavona, I. Poirier, E. École de Technologie Supérieure Quebec Canada

ISBN: (纸本)9789811910289

Building Information modeling (BIM) emphasizes the importance of information flow, communication, and collaboration amongst team members. Successful implementation of BIM is helping the industry move from traditional project delivery systems to integrated ones. This transition, however, requires reliable and concrete contractual mechanisms to provide guidance and structure. Risk allocation, role definition, and legal dimensions have been achieved through a series of contractual functions such as control, coordination, and contingency. While past scientific publications have investigated the impact of contracts on BIM and vice-versa, questions remain as to how these realization mechanisms interact with BIM requirements and legal issues. This study aimed at understanding the influence of contractual language and legal aspects on BIM-enabled projects. To do so, an in-depth literature review was performed in multiple rounds. Problematic issues in contracts were identified, including contractual complexity, emphasis on controlling provisions, contract incompleteness and missing or unclear legal clauses. Then a coding system was created based on the legal factors identified. The results indicate that current standardized contracts in Canada are incomplete and ill-adapted to support effective BIM implementation. The key elements such as intellectual property, ownership of data, responsibilities regarding the production and control of critical project data and asset information are underrated or overlooked. While efforts have been made to counter this (e.g., IBC BIM contract appendix and BIM Execution Plans), these efforts remain fragmented and bespoke for the most part, which introduces variability in the contracting process and therefore impacts the BIM implementation process at the project level. © 2023, Canadian Society for Civil Engineering.

关键词： Architectural design

来源：评论

学校读者我要写书评

暂无评论

modeling and predictive control of networked systems via physics-informed neural networks

Modeling and predictive control of networked systems via phy...

引用

IEEE conference on Decision and control

作者： Laura Boca de Giuli Alessio La Bella Marcello Farina Riccardo Scattolini Dipartimento di Elettronica Informazione e Bioingegneria Politecnico di Milano Milan Italy

ISBN: (数字)9798350316339

ISBN: (纸本)9798350316346

This article addresses the data-driven modeling and predictive control of networked systems. The main contribution is a novel methodology to develop a physics-informed recurrent neural network (PI-RNN) model with guaranteed stability properties. The idea consists in interconnecting multiple RNNs consistently with the known physical topology of the networked system, and in jointly training them while enforcing conditions guaranteeing the input-to-state stability of the PIRNN model. The stability properties of the proposed PI-RNN model pave the way for the design of (i) a decentralized state observer and (ii) a Nonlinear Model Predictive control (NMPC) regulator with convergence guarantees. The presented strategies are tested on a realistic large-scale networked system, i.e., a district heating network, demonstrating promising results from both the modeling and the control design perspective.

关键词： Training Adaptation models Recurrent neural networks Network topology Predictive models Stability analysis Topology Standards Predictive control Convergence

来源：评论

学校读者我要写书评

暂无评论

process Industry System modeling Based on Time Series Imputation: A Case Study of Paste Thickener

Process Industry System Modeling Based on Time Series Imputa...

引用

Automation in Manufacturing, Transportation and Logistics (ICaMaL), International conference on

作者： Xiaorui Li Xiaojuan Ban Yizhou Shao Haowei Chen Chao Yao Zhaolin Yuan Guangsheng Liu Lijie Guo Institute of Artificial Intelligence University of Science and Technology Beijing Beijing China School of Artificial Intelligence Hebei University of Technology Beijing China School of Computer and Communication Engineering University of Science and Technology Beijing Beijing China Department of Industrial and Systems Engineering Hong Kong Polytechnic University Hong Kong China BGRIMM Technology Group Beijing China

ISBN: (数字)9798350378658

ISBN: (纸本)9798350378665

In process CPS systems, highly accurate modeling of the production system is essential for optimal control, fault diagnosis, and flexible manufacturing. Traditional data-driven modeling of industrial processes focuses on predicting future trends based on variable periodicity and trends, often neglecting the impact of control variables. This paper proposes a new approach to improve CPS accuracy, particularly for systems heavily influenced by controlled variables. Firstly, CPS modeling is redefined as a time series imputation problem, introducing exogenous variables via a sequence modeling algorithm based on a state space model to enhance forecasting accuracy. Secondly, sequence inputs are encoded in patches, improving the model's ability to process local sequence information. The proposed method is evaluated on a real deep cone thickener underflow concentration forecasting task and compared with state-of-the-art time series forecasting methods, demonstrating superior performance. This study not only provides a more accurate model for CPS but also offers a framework for integrating control variables into predictive modeling.

关键词： Accuracy Time series analysis process control Predictive models Systems modeling Prediction algorithms Market research Imputation Manufacturing Forecasting

来源：评论

学校读者我要写书评

暂无评论

A deep-learning method for modeling geometric deviations of complex surfaces 33

A deep-learning method for modeling geometric deviations of ...

引用

33rd CIRP Design conference

作者： Ruan, Jianhao Qie, Yifan Anwer, Nabil Yin, Yuehong Robotics Institute Shanghai Jiao Tong University Shanghai200240 China Université Paris-Saclay ENS Paris-Saclay LURPA Gif-sur-Yvette91190 France

Parts with complex surfaces have become increasingly exploited due to advanced manufacturing processes. The extensive use of these complex parts in industry in recent years has led to new challenges within the design process when simulating their geometric defects for function assessment, quality control and tolerance analysis. Compared to mechanical parts with regular geometric surfaces and well-established geometrical specification standards, the geometry of complex surfaces is often difficult to be represented by explicit parameters or processed by feature operations, which poses challenges to the modelling and simulation of geometric deviations. Skin Model Shapes (SMSs) enable a discrete representation of surface deviations that allows the storage, simulation and analysis of shapes' geometric variations, and have been successfully applied for canonical geometries. In this paper, a method for generating geometric deviations on parts with complex surface based on deep learning is proposed. Laplace-Beltrami Operator (LBO) is exploited to encode geometric deviations as manufacturing signature and deviations patterns. After pre-processing steps, deviation patterns selected from modal decomposition are used as training data for the mesh Convolutional Neural Networks (CNN), which establishes the links between patterns and parts' manufacturing factors, and transferred to target shapes. Geometric deviations are generated on target shapes by linear combination of the transferred patterns with respect to manufacturing signature. A case study is implemented from an open dataset to illustrate the proposed method. The simulated geometric deviations show their effectiveness and potential to improve the design process and the manufacturing accuracy of parts with complex surfaces. © 2023 The Authors. Published by Elsevier B.V. This is an open access article under the CC BY-NC-ND license (https://***/licenses/by-nc-nd/4.0)

关键词： Quality control

来源：评论

学校读者我要写书评

暂无评论

Discovering Instance Spanning Exceptions from process Execution Logs 24

Discovering Instance Spanning Exceptions from Process Execut...

引用

24th IEEE International conference on Business Informatics (CBI)

作者： Stertz, Florian Winter, Karolin Rinderle-Ma, Stefanie Univ Vienna Fac Comp Sci Vienna Austria Tech Univ Munich Dept Informat Munich Germany

ISBN: (数字)9781665460163

ISBN: (纸本)9781665460163

Exceptions in process execution occur frequently and require appropriate handling strategies in order to avoid undesired consequences. For quality control in manufacturing processes, for example, when a blade gets missing, the set of affected instances is put on hold until the blade is found. As it can be seen from this example, the exception affects multiple instances and is hence denoted as instance spanning exception. Exceptions leave footprints in the process execution logs of the affected instances. Hence, process execution logs provide a valuable data source for discovering and analyzing exceptions. However, the discovery of instance spanning exceptions is still an open challenge. Thus, this paper proposes i) a classification of instance spanning exceptions based on literature and a set of real-world examples, followed by ii) a description of how instance spanning exceptions manifest in process execution logs along with an elicitation of minimal requirements for enabling their discovery, and iii) five instance spanning exception discovery algorithms, one for each class. The discovery algorithms are implemented and evaluated on a set of synthetic process execution logs reflecting real-world instance spanning exceptions and on a real-world process execution log from the public transport domain demonstrating the feasibility as well as applicability of the presented algorithms.

关键词： Instance Spanning Exceptions Exception Discovery and Handling process analysis and Improvement process Aware Information Systems

来源：评论

学校读者我要写书评

暂无评论

Generalized data Distribution Iteration 39

Generalized Data Distribution Iteration

引用

39th International conference on Machine Learning (ICML)

作者： Fan, Jiajun Xiao, Changnan Tsinghua Univ Tsinghua Shenzhen Int Grad Sch Beijing Peoples R China ByteDance Beijing Peoples R China

To obtain higher sample efficiency and superior final performance simultaneously has been one of the major challenges for deep reinforcement learning (DRL). Previous work could handle one of these challenges but typically failed to address them concurrently. In this paper, we try to tackle these two challenges simultaneously. To achieve this, we firstly decouple these challenges into two classic RL problems: data richness and exploration-exploitation trade-off. Then, we cast these two problems into the training data distribution optimization problem, namely to obtain desired training data within limited interactions, and address them concurrently via i) explicit modeling and control of the capacity and diversity of behavior policy and ii) more fine-grained and adaptive control of selective/sampling distribution of the behavior policy using a monotonic data distribution optimization. Finally, we integrate this process into Generalized Policy Iteration (GPI) and obtain a more general framework called Generalized data Distribution Iteration (GDI). We use the GDI framework to introduce operator-based versions of well-known RL methods from DQN to Agent57. Theoretical guarantee of the superiority of GDI compared with GPI is concluded. We also demonstrate our state-of-the-art (SOTA) performance on Arcade Learning Environment (ALE), wherein our algorithm has achieved 9620.33% mean human normalized score (HNS), 1146.39% median HNS and surpassed 22 human world records using only 200M training frames. Our performance is comparable to Agent57's while we consume 500 times less data. We argue that there is still a long way to go before obtaining real superhuman agents in ALE.

关键词：

来源：评论

学校读者我要写书评

暂无评论

4th International conference on Intelligent Systems in Production Engineering and Maintenance , ISPEM 2023

4th International Conference on Intelligent Systems in Produ...

引用

4th International conference on Intelligent Systems in Production Engineering and Maintenance , ISPEM 2023

ISBN: (纸本)9783031450204

The proceedings contain 44 papers. The special focus in this conference is on Intelligent Systems in Production Engineering and Maintenance. The topics include: Information Design Management of Machining Parts on Metal Cutting Machines;Virtual Training at ELLA Platform – The Case Study;web Application for the Learning of Emotions in Children with Autism Spectrum Disorder;lean Manufacturing Knowledge Correlation Model;assessment of the Effectiveness of Six Sigma Methodology Implementation - A Literature Review;analysis of Basic Characteristics of Textile Yarn Using Image processing Techniques;modeling the Impact of Leadership on Change Management Decisions Using System Dynamics Simulation;Using an ISO 9001 Based Framework as a Benchmark to Identify Best Practices Used by Sri Lankan Practitioners when Selecting Suppliers;requirements for Flow control Systems for Discrete Production of Mechanical Products;NIRF Imaging with Indocyanine Green (ICG) in a Veterinary Minimally Invasive Surgery;an Augmented System Based on Machine Learning for Boccia Assisted Gameplay;Ultrasound Tissue Differentiation (UTC) an Objective Diagnostic Tool in Prevention and Healing Monitoring Tendon Problems in Race Horses;location of Obstacles on Transport Routes in a Centralized Multi-agent System;converging data Mesh and Microservice Principles into a Unified Logical Architecture;Development and Comparative analysis of IT Tools Supporting data processing in Custom Manufacturing of Orthoses;design of Experiments: An Overview and Future Paths;SOC Evaluation of Lithium-ion Battery Based on MFC Sensors;indicators of Hierarchical Structure Model of Supporting the Production Management process – A Framework;gamification-Based Crowdsourcing as a Tool for New Product Development in Manufacturing Companies.

关键词：

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480页 << < 43 44 45 46 47 48 49 50 51 52 > >>

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：