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

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A Continuous-Time Optimal control Approach to Congestion control

A Continuous-Time Optimal Control Approach to Congestion Con...

引用

European control conference (ECC)

作者： Uppaluru, Harshvardhan Liu, Xun Emadi, Hamid Rastgoftar, Hossein Univ Arizona Aerosp & Mech Engn Dept Tucson AZ 85721 USA Villanova Univ Mech Engn Dept Villanova PA 19085 USA

ISBN: (数字)9783907144077

ISBN: (纸本)9783907144077

Traffic congestion has become a nightmare to modern life in metropolitan cities. On average, a driver spending X hours a year stuck in traffic is one of most common sentences we often read regarding traffic congestion. Our aim in this article is to provide a method to control this seemingly ever-growing problem of traffic congestion. We model traffic dynamics using a continuous-time mass-flow conservation law, and apply optimal control techniques to control traffic congestion. First, we apply the mass-flow conservation law to specify traffic feasibility and present continuous-time dynamics for modeling traffic as a network problem by defining a network of interconnected roads (NOIR). The traffic congestion control is formulated as a boundary control problem and we use the concept of statetransition matrix to help with the optimization of boundary flow by solving a constrained optimal control problem using quadratic programming in MATLAB. Finally, we show that the proposed algorithm is successful by simulating on a network of interconnected roads based on the street map of Phoenix city.

关键词： Roads Urban areas Optimal control process control Mathematical models Stability analysis Quadratic programming

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analysis of Operational data and Self-learning control Rules for Mining Mill Equipment

Analysis of Operational Data and Self-learning Control Rules...

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Asian control conference

作者： Guicheng Wang Liang Yuan Zhicheng Bai Guoliang Cai Ning Hua Xiaobin Li School of Electrical and Electronics Engineering Shanghai Institute of Technology Shanghai China State Key Laboratory of Intelligent Optimized Manufacturing in Mining & Metallurgy Process and Beijing Key Laboratory of Process Automation in Mining & Metallurgy Beijing China Zijin Intelligent Control (Xiamen) Technology Co. Ltd. Xiamen China

ISBN: (数字)9789887581598

ISBN: (纸本)9798331540845

The engineering application under industrial big-data analysis is of great significance for improving the optimization effect of enterprise production process control processes. By analyzing the operating principle of the semi-automatic mill and studying its control optimization strategy, based on the operational data of the SAG mill, industrial big-data analysis is adopted to self-learning its control optimization rules. Firstly, SPSS is used to preprocess the high-dimensional process data generated during the operation of the semi-automatic mill. Four parameters, namely power, axial pressure, grinding sound, and grinding concentration, are preliminarily selected. Then, PCA is used to screen and reduce the dimensionality of multidimensional data, and K-Means clustering algorithm is used to classify and identify the reduced dataset. After simulation research, the results show that PCA can reduce the redundancy of SAG mill operation data, and the control optimization rules formed by self-learning can serve as operational guidance for improving the efficiency and energy-saving of SAG mill operation. The effectiveness can be further verified in practical engineering applications in the later stage.

关键词： Dimensionality reduction Energy consumption Technological innovation Redundancy Force process control Clustering algorithms

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Research on Risk Situation Awareness and Prediction Method of Industrial control Systems 4

Research on Risk Situation Awareness and Prediction Method o...

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4th International conference on System Reliability and Safety Engineering (SRSE)

作者： Zhang, Chao Chen, Sijuan Yang, Ming Zhu, Ruoyu Sun, Jiajun State Nucl Power Automat Syst Engn Co Dept Sci & Technol Innovat Shanghai Peoples R China Shenzhen Univ Inst Adv Study Nucl Energy & Safety Coll Phys & Optoelect Engn Shenzhen Guangdong Peoples R China State Nucl Power Automat Syst Engn Co Power Plant Control Ctr Shanghai Peoples R China

ISBN: (纸本)9781665473880

In the operation process of the power plant, in addition to the operating state information of the power plant process systems and components is monitored by Industrial control Systems (ICSs), a large number of the operating state information of ICSs and its components themselves can be obtained. These information helps operators to understand the operation safety state of ICSs themselves, and whether ICSs operate reliably, which plays an important role in maintaining the normal operation of the power plant, controlling abnormal events and mitigating the development of accidents. This paper proposes an integrated methodological framework for real-time risk awareness and prediction of ICS based on the particle filtering model whose features are updating monitoring data and predicting the state transition process, and focus on the measurement of risk states, identification of critical risk states and key components, modeling of the state transition process, prediction of risk levels and estimation of remaining arrival time of high-risk residual. The assumption that the transition probability matrix of system states does not change over time in traditional Markov predictions is discarded in this proposed method. Compared with the traditional ICS safety analysis method, this method can provide global and systemic risk insights for ICS risk situation, with a better real-time performance, and it is a kind of more scientific and objective measurement for ICS risk situation.

关键词： Industrial control systems (ICSs) risk situation awareness residual risk time prediction

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AI-Assisted data modeling and High-Resolution Image Synthesis: An Interactive Framework with Latent Diffusion Model Visualization

AI-Assisted Data Modeling and High-Resolution Image Synthesi...

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Intelligent control, Computing and Communications (IC3), International conference on

作者： Asha Rani Borah Archana K. Pushpa Rani Sajjad Ziara Sorabh Lakhanpal Chalasanvi Vidyadhari Department of Computer Science Engineering New Horizon College of Engineering Bangalore India Department of Electrical Electronics & Communication Engineering Galgotias university Gerater Noida Uttar Pradesh Department of Computer Science and Engineering MLR Institute of Technology Hyderabad Telangana India Radiology Techniques Department College of Medical Technology The Islamic University Najaf Iraq Lovely Professional University Phagwara Punjab India Department of Information Technology GRIET Bachupally Hyderabad Telangana India

ISBN: (数字)9798331527495

ISBN: (纸本)9798331527501

In this research paper, we present the design and implementation of an AI assisted interactive framework for data modeling and high resolution image synthesis that leverages both state of the art latent diffusion models and visualisation of the real-time algorithm. The system proposed enables user to be able to better understand complex data modeling processes and creates high resolution images in the latent space using diffusion. The framework is both interactive, allowing modifications in parameters and real time visualization of change, making it a useful tool both for educational and for advanced AI research. In this paper, we also discuss the underpinning AI-assisted data modeling algorithms, and why they enable efficient data manipulation as well as high quality image synthesis then provide simulation results and practical applications to illustrate the capabilities of the framework of visualizing the latent diffusion process and generating high resolution images.

关键词： Image resolution Image synthesis Computational modeling Simulation data visualization Streaming media Diffusion models Real-time systems data models Artificial intelligence

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Enhancement of a Complex Field's Reservoir Model Through Novel Application of Forward Stratigraphic modeling

Enhancement of a Complex Field's Reservoir Model Through Nov...

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2022 Offshore Technology conference Asia, OTCA 2022

作者： Adam, Rusli Bin Ayub, Siti Hasmah Nguyen, Huu Nghi Masoudi, Rahim Murugesu, Thanapala Singam Haziq Mohammad, Muhammad Hanif Kadir, Fauzi Margotta, Jose Tuan Harith, Zuhar Zahir Kolupaev, Alexander Zainudain, Yuhanis Thomas, Djowan PETRONAS Malaysia Beicip-Franlab Asia

ISBN: (纸本)9781613998359

The objective of this paper is to demonstrate the success of an alternative numerical modeling approach to build a static model by incorporating Forward Stratigraphic Modelling (FSM) as geological input. This new methodology was performed on a field in the Malay Basin where early production wells indicated the high uncertainty in oil-originally-in-place, facies distribution and reservoir connectivity. For this reason, a new approach was developed for a static model in the area that provides new insights of subsurface reservoirs, de-risking future field assets and mitigates the subsurface uncertainty. process-based simulations as presented with FSM present realistic scenarios of lithology distribution and vertical barriers that enable advanced subsurface characterization. FSM process built a quantitative method that simulate sediment distribution from regional to reservoir architecture for A field D and E sands. The main parameters for simulation run include regional understanding of sediment sources, in-situ organic sediment production, global sea-level curve enhanced by Milankovitch cycles and main long-term processes that control the subsidence of the area. FSM prediction combined with regional seismic, cores and well log data have provided a robust scenario of reservoir characteristics for static model. The results of the study detailed high-resolution sequence stratigraphy, significant changes in the depositional system and sand accumulation through time. The results of FSM were quality-checked with the A field well dataset for consistency. After performance of sensitivity analysis, the best-matched model was chosen for subsequent static model building process. In generating static depo- and rock type models, the FSM result were compared with the Geostatistical Stochastic Inversion (GSI) for property distribution away from the well control. The result of FSM guided model building showed A field D reservoirs as relatively having better sand quality with good late

关键词： Sensitivity analysis

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Copula Guided Parallel Gibbs Sampling for Nonparametric and Coherent Topic Discovery (Extended Abstract) 39

Copula Guided Parallel Gibbs Sampling for Nonparametric and ...

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39th IEEE International conference on data Engineering, ICDE 2023

作者： Lin, Lihui Rao, Yanghui Xie, Haoran Lau, Raymond Y. K. Yin, Jian Wang, Fu Lee Li, Qing Sun Yat-sen University School of Computer Science and Engineering Guangzhou China Lingnan University Department of Computing and Decision Sciences New Territories Hong Kong City University of Hong Kong Department of Information Systems Kowloon Hong Kong Sun Yat-sen University Guangdong Key Laboratory of Big Data Analysis and Processing Guangzhou China Hong Kong Metropolitan University School of Science and Technology Kowloon Hong Kong The Hong Kong Polytechnic University Department of Computing Kowloon Hong Kong

ISBN: (纸本)9798350322279

In terms of the generative process, the Gamma-Gamma-Poisson process (G2PP) is equivalent to the nonparametric topic model of Hierarchical Dirichlet process (HDP). Considering the high computational cost of estimating parameters in HDP, a parallel G2PP was developed to generate topics efficiently via multi-threading. Unfortunately, the above model needs to predefine the number of topics. To address this issue, we first propose a Topic Self-Adaptive Model (TSAM) for nonparametric and parallel topic discovery. In TSAM, a monitor-executor mechanism is developed to manage the global topic information using a hierarchical structure of threads. Based on the apparatus of copulas, we further extend our TSAM to TSAMcop for coherent topic modeling by exploiting a copula guided parallel Gibbs sampling algorithm. Extensive experiments validate the effectiveness of both TSAM and TSAMcop. © 2023 IEEE.

关键词： Information management

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Research on Simulation Model of Urban Environment Design and Renewal Using Virtual Reality Technology

Research on Simulation Model of Urban Environment Design and...

引用

Electronics, Energy Systems and Power Engineering (EESPE), IEEE International conference on

作者： Wei Ma Changchun University of Architecture and Civil Engineering Changchun China

ISBN: (数字)9798350389579

ISBN: (纸本)9798350389586

This paper proposes a research method of urban environment design and renewal simulation model based on virtual reality technology, aiming to improve the efficiency and accuracy of urban planning and renewal process. This method takes point cloud data processing as the core technology, combines advanced 3D modeling and virtual reality technology, and constructs a high-precision urban environment simulation system. The system includes key modules such as data acquisition, optimization algorithm design, model construction, simulation verification and interactive operation. Among them, through the improved point cloud data processing algorithm, the rapid reconstruction of complex urban spatial structure is realized, and efficient 3D rendering and large-scale scene simulation are supported. data analysis of multiple actual urban scenes shows that this method has excellent performance in various environments. The simulation system supports accurate visual comparison of different urban design schemes, interactive scene adjustment through real-time dynamic operation, and quantitative evaluation of design results. Experimental data show that the system can control the simulation error within 5% in multiple urban renewal scenarios; the data processing efficiency is improved by about 30% compared with traditional methods, and the 3D reconstruction time is shortened to 70% of the original.

关键词： Point cloud compression Solid modeling Accuracy Three-dimensional displays Heuristic algorithms Urban planning Virtual reality data processing Rendering (computer graphics) data models

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Classification of Weld Defects Based on Computer Vision System data and Deep Learning

Classification of Weld Defects Based on Computer Vision Syst...

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2023 International conference on Industrial Engineering, Applications and Manufacturing, ICIEAM 2023

作者： Cherkasov, Nikita Ivanov, Mikhail Ulanov, Aleksey Institute of Engineering and Technology South Ural State University National Research University Chelyabinsk Russia

ISBN: (纸本)9781665475952

Visual and dimensional inspection is widely used in the search for external weld defects that locate on the surface of welded joints. Such inspections are carried out by trained specialists whereas computer vision-based quality control systems require the significant investments. In addition, the data about the object of scanning that can be obtained during the operation of computer vision systems irretrievably disappear, or remain in the memory of the system without their processing and any analysis to find probable patterns of welding defects. This study utilized the capabilities of the iRVision system, which is built into a Fanuc welding robot, to obtain the data about the weld joint after robotic welding. Such data could be accumulated with the help of the 3D Laser Scanning subsystem's laser sensor. Pre-processing of the collected data was carried out. And the artificial neural networks, using deep learning, were subsequently developed for the classification of the data of welds into defective and non-defective. The results of the most effective of the developed neural network models are an accuracy of 0.92, a precision of 0.90, and a recall of 0.81 on the test sample. The presented results allow us to automate the quality control and visual inspection process of welded joints based on the data from the iRVision system. The research has shown that the perspective direction of the project is to improve the model to search for the small size defects of © 2023 IEEE.

关键词： Neural networks

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Rectified Linear Unit based Local Linear Model Tree for Nonlinear System Identification Incorporating Prior Knowledge 61

Rectified Linear Unit based Local Linear Model Tree for Nonl...

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IEEE 61st conference on Decision and control (CDC)

作者： Glass, Leon Hilali, Wael Nelles, Oliver Bosch Corp Res D-71272 Renningen Germany Univ Siegen Res Grp Automat Control Mechatron D-57076 Siegen Germany

ISBN: (纸本)9781665467612

We combine the local model network algorithm Rectified Linear Unit based Local Linear Model Tree (ReLU-MoT) with recently developed tools for differentiable solution of (neural) ordinary differential equations (ODEs). The result is a model for system identification, which allows for straight-forward inclusion of prior knowledge about the underlying physical process. By applying the model to a well-known Wiener-Hammerstein system identification benchmark data set, we show how the inclusion of prior knowledge can improve model quality, interpretability, memory footprint and system analysis of the trained model. Our models compare favorably to existing local model networks on this benchmark, both with and without the inclusion of prior knowledge.

关键词： Ordinary differential equations

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Satisfaction analysis of Online Shopping Based on Fuzzy Analytic Hierarchy process

Satisfaction Analysis of Online Shopping Based on Fuzzy Anal...

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2021 International conference on Applied Mathematics, modeling and Computer Simulation, AMMCS 2021

作者： Su, Zhongqian Wang, Hongyan Liaoning Institute of Science and Technology China

ISBN: (纸本)9781643682549

Through collected data from general consumer questionnaire and scored the key degree of influencing factors with 1-9 scale method, we analyse the consumers' satisfaction with software Python about online shopping. Fuzzy analytic hierarchy process (FAHP) is used to score the satisfaction degree of online shopping, and the rationality model is analyzed with the actual data to obtain the fuzzy evaluation model of satisfaction degree of online *** the last several Consumers's reference factors in online shopping were tested, but it is the first time that an exact, parametric, the fuzzy analytic hierarchy process is compared to data. © 2022 The authors and IOS Press.

关键词： Analytic hierarchy process

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