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

共 4764 条记录，以下是61-70 订阅

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Research on interconnection technology of heterogeneous platforms for privacy computing for energy big data 3

Research on interconnection technology of heterogeneous plat...

引用

3rd International conference on Energy and Power Engineering, control Engineering (EPECE)

作者： Zhai, Yujia Huang, Xiuli Yu, Pengfei State Grid Smart Grid Res Inst Co Ltd State Grid Lab Power Cyber Secur Protect & Monito Nanjing Peoples R China

ISBN: (纸本)9798350366105;9798350366099

Energy data, especially power data, has the advantages of covering a wide range of industries, high value density, and good accuracy, relying on energy big data can widely describe all kinds of terminal production and life activities. However, the privacy computing platforms of various vendors often adopt different technical architectures and algorithm protocols in the early implementation process, which makes the implementation of various platforms have great differences, resulting in the direct interconnection between heterogeneous privacy computing platforms of various organizations. Aiming at the interoperability needs and problems of energy big data privacy computing platforms with different technical architectures, this paper decouple the management plane and data plane of the privacy computing platform, and in accordance with the principle of business priority, proposes a new privacy computing interconnection model of "unified business collaboration component + flexible configuration algorithm engine" suitable for energy big data. Through the design of the east-west and North-South interface framework of the privacy computing platform and the security access principle of the algorithm engine, the whole process control, cross-platform interconnection, and internal and external network penetration modeling and analysis of energy big data collaboration with the outside world are realized, which meets the key data security protection requirements of the State Grid such as distributed computing and storage of data inside and outside the platform. It is of great significance to promote energy big data to empower external institutions such as governments, banks and operators.

关键词： Privacy computing energy big data cross-heterogeneous platforms connectivity technologies

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Software Architecture for process Simulation in Biogas Plants 14

Software Architecture for Process Simulation in Biogas Plant...

引用

14th International conference on Advanced Computer Information Technologies, ACIT 2024

作者： Melnyk, Andriy Maslyiak, Yurii Popovych, Pavlo Sitkar, Taras Momotiuk, Evhenii Kostyk, Bohdan West Ukrainian National University Department of Computer Science Ternopil Ukraine West Ukrainian National University Department of Transport and Logistics Ternopil Ukraine Ternopil Volodymyr Hnatiuk National Pedagogical University Department of Computer Technologies Ternopil Ukraine

ISBN: (纸本)9798350350036

The work substantiates the use of modern information technologies and mathematical modeling based on the analysis of interval data as effective process management tools in biogas plants. The use of interval modeling allows you to build models with guaranteed prognostic properties. The article also presents the features of building the software architecture for mathematical modeling of processes in biogas plants. The main aspects of the implementation of software for modeling processes in biogas plants are described, the feature of which is the software interpretation of interval discrete models and an open service-oriented architecture, which ensures their integration into existing control systems of biogas plants and allows to control biochemical processes in real time and thereby increase efficiency of functioning of biogas plants. A number of diagrams illustrating the features of the software implementation of the environment for simulating processes in biogas plants are given, and the specifics of its implementation into the SIMBA#biogas universal system of simulating and simulating the operation of biogas plants are described. © 2024 IEEE.

关键词： Service oriented architecture (SOA)

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Mathematical modeling of Quality control Based on Machine Learning 1

Mathematical Modeling of Quality Control Based on Machine Le...

引用

1st IEEE International conference on Ambient Intelligence, Knowledge Informatics and Industrial Electronics, AIKiiE 2023

作者： Bao, Qihan University of Calgary Calgary Canada

ISBN: (纸本)9798350316469

Quality control mathematical model is a mathematical model based on the principle of statistical process control. Its application in modern quality management provides a scientific basis for quality management. The establishment process includes three parts: one is to make statistical analysis from a large number of actual data, the other is to make use of statistical data to establish a mathematical model. Based on support vector machine regression, logistic regression and neural network in machine learning, the mathematical modeling of quality control is studied in this paper. Experimental results show that machine learning based quality control mathematical model can achieve the highest accuracy of 94.4%. It is concluded that machine learning has high application potential in quality management and can provide a scientific basis for quality management. © 2023 IEEE.

关键词： machine learning neural network quality control mathematical modeling support vector machine

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Intelligent control of building electricity based on intelligent Internet of Things and wireless communication technology

Intelligent control of building electricity based on intelli...

引用

2024 International conference on Electronics, Electrical and Information Engineering, ICEEIE 2024

作者： Tu, Xuren Song, Ganlu Li, Gang School of Art Jiangxi University of Finance and Economics Jiangxi Nanchang330032 China

ISBN: (数字)9781510686809

ISBN: (纸本)9781510686793

In order to improve the intelligent control effect of building electrical, this paper combines wireless communication technology with Internet of Things technology, and proposes a new type of building intelligent system based on Internet of Things technology, which has the characteristics of no center, self-organization and flattening. The building electrical equipment under this system building can realize wireless self-organization network, plug and play, and coordinated operation. This equipment management information system refers to the equipment life cycle management concept of equipment management in Industry 4.0 era, and manages the information generated by all activities in the whole life cycle of equipment. Moreover, the operation data of four kinds of electrical equipment commonly used in office buildings are selected for analysis, and the probability conversion process of users' actions between startup and shutdown. © 2024 SPIE.

关键词： Internet of things Instrument modeling data modeling Intelligence systems Solar energy control systems Wireless communications Internet technology Statistical analysis Telecommunications

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Probabilistic analysis of GPS Spoofing Attack Failures Using Poisson Point process 3

Probabilistic Analysis of GPS Spoofing Attack Failures Using...

引用

3rd International conference on Power, control and Computing Technologies, ICPC2T 2024

作者： Kiruthika, D. Vinothini, N. Ananthi, G. Engineering Thiagarajar College of Engineering Department of Electronics and Communication Madurai India

ISBN: (纸本)9798350349207

This study presents a geospatial analysis approach to derive the failure probability of GPS spoofing attacks by utilizing Poisson Point process (PPP) modeling. The research begins by establishing a robust framework for characterizing GPS spoofing attacks based on available data and historical attack patterns. Leveraging the PPP model, which is commonly used in spatial point process analysis, the study integrates real-world information such as GPS receiver locations, environmental conditions, and spoofing device parameters to simulate the spatial distribution of spoofing attack attempts across a given area. Through the application of PPP modeling, the study aims to estimate the failure probability of GPS spoofing attacks, which is defined as the likelihood of the spoofer's signal being successfully received and accepted by a targeted GPS receiver. This approach allows for the incorporation of various geospatial factors, including receiver density, signal propagation, and environmental interference, to provide a more accurate representation of the vulnerability of the GPS system to spoofing attacks in specific geographic areas. The findings from this research are expected to contribute to enhancing the understanding of GPS vulnerability and improving countermeasures against spoofing attacks. The closed form expression for GPS Spoofing attack failure probability is derived using the Poisson point process. The simulation is compared with the theoretical results and observed that it is exactly close to each other. © 2024 IEEE.

关键词： Global positioning system

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On the Nature of data in RPA Bots 21st

On the Nature of Data in RPA Bots

引用

21st International conference on Service-Oriented Computing (ICSOC)

作者： Voelker, Maximilian Weske, Mathias Univ Potsdam Hasso Plattner Inst Potsdam Germany

ISBN: (纸本)9783031484230;9783031484247

Robotic process automation (RPA) automates tasks traditionally performed by employees, reducing repetitive and error-prone work. While RPA bot models are based on graphical notations, data, a key component of RPA, is often not explicitly represented, making it difficult to understand how data contributes to the automation. This paper explores the role of data in RPA, extends the ontology of RPA operations by data aspects, and proposes a visualization of data in RPA bot models, promoting the design of more comprehensible RPA bot services and enabling different bot analysis techniques.

关键词： Robotic process Automation Ontology modeling data

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Two-Dimensional Statistical Pattern analysis for Effective modeling and Monitoring of Limited Batch process data in Food Industry 13

Two-Dimensional Statistical Pattern Analysis for Effective M...

引用

13th IEEE data Driven control and Learning Systems conference, DDCLS 2024

作者： Zhu, Jinlin Zhang, Zheng Jiangnan University State Key Laboratory of Food Science and Resources Wuxi214122 China School of Food Science and Technology Jiangnan University Wuxi214122 China Hong Kong University of Science and Technology Department of Chemical and Biological Engineering 999077 Hong Kong

ISBN: (纸本)9798350361674

This study presents a novel two-dimensional statistical pattern analysis (2D-SPA) method, specially designed to address the challenges inherent in monitoring and modeling processes within low-volume, high-quality food manufacturing settings. By ingeniously integrating robust statistical techniques within a two-dimensional sliding window framework, this approach significantly expands the analytical dataset by operating across both batch and time dimensions, effectively overcoming the constraints posed by limited batch sizes. This innovative strategy not only augments the detection and diagnosis capabilities for subtle process deviations and emerging trends but also capitalizes on the dynamic statistical variances observed across batches and over time, thus offering a comprehensive view of the process variability. The application of 2D-SPA is meticulously validated through an industrial case study focused on lactic acid bacteria fermentation, where it demonstrates marked improvements in accuracy and sensitivity for process monitoring. The results underscore the method's potential to significantly enhance quality assurance measures in food batch production. © 2024 IEEE.

关键词： Food industry

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Predictive analysis of CPI Based on Machine Learning Algorithms

Predictive Analysis of CPI Based on Machine Learning Algorit...

引用

2024 International conference on Power, Electrical Engineering, Electronics and control, PEEEC 2024

作者： Wang, Xiawei Sichuan University School of Digital Economics Jinjiang College Sichuan Pengshan China

ISBN: (纸本)9798350378917

In recent decades, with the vigorous development of the national economy, the living standards of residents have also risen, and various types of consumption have emerged. In order to study the consumption situation of residents, the government has proposed the Consumer Price Index (CPI) as an indicator to reflect changes in their consumption and service levels. In order to better study the Consumer Price Index, this paper proposes a predictive analysis method for CPI based on machine learning algorithms. The first stage of this research method involves data visualization, which includes two small steps: data preparation explanation and chart visualization. This stage mainly provides initial basis for subsequent modeling;The second stage is the highlight of machine learning (random forest) algorithm modeling, which uses the monthly indices of national, city, and rural levels to train the model separately, with scores of 0.9927,0.9936, and 0.9919 respectively, and draws the best fitting line;The third stage is for the model to predict the new data for the next month. Through the verification of the entire process mentioned above, the model in this article has good predictive performance and can effectively help solve the problem of CPI prediction. © 2024 IEEE.

关键词： Adversarial machine learning

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Real-time heat sealing quality analysis of film based on digital twin system 3

Real-time heat sealing quality analysis of film based on dig...

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3rd International conference on Electronic Information Engineering, Big data, and Computer Technology, EIBDCT 2024

作者： Zhao, Jun Shen, Nanyan Li, Jing Li, Yufei Li, Haoyang School of Mechatronic Engineering and Automation Shanghai University Shanghai Baoshan China

ISBN: (纸本)9781510680449

Digital twin achieves interactive mapping between physical entities and virtual models, enabling continuous real-time monitoring of process quality in virtual spaces. This paper addresses the issues of high latency and poor correlation with heat sealing process parameters in the quality inspection of plastic film heat sealing, and explores real-time analysis of heat sealing quality based on digital twin technology. The focus is on the finite element analysis of typical heat sealing process parameters combined with thermo-structural coupling, boundary condition modification and data-driven modeling. The study reveals the relationship between controllable heat sealing process parameters and film heat sealing quality, achieving real-time monitoring of the heat sealing quality of plastic sealing film © COPYRIGHT SPIE. Downloading of the abstract is permitted for personal use only.

关键词： Quality control

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Comparative analysis for System modeling Using System Identification Techniques 14

Comparative Analysis for System Modeling Using System Identi...

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14th International conference on Electrical Engineering (ICEENG)

作者： Annan, Mayada Hassan, Mohamed Ashry, Mahmoud Sci Technol Excellent STCE Dept Mil Prod Minist Cairo Egypt Egyptian Armed Forces Dept Automat Control Cairo Egypt Arab Acad Sci Technol AAST Dept Automat Control Cairo Egypt

ISBN: (纸本)9798350343427;9798350343434

System modelling is an essential task for controller design. System identification is widely used for dynamic systems modelling and provides high performance practical dynamic systems modelling. In this paper, a least square approach and recursive least square based identification techniques are proposed for comparative analysis of dynamic modelling of a single -input single-output tank process. Chirp and multi-sine signals are utilized for system modelling as they provide the required data for capturing the system dynamics. A comparative analysis is carried out with nonlinear recursive least square techniques such as ARX model, ARMAX model, Box-Jenkins model, OutputError model for evaluating the proposed approach effectiveness. The ARX method provided high performance for single-input single-output tank system identification in the presence of system noise.

关键词： ARX ARMAX System identification

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