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检索条件"任意字段=Proceedings of the 2023 12th International Conference on Computing and Pattern Recognition"

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Synthesis of stable control law for ball and beam system robust to disturbances based on synergetic control theory 12

Synthesis of stable control law for ball and beam system rob...

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12th IEEE international conference on Control, Automation and Information Sciences, ICCAIS 2023

作者： Chiem, Nguyen Xuan thang, Le Tran Dinh, Nguyen Cong Le Quy Don Technical University Department of Automation and Computing Techniques Hanoi Viet Nam Controls Automation in Production and Improvement of Technology Institute Hanoi Viet Nam

ISBN: (纸本)9798350328783

In the article, a method of synthesizing stable control laws for ball and beam system in the presence of disturbances is presented based on synergetic control theory. the ball and beam system is a short mechanical system, has large nonlinear properties, and is easily affected by external noise. this new approach to the design of system stabilizers is based on the synergetic control theory. When synthesizing control laws based on this theory, the desired ball position is considered invariant. With the synthetic control law, only the necessary invariant is achieved but also the asymptotic stability of the entire system is guaranteed. In addition, the control law also ensures the system is robust against external disturbances and model parameter uncertainties. Analyze the stability of the system in the presence of noise through the Lyapunov function. Simulation results with different scenarios demonstrate the correctness and effectiveness of the proposed controller. © 2023 IEEE.

关键词： Lyapunov functions

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proceedings of 12th Latin-American Symposium on Dependable and Secure computing, LADC 2023

Proceedings of 12th Latin-American Symposium on Dependable a...

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12th Latin-American Symposium on Dependable and Secure computing, LADC 2023

ISBN: (纸本)9798400708442

the proceedings contain 32 papers. the topics discussed include: ALR-LoRaWAN — an application-level retransmission management algorithm for LoRaWAN networks;using formal methods for on-the-fly time series verification;loom: a closed-box disaggregated database system;efficient synchronization of CRDTs using VCube-PS;generating realistic attack data for microservices: framework and case study;leveraging time series autocorrelation through numerical differentiation for improving failure prediction;third-party trackers in COVID-19 mobile applications can enable privacy leaks;joining parallel and partitioned state machine replication models for enhanced shared logging performance;a time-phased partitioned checkpoint approach to reduce state snapshot overhead;and parallel execution of transactions based on dynamic and self-verifiable conflict analysis.

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Database Knowledge Discovery Combining Cluster Analysis and Classification Using Data Mining 12

Database Knowledge Discovery Combining Cluster Analysis and ...

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12th international conference on System Modeling and Advancement in Research Trends, SMART 2023

作者： Singh, Mandeep Kaur, Tanmeet Shukla, Anand Kumar University Institute of Computing Chandigarh University Mohali Punjab Cgc Jhangeri Punjab Mohali India Noida International University Electronics and Communication Engineering Greater Noida India

ISBN: (纸本)9798350369861

Two key data mining methods are clustering and classification. the problem of classification involves categorizing object into one-to-many pre-established categories according to the characteristics of the object. While clustering groups objects based on their proximity or similarity and is a clear learning problem. Every group is referred to as a cluster. In the study, we perform integration to data mining by the clustering and classification techniques using a big database called the 'Fisher's Iris Dataset' with the attribute and some examples. Using the Data Mining application Waikato Environment for Knowledge Analysis, We contrasted the outcomes of integrating a clustering and classification technique based on numerous criteria with the outcomes of a straightforward classification strategy (using the J48 classifier). the experiment's findings demonstrate that combining clustering and classification produces effective outcomes with a high robustness and accuracy rate, and the data set contains some values that are missing. © 2023 IEEE.

关键词： Data mining

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Research on pattern recognition of Urban and Rural Consumption Behavior Based on Machine Learning and Its Application in Digital Economy 2

Research on Pattern Recognition of Urban and Rural Consumpti...

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2nd international conference on Mechatronics, IoT and Industrial Informatics, ICMIII 2024

作者： Mu, Xiaowei Liu, Yan Sheng, Zhijun Chen, Jiahui Changchun Normal University Changchun Humanities and Sciences College Changchun China Changchun Humanities and Sciences College Changchun China Changchun University of Science and Technology Changchun China

ISBN: (纸本)9798350386639

this paper introduces an SVM algorithm for studying consumer behavior. this model is a new pattern recognition algorithm based on statistical principle. It has unique advantages in dealing with small samples, nonlinearity and high dimensional pattern recognition. the fuzzy semantic modeling method is constructed by using emotion computing and text mining. At the same time, the internal and external inducement factors are the first part and the purchasing degree of consumers is the second part, and the fuzzy reasoning model is established. the consumption behavior and process of urban and rural residents are constructed by using probability theory. through the analysis of the relationship between the elements, the corresponding knowledge base is established. the unreasonable purchase degree model of customers is established by Jess method. Finally, taking a tobacco enterprise as an example, an empirical study was made on it. the results show that in urban and rural areas, SVM-based consumer behavior identification and statistical analysis has high accuracy and efficiency. © 2024 IEEE.

关键词： Adversarial machine learning

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Application of Computer Artificial Intelligence Technology in the Manufacturing System of Aero-Powered Aircraft

Application of Computer Artificial Intelligence Technology i...

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2023 international conference on Internet of things, Robotics and Distributed computing, ICIRDC 2023

作者： Bi, Yingpu Xu, Weichang Liu, Jifang Wu, Yake Hu, Zongchun High-tech Institude FanGong-ting South Street on the 12th Shandong Qingzhou262500 China

ISBN: (纸本)9798350375275

this project proposes a programmable logic-oriented algorithm to solve the difficult problem of coding generation of aircraft control system. the synchronous data flow computing model suitable for control system modeling is used to realize the cooperative communication between multiple functional modules in UAV control system. the spatial information fusion platform including physical space, transport layer, data layer, model layer, service layer and application layer is constructed. the dynamic programming method between multiple agents is used to solve the problem of motion trajectory optimization and cooperative task assignment among multiple agents. A multi-machine joint simulation platform with cluster collaboration is constructed and its performance is verified. the simulation results show that the system has high efficiency. © 2023 IEEE.

关键词： Dynamic programming

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On Two-Dimensional Approximate pattern Matching Using Fuzzy Automata 12th

On Two-Dimensional Approximate Pattern Matching Using Fuzzy ...

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12th international conference on Soft computing for Problem Solving, SocProS 2023

作者： John Kaspar, A. Sheena Christy, D.K. Department of mathematics Christ University Karnataka Bengaluru560029 India Department of mathematics SRM Institute of Science and Technology Tamil Nadu Kattankulathur 603203 India

ISBN: (纸本)9789819731794

pattern matching has been extensively studied in the last few decades, owing to its great contribution in various fields such as search engines, computational biology, etc. Several real-life situations require patterns that allow ambiguity in specified positions. In this paper, one-dimensional and two-dimensional approximate pattern matching models have been constructed using fuzzy automata. the similarity function used in fuzzy automata enables the occurrence of all exact and similar one-dimensional and two-dimensional patterns. this kind of searching approximate patterns is not possible with regular search models. the time complexity of the proposed algorithm has also been analyzed. © the Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2024.

关键词： Search engines

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A Comparison of Multi-Object Sub-pattern Linear Assignment Metrics 12

A Comparison of Multi-Object Sub-Pattern Linear Assignment M...

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12th IEEE international conference on Control, Automation and Information Sciences, ICCAIS 2023

作者： Barrios, Pablo Adams, Martin Santiago Chile

ISBN: (纸本)9798350328783

Error estimation in multi-target tracking and robotic mapping is critical for algorithmic evaluation. In multi-target tracking and robotic mapping, both target or feature detection, as well as localization errors often exist. For this reason, recently, the multi-object Optimal Sub-pattern Assignment (OSPA) and Cardinalized Optimal Linear Assignment (COLA) metrics were introduced, based on the Wasserstein construct. these metrics have the ability to compare set-based multi-target or multi-feature estimates and penalize both detection as well as state (spatial) errors. After the OSPA and COLA metrics were introduced, a variant referred to as the Generalized Optimal Sub-pattern Assignment (GOSPA) metric was introduced, based on the claim that it is a generalization of the OSPA metric. this article compares the OSPA, COLA and GOSPA metrics in terms of their abilities to penalize certain multi-target/multi-feature scenarios. the article will determine when these metrics can disagree with one another when evaluating multi-target/multi-feature set-based errors and will evaluate their sensitivities to their characteristic 'cut-off' parameters. As a result, their intuitive penalizations of various multi-target/multi-feature configurations will be demonstrated to provide a more complete and nuanced understanding of their applicability and performance in different contexts. © 2023 IEEE.

关键词： Errors

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proceedings - 20th IEEE international Symposium on Parallel and Distributed Processing with Applications, 12th IEEE international conference on Big Data and Cloud computing, 12th IEEE international conference on Sustainable computing and Communications and 15th IEEE international conference on Social computing and Networking, ISPA/BDCloud/SocialCom/SustainCom 2022

Proceedings - 20th IEEE International Symposium on Parallel ...

引用

20th IEEE international Symposium on Parallel and Distributed Processing with Applications, 12th IEEE international conference on Big Data and Cloud computing, 12th IEEE international conference on Sustainable computing and Communications and 15th IEEE international conference on Social computing and Networking, ISPA/BDCloud/SocialCom/SustainCom 2022

ISBN: (纸本)9781665464970

the proceedings contain 117 papers. the topics discussed include: detection of a novel dual attack in named data networking;fair DMA scheduler for low-latency accelerator offloading;multi-attribute decision-making method based on interval intuitionistic trapezoidal fuzzy number to determine the expert weight: note: sub-titles are not captured in Xplore and should not be used;binary-level directed symbolic execution through pattern learning;an efficient metric-based approach for static use-after-free detection;a graph convolution neural network based method for insider threat detection;maintenance worker scheduling for charging pile fault: a multi-agent RL approach;towards secure bilateral friend query with conjunctive policy matching in social networks;structure-noise-aware anchor link prediction across social networks;file system to support secure cloud-based sharing;discovering agent models using process mining: initial approach and a case study;and towards agent-based simulation of the parallel trading market of pharmaceuticals.

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Learning to Optimize Quantum Neural Networks Without Gradients 4

Learning to Optimize Quantum Neural Networks Without Gradien...

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4th IEEE international conference on Quantum computing and Engineering, QCE 2023

作者： Kulshrestha, Ankit Liu, Xiaoyuan Ushijima-Mwesigwa, Hayato Safro, Ilya Newark United States Fujitsu Research of America Sunnyvale United States

ISBN: (纸本)9798350343236

Quantum Machine Learning is an emerging sub-field in machine learning where one of the goals is to perform pattern recognition tasks by encoding data into quantum states. this extension from classical to quantum domain has been made possible due to the development of hybrid quantum-classical algorithms that allow a parameterized quantum circuit to be optimized using gradient based algorithms that run on a classical computer. the similarities in training of these hybrid algorithms and classical neural networks has further led to the development of Quantum Neural Networks (QNNs). However, in the current training regime for QNNs, the gradients w.r. t objective function have to be computed on the quantum device. this computation is highly non-scalable and is affected by hardware and sampling noise present in the current generation of quantum hardware. In this paper, we propose a training algorithm that does not rely on gradient information. Specifically, we introduce a novel meta-optimization algorithm that trains a meta-optimizer network to output parameters for the quantum circuit such that the objective function is minimized. We empirically and theoretically show that we achieve a better quality minima in fewer circuit evaluations than existing gradient based algorithms on different datasets. © 2023 IEEE.

关键词： pattern recognition

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Rendering Optimization of Massive Map Annotation Point Data Based on Multi Strategy Fusion 12

Rendering Optimization of Massive Map Annotation Point Data ...

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12th international conference of Information and Communication Technology, ICTech 2023

作者： Wei, Zhijie Zhou, Xiaolei Xing, Wentai Bao, Changlin Zhou, Cheng Cao, Ruipu Shenyang Institute of Computing Technology Chinese Academy of Sciences University of Chinese Academy of Sciences Beijing China Qinghai Academy of Building Materials Science Xining China Suzhou Jiaoke Group Co. Ltd Nanjing China

ISBN: (纸本)9798350332919

Aiming at the problems of poor visualization effect and system lag delay caused by the rendering of massive map label points, an optimization strategy combining visual optimization technology and point aggregation algorithm is proposed, and it is officially put into use in a city and town pavement collapse monitoring visualization platform. Compared with the traditional annotation point optimization scheme, firstly, the annotation point classification processing according to the specific business scenario, asynchronous traversal of data combined with documentFragment and other optimization technologies, combined with the K-D tree-based Grid-Distance-based Clustering, by comparing the performance report detected by Google Lighthouse, the performance indicators in the page display are improved by about 26%. At the same time, in terms of optimization effect, the number of callout points rendered on the page is controlled, so that the number of reflow redraws caused by page rendering is further reduced. © 2023 IEEE.

关键词： Visualization

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