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1st international Virtual conference on Visual Pattern Extraction and Recognition for Cultural Heritage Understanding (VIPERC 2022) 1

1st International Virtual Conference on Visual Pattern Extra...

引用

1st international Virtual conference on Visual Pattern Extraction and Recognition for Cultural Heritage Understanding, VIPERC 2022

作者： Amelio, Alessia Montelpare, Sergio Ursino, Domenico InGeo University "G. d’Annunzio" Chieti-Pescara Viale Pindaro 42 Pescara65127 Italy DII Marche Polytechnic University Via Brecce Bianche 12 Ancona60131 Italy

This document introduces the 1st international Virtual conference on Visual Pattern Extraction and Recognition for Cultural Heritage Understanding (VIPERC 2022), a premier forum for presenting the state-of-the-art, new research, ongoing work, academic and project reports in advanced statistics and machine learning, 3D modelling and simulation, knowledge representation, intelligent systems, information retrieval and software engineering, for visual pattern extraction, analysis and recognition to preserve the cultural heritage. © 2022 Copyright for this paper by its authors.

关键词： 3D modeling

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Research on Dynamic Path Planning of Theme Park Based on Improved Genetic Algorithm 2

Research on Dynamic Path Planning of Theme Park Based on Imp...

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2nd international conference on Applied Mathematics, Modeling and computer simulation, AMMCS 2022

作者： Zhang, Jialin Qu, Xingke Li, Lei Zhang, Yueyang School of Computer and Information Engineering Harbin University of Commerce Harbin China

ISBN: (纸本)9781643683522

Aiming at the current queuing problem in large theme parks and the insufficient utilization of facilities, a dynamic virtual queuing model is proposed, which can recommend the most time-saving tour route for visitors based on each visitor's interest points and combined with the real-time dynamic changes of crowd flow in each facility. An improved data structure is proposed to transform the Dynamic Travelling Salesman Problem into Travelling Salesman Problem;the traditional genetic algorithm is also improved by proposing the Optimal Replication Method to optimally adjust the population before the selection operation, and the Parent-Child Competition Method is introduced in crossover and mutation to guarantee that the evolutionary process always proceeds in a beneficial direction. The improved data structure greatly improves the efficiency of the algorithm;the improved genetic algorithm can achieve convergence faster and find a better tour route in a faster time, thus improving the visitor experience. © 2022 The authors and IOS Press.

关键词： Genetic algorithms

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Research and application of heterogeneous data collection and analysis platform based on behavior simulation 2

Research and application of heterogeneous data collection an...

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2021 2nd international conference on Machine Learning and computer Application, ICMLCA 2021

作者： Hao, Zhenliang Chang, ZhiJun Qi, Bolin Li, Xu Shenyang Institute of Computing Technology Chinese Academy of Sciences Shenyang China University of Chinese Academy of Sciences Beijing China Documentation and Information Center of Chinese Academy of Sciences Beijing China Beijing Zhongke Zhihe Digital Technology Co. Ltds Shenyang China

ISBN: (纸本)9783800757398

The competition for data resources has become an important part of the current market competition. The main sources of the college entrance examination data currently studied are third-party websites, or manually input data from the official website. Both of these methods have major shortcomings. First of all, in terms of accuracy and limitation, there is no guarantee that the data is accurate. Secondly, in the process of using data, it will be clamped by a third party, so we use behavior simulation technology to collect data from the official website, and then resolve the data by solving the heterogeneity problem. Finally, the completeness and accuracy of the college entrance examination data can be guaranteed through this system platform. © VDE VERLAG GMBH · Berlin · Offenbach.

关键词： Websites

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Risk prediction method of multi-source network information cross-space fusion based on reinforcement learning

Risk prediction method of multi-source network information c...

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Sensors, Electronics and computer Engineering (ICSECE), IEEE international conference on

作者： Yiping Chen Yingzi Zheng Department of Computer Science and Engineering Guangzhou Institute of Science and Technology Guangzhou China

ISBN: (数字)9798350373646

ISBN: (纸本)9798350373653

In order to improve the level of cross-space transmission and sharing of multi-source network information, it is necessary to effectively predict the process risk of fusion, and a risk prediction method of cross-space fusion of multi-source network information based on reinforcement learning is proposed. A cross-spatial dimension construction and transformation model of multi-source network information is constructed, and a feature-tag correlation selection model is established. Combined with the maximum feature-tag correlation identification method, the cross-spatial transformation and reinforcement tracking learning of multi-source network information are realized, and the redundancy test in the process of information cross-spatial fusion is realized by reinforcement learning. The frame structure model of network topology transmission is established according to the self-organized decentralized distributed networking mode of multi-source network space, and the reinforcement learning of information fusion risk prediction is realized by using the replacement parameter configuration and protocol configuration of channel resources, according to the reinforcement learning results. The simulation results show that the proposed method has a high degree of fitness for risk prediction of cross-space fusion of multi-source network information, improves the utilization rate of networking channels, and has good reliability in the process of channel access and resource allocation, effectively reducing the fusion risk, thus improving the transmission channel balance of multi-source networks.

关键词： Analytical models Correlation Protocols simulation Reinforcement learning Predictive models Sensor fusion Reliability engineering Sensors Resource management

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Combining computer simulation Visualization and Multi-Objective Optimization Algorithm for Urban Light Pollution Research

Combining Computer Simulation Visualization and Multi-Object...

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Image processing and computer Applications (ICIPCA), IEEE international conference on

作者： Yuhang Zhang Beijing Technology and Business University Beijing China

ISBN: (数字)9798350360240

ISBN: (纸本)9798350384161

This study aims to solve the problem of urban light pollution by establishing a series of models to achieve the best balance between economy and efficiency. Firstly, we decompose the complex problem into a simple one and establish a light pollution risk level evaluation model, a light pollution threshold differential equation model, a lighting system optimisation strategy model and a Poisson process simulation model validation. In Model I, we use hierarchical analysis and Topsis algorithm, combined with multiple attribute data, to determine the evaluation indexes of light pollution risk level, and effectively classify the light pollution risk level of the area. In Model II, we used the differential equation model to find out the light intensity threshold, and the results showed the diversity of different regions. In Model III, a multi-objective optimisation algorithm is used to achieve the balance of time, light intensity threshold and light range through the lighting system optimisation strategy. Model IV combines the data from Beijing and Shanghai and calculates the number of times residents exceed the permitted use of light using a Poisson distribution.

关键词： Analytical models Biological system modeling Computational modeling Diversity reception Differential equations Artificial light Mathematical models Data models Optimization Light sources

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Intelligent Manufacturing Education and Tutoring Experimental Platform Studies Based on Reconfigurable Module

Intelligent Manufacturing Education and Tutoring Experimenta...

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Information and Communication Engineering (JCICE), international Joint conference on

作者： Dandan Lu Shiyan Liang Min Wang Yinling Wang Dongxuan Han Yao Cheng Dept. Engineering Technology Center Southwest University of Science and Technology Mianyang China Dept. College of Computer Science and Technology Southwest University of Science and Technology Mianyang China

Given the disconnection between the experimental content and the theory in the experimental project in the field of control engineering education, and the experimental process only stays at the level of virtual simulation and small development kit, we propose an intelligent manufacturing teaching assistant experimental platform based on the reconfigurable module. The “intelligence + reconfigurable modularization” experimental module is designed by simulating the industrial production line, and a high-fidelity experimental platform for control engineering education is assembled. We describe in detail the design and implementation process of the teaching assistant experimental platform and expound on the experimental project’s task design, technological revolution, and program design through a case study, which shows that the teaching auxiliary experimental platform is closely integrated with engineering practice. It is proved that students can acquire industrial technical ability from the experimental platform and improve their systematic cognitive ability in the manufacturing system.

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Emergency People Evacuation System using Crowd Density Detection and Path Finding Algorithm

Emergency People Evacuation System using Crowd Density Detec...

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Applied Artificial Intelligence and Computing (ICAAIC), international conference on

作者： S Samundeswari S Yogeshwaran S Gokulaa Krishnaa Computer Science and Engineering Sri Sairam Engineering College Chennai

A complex process, crowd evacuation involves a variety of human behaviours like evacuation motion and behavioural response. Most injuries or losses are not caused by the crises or disasters themselves. Instead, sudden actions like stampedes, shoving people aside, knocking people over, and trampling people over result in fatalities. The logicalness of architectural design, safety management, and the prevention or reduction of fatalities in crises can all be improved by well-organized crowd evacuations. In emergency situations, CCTV footage creates dim, blurry images that make it challenging to evacuate crowds. The bottleneck effect at emergency exits is a significant result of the current models and simulation systems for crowd evacuation based on the Ant Colony Optimization algorithm. By combining low illumination video image enhancement algorithm and CS RNet crowd density estimation model, a faster crowd evacuation can be done during emergency situations.

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simulation of computer Image processing Model Based on Random Forest Algorithm

Simulation of Computer Image Processing Model Based on Rando...

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3D Immersion, Interaction and Multi-sensory Experiences (ICDIIME), international conference on

作者： Haotian Liu University of Edinburgh Edinburgh UK

In essence, image recognition, as a pattern classification problem, can also be processed by classical pattern classification algorithms. Under the background of network information technology, it is need to use computer vision algorithm to process the image and realize the three-dimensional reconstruction of the image for the distortion of the true three-dimensional display image of intelligent interactive system. Random Forest (RF) is a new ensemble learning algorithm developed in recent years, which has good classification accuracy. In this article, a computer image processing model based on RF algorithm is proposed to enhance the ability of depth feature learning. The experimental results show that this image processing technology is more accurate than BP neural network and can be widely used in image processing. High-level target feature representation can often improve the recognition accuracy. However, the extraction of high-level target features generally has certain computational complexity. Compared with traditional methods, the accuracy of the proposed method is greatly improved, and the generalization performance is superior, which can identify images that have been beautified and repaired.

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Reduced Order modelling and Control of Induction Motor with Chaos-Based Gorilla Troop Optimizers (CBGTO) 2

Reduced Order Modelling and Control of Induction Motor with ...

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2nd international conference on Applied Mathematics, Modeling and computer simulation, AMMCS 2022

作者： Ganguli, Souvik Department of Electrical and Instrumentation Engineering Thapar Institute of Engineering and Technology Punjab Patiala147004 India

ISBN: (纸本)9781643683522

This paper proposes 50 new chaos-based gorilla troop optimizers (CBGTO). It is possible to change two regulating parameters in the parent algorithm by using various one-dimensional chaotic maps. Along with these two controlling variables, one of the random variables is also changed in order. Ten well-known and widely used chaotic maps are used to create chaotic algorithms. An induction motor model of order five is used to evaluate the performance of the suggested method. In addition, the same approach is used to build an intelligent PID controller. By using the delta operator, the induction motor model is made simpler. The applicability of the findings is confirmed by statistical analyses of the optimised values, in this example, the integral of time-weighted absolute error (ITAE). Results for the test system under consideration, a 50 hp induction motor, are remarkably positive. Additional parameter changes could be done in the future to boost the functionality of the gorilla troop optimizer (GTO). The PID controller is put into action using a framework for approximate model matching. The novel methods outperform the existing standard and state-of-the-art methods in terms of convergence speed and accuracy. © 2022 The authors and IOS Press.

关键词： Induction motors

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A model for the economic assessment of disassembly-line integration in traditional manufacturing processes 2

A model for the economic assessment of disassembly-line inte...

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2nd international conference on Industry 4.0 and Smart Manufacturing (ISM)

作者： Sergio, Marco Franciosi, Chiara Iannone, Raffaele Univ Salerno Dept Ind Engn Via Giovanni Paolo II 132 I-84084 Fisciano SA Italy

Managing End-of-Life (EoL) products and reintroducing materials and components within the production loop become crucial for guaranteeing the Circular Economy business model. In such a way, the proper management of disassembly process for recovering components and materials from returned EoL products is essential as well as strategic: disassembly is the main gateway of information and can ensure economic returns. This paper aims to provide a model for the economic assessment of the introduction of a manual disassembly line in a traditional and already operating assembly line of manufacturing industries. Therefore, recovered components and materials could directly feed the assembly lines and the recycling processes. The model takes in input probabilistic factors, as products' characteristics, and provides the operating times and component recovery indicators, as well as allows the sizing of the right number of operators needed in the new disassembly line through the optimisation of the industrial cost. An interesting natural evolution of this study is the development of a model-based simulator, with the aim of providing a user-friendly tool to industrial practitioners to estimate the economic feasibility and convenience of introducing a disassembly line. (C) 2021 The Authors. Published by Elsevier B.V.

关键词： disassembly circular economy manufacturing industry end of life products modelling sustainability

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