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7th IEEE Information Technology, Networking, Electronic and Automation Control Conference, ITNEC 2024

作者： Yin, Naiqing Zhou, Jie Institute of Psychology Chinese Academy of Sciences Beijing China University of Chinese Academy of Sciences Department of Psychology Beijing China

ISBN: (纸本)9798350370782

This study combines psychological theories and utilizes structural equation modeling and the XGBoost artificial intelligence algorithm to explore the mechanism of how involvement with domestic fashion brands affects cultural identity. Through a questionnaire survey of 827 participants aged 18 to 65 years, it was found that involvement with domestic fashion brands has a significant positive impact on cultural identity, with nostalgia partially mediating this relationship. Authenticity positively moderates the influence of involvement with domestic fashion brands on nostalgia, while Western cultural exposure positively moderates the influence of nostalgia on cultural identity. Additionally, this study further analyzes the influence of demographic variables and questionnaire items on cultural identity behavior using the XGBoost algorithm. With 90% of the data used as a training set, an algorithm model is established to predict the remaining 10% of the data, and the results show an accuracy of 95.18% in predictions. Furthermore, XGBoost can rank the importance of independent variables, allowing for more timely and effective prediction and adjustment of cultural identity based on important factors. © 2024 IEEE.

关键词： artificial intelligence algorithm authenticity cultural identity domestic fashion brands involvement nostalgia Western cultural exposure XGBoost

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Research on cleaning integrated mechanical system based on artificial intelligence algorithm 3

Research on cleaning integrated mechanical system based on a...

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2023 IEEE 3rd International Conference on Data Science and Computer Application, ICDSCA 2023

作者： Weize, Li Junhao, Shu Zhiheng, Zou Tongda, Liu Gloire Chancel, Louissi Delaunay Shuping, Xu North China Electric Power University Beijing102206 China

ISBN: (纸本)9798350341546

Cleaning integrated mechanical system plays an important role in industrial production. However, the traditional cleaning methods have some problems such as low efficiency and waste of resources. In order to solve these problems, a new cleaning integrated mechanical system is proposed based on artificial intelligence algorithm. In the daily table tennis exercise, the surface of table tennis is often sunken or stained. The existing table tennis cleaning method is only manual cleaning, and the cleaning efficiency is low, and the high-efficiency cleaning cannot always be guaranteed after long-term work. In addition, the table tennis with sunken surface can only be restored by hot water shower, which will cause waste of water resources. At the same time, the efficiency is also very inefficient. The integrated cleaning mechanical system based on artificial intelligence algorithm has obvious advantages, which is of great significance for improving cleaning efficiency and saving resources. Therefore, a table tennis recovery and cleaning integrated device is proposed to solve the above problems. © 2023 IEEE.

关键词： artificial intelligence algorithm Cleaning Device Restore study Table tennis

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Research on robot path optimization based on artificial intelligence algorithm 6

Research on robot path optimization based on artificial inte...

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6th IEEE International Conference on Automation, Electronics and Electrical Engineering, AUTEEE 2023

作者： Xi, Linfan Zhang, Ming Tianjin University of Technology Tianjin China

ISBN: (纸本)9798350305623

With the development of science and technology, intelligent robots are widely used in navigation, exploration and medical fields. At the same time, the development of artificial intelligence algorithm is also gradually mature, and gradually applied in various fields. Specifically, ant colony algorithm is widely used in the field of path planning because it has global search capability and high robustness. However, the ant cluster algorithm has a problem that the convergence speed is slow and locally decreases. In order to solve the lack of colonial algorithms and the problem of path planning problems, we upgraded the ancient colony algorithm, compared the results of different algorithms using simulation software, and compared the path planning parameters, and tested the effectiveness of the colony algorithm. © 2023 IEEE.

关键词： Ant colony algorithm artificial intelligence algorithm Intelligent robot Path optimization

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Bike-sharing Demand Prediction based on artificial intelligence algorithm Using Weather Data

Bike-sharing Demand Prediction based on Artificial Intellige...

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2024 IEEE International Conference on Consumer Electronics, ICCE 2024

作者： Lee, Yebeen Son, Hyungju Ahn, Jiin Cho, Seokheon Konkuk University Department of Computer Science Engineering Seoul Korea Republic of Keimyung University Department of Transportation Engineering Daegu Korea Republic of Keimyung University Department of Biomedical Engineering Daegu Korea Republic of University of California Qualcomm Institute La Jolla San Diego United States

ISBN: (纸本)9798350324136

To alleviate traffic congestion and environmental pollution in heavily populated Seoul, South Korea, the city has actively introduced a bike-sharing service. As the demand for this service increases, efficient supply and management of shared bikes are becoming critically important. Because bike-sharing demand correlates with the weather, we performed a prediction for bike demand based on artificial intelligence algorithms utilizing weather data. The Multiple Linear Regression, Random Forest Regression, and Multi-Layer Perceptron artificial intelligence algorithms were considered and applied to processed weather data collected in Seoul using various methods. The results revealed that the best performance in predicting bike-sharing demand was achieved by a model trained by the Random Forest Regression algorithm, which considers historical weather and demand data and separates itself into two sub-datasets by weekdays and weekends, but without distinguishing itself with the information of the four seasons. © 2024 IEEE.

关键词： and bike-sharing service artificial intelligence algorithm bike-sharing demand prediction machine learning algorithm

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Utilization of Intelligent LIMS System Based on artificial intelligence algorithm in Environmental Evaluation

Utilization of Intelligent LIMS System Based on Artificial I...

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International Conference on Smart Applications and Sustainability in the artificial intelligence of Things, SAS-AIoT 2024

作者： Yao, Yao LiaoNing Vocational University of Technology Liaoning Jinzhou121000 China

ISBN: (纸本)9783031782756

In the process of environmental monitoring, the accuracy and reliability of laboratory testing data play a crucial role in the smooth progress of monitoring work. With the continuous development of environmental monitoring business, traditional manual methods can no longer meet the needs of environmental monitoring work. The article studied an intelligent LIMS (Laboratory Information Management System) based on artificial intelligence algorithms and elaborated on its application in environmental monitoring business. Firstly, a large amount of environmental evaluation data was collected and organized, and then convolutional neural networks were used to train and model these data to establish an environmental quality prediction model. Tests have proven that the intelligent LIMS established using convolutional neural networks has an assessment efficiency of 87.6% and an accuracy of 95%, providing strong support for environmental protection and governance work. The application of intelligent LIMS provides a new data management and analysis tool for the environment management department. © The Author(s), under exclusive license to Springer Nature Switzerland AG 2024.

关键词： artificial intelligence algorithm Convolutional Neural Network Environment Assessment Laboratory Information Management System

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Application of BP Neural Network and artificial intelligence algorithm in Pharmaceutical Production 1

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作者： Lin, Lianjun Shaanxi Fashion Engineering University Shaanxi Xi’an712046 China

ISBN: (数字)9789819719839

ISBN: (纸本)9789819719822

Backpropagation neural network (BP neural network) is a new efficient and highly parallel information processing pattern algorithm. artificial intelligence algorithms can enable systems to achieve rapid response and accurate calculations. This article analyzed the application of these two methods in pharmaceutical production, with the aim of improving pharmaceutical technology and level, ensuring safety and improving efficiency in drug production. This article mainly applied algorithm comparison and experimental simulation to analyze the application capabilities of BP neural network and genetic algorithm in pharmaceutical production. Experimental data showed that both BP neural network and genetic algorithm have improved the intelligence of pharmaceutical production by over 20%, both of which have a certain degree of improvement. © The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2024.

关键词： Application analysis artificial intelligence algorithm BP neural network Pharmaceutical production

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Research on signal analysis and diagnosis of chain drive system of the scraper conveyor guided by artificial intelligence algorithm

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OPTIK 2022年 271卷

作者： Mao, Jun Yang, Zhiyong Lu, Jinnan Liaoning Tech Univ Sch Mech Engn Liaoning 123000 Peoples R China

In order to improve the signal analysis and diagnosis effect of the chain drive system of the scraper conveyor, this paper combines the artificial intelligence algorithm to analyze and di-agnose the signal of the chain drive system of the scraper conveyor to judge the signal condition of the chain drive system of the scraper conveyor in time. Moreover, by referring to the actual application environment of the chain drive system of the scraper conveyor, the relevant pa-rameters of the signal are set, and the model is simulated. In addition, this paper analyzes the DC gain under different link conditions, and proves that it is more practical to consider the reflection in the channel through simulation. From the data statistics, the method proposed in this paper can play an important role in the signal analysis and diagnosis of the chain drive system of the scraper conveyor, and effectively improve the signal analysis and diagnosis accuracy of the chain drive system of the scraper conveyor.

关键词： Signal analysis and diagnosis research of scraper conveyor chain drive system guided by artificial intelligence algorithm

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Research on artificial intelligence algorithm and Optical Imaging Detection Based on Wireless IoT Devices in the Optimization Process of Strength Training

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MOBILE NETWORKS & APPLICATIONS 2024年

作者： Shi, Manman Guan, Lingxiang Leshan Normal Univ Leshan 614000 Sichuan Peoples R China Suan Sunandha Rajabhat Univ Coll Innovat & Management Bangkok Thailand

With the development of wireless iot devices, light imaging detection combined with artificial intelligence algorithms provides new possibilities for the optimization of strength training. The application of wireless sensor network makes data acquisition and real-time monitoring more efficient and convenient. In this study, a wireless sensor network was used to collect motion data during strength training, and the dynamic posture of athletes was monitored in real time by optical imaging technology. By feeding the collected data into a deep learning algorithm, the athlete's training performance is analyzed, potential risks are identified and personalized training recommendations are made. The experiment was carried out in multiple training scenarios and compared with traditional strength training monitoring methods. The experimental results show that the light imaging detection technology based on wireless Internet of Things can accurately identify the attitude deviation in motion, provide real-time feedback, and significantly improve the training effect and safety of athletes. In the process of strength training optimization, the algorithm can effectively analyze the data and improve the training scheme, which proves the effectiveness of artificial intelligence algorithm based on wireless Internet of Things devices combined with optical imaging detection technology in the process of strength training optimization.

关键词： Wireless Internet of Things equipment artificial intelligence algorithm Optical imaging detection Strength training optimization

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Nonlinear transient deflections of multi-layer sector plate structures on auxetic concrete foundation: Introducing an artificial intelligence algorithm for nonlinear problems

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STRUCTURES 2024年 70卷

作者： Guo, Peixi Zhang, Yao Xi, Yu Saleem, Kashif El-Meligy, Mohammed Safarpour, Hamed Xijing Univ Xian 710123 Shaanxi Peoples R China Xijing Univ Shaanxi Key Lab Safety & Durabil Concrete Struct Xian 710123 Peoples R China King Saud Univ Coll Appl Studies & Community Serv Dept Comp Sci & Engn Riyadh 11362 Saudi Arabia Jadara Univ Res Ctr POB 733 Irbid Jordan Appl Sci Private Univ Appl Sci Res Ctr Amman Jordan

This paper presents a comprehensive study on the nonlinear transient deflections of multi-layer sector plates, with a focus on presenting an artificial intelligence algorithm for addressing nonlinear problems in structural mechanics using the datasets of mathematical simulation. Multi-layer sector plates, commonly used in various engineering applications, exhibit complex nonlinear behaviors under external loading, particularly when coupled with unconventional materials such as auxetic concrete foundations. In this study, we propose the use of a mathematical simulation to analyze the nonlinear transient deflections of multi-layer sector plates on an auxetic concrete foundation. After that, a dataset (approximately 3750 data) is obtained and the algorithm is trained to capture the intricate nonlinear responses of the structure under different loading conditions. By leveraging an artificial intelligence algorithm, the algorithm can accurately predict the nonlinear behaviors of the multi-layer sector plate system, including vibration characteristics, dynamic response, and stability analysis. Through extensive numerical and validation studies, we demonstrate the effectiveness of the current mathematical modeling in accurately capturing the nonlinear transient deflections of multi-layer sector plates on auxetic concrete foundations. Furthermore, the proposed machine learning algorithm offers a promising approach for addressing nonlinear problems in structural mechanics, providing a versatile and efficient tool for engineers to analyze and optimize complex structural systems. By integrating machine learning techniques into structural analysis, researchers can enhance the accuracy and efficiency of nonlinear transient deflection studies, paving the way for advancements in structural engineering and related fields.

关键词： Nonlinear transient deflections Auxetic concrete foundation artificial intelligence algorithm Multi-layer sector plates FG-GOEM

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Application of artificial intelligence algorithm in Indoor Virtual Display System

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Procedia Computer Science 2023年 228卷 1294-1301页

作者： Ye Wang Yanmin Li School of Art Design and Media Sanda University Shanghai 201209 China Institute of Applied Research on Intelligent Science & Technology Jiangsu and Chinese Academy of Sciences Changzhou 213164 Jiangsu China

In recent years, virtual exhibition technology has been continuously developed and extended. Indoor virtual exhibition is assisted by various information technologies, and artificial intelligence algorithms are more and more used. Indoor virtual exhibition can gradually create a more infectious and personalized exhibition space, and through this space, the contents to be displayed are displayed to the audience in a purposeful and planned way. With the continuous evolution and development of artificial intelligence, the space and application fields of indoor virtual display are becoming more and more extensive. From various science and technology museums, museums, exhibition halls to game venues, fashion design, interior design and many other fields, we can see the integration of artificial intelligence and indoor virtual display. This paper studies and analyzes the development of artificial intelligence algorithm, focusing on its integration with indoor virtual display system, hoping to provide some reference for the development of indoor virtual display technology.

关键词： artificial intelligence algorithm International Trade Indoor Virtual Display

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