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International Conference on Modeling, Natural Language Processing and Machine Learning (CMNM)

作者： Hao Wenfei Shandong Univ Technol Law Sch Zibo Shandong Provin Peoples R China

ISBN: (纸本)9798400709760

In contemporary society, the advent of the digital economy is swiftly emerging as a novel catalyst propelling global economic advancement. Against this backdrop, the adept management of vast economic datasets has become a focal point of inquiry. Leveraging its robust data processing and learning capabilities, artificial intelligence algorithms offer fresh perspectives on the analysis and application of digital economic data. This discourse introduces sophisticated algorithms such as kernel principal component analysis, time series analysis, and support vector machines, culminating in the conception and realization of a data processing framework. Empirical analysis of real-world data validates the efficacy of the system, juxtaposed with comparative analyses to delve into the merits and limitations of various algorithms in digital economic data management. Ultimately, this research endeavors to furnish the domain of digital economics with scientifically grounded data processing methodologies and pragmatic strategic solutions.

关键词： artificial intelligence algorithms digital economy data processing systems

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Design of Children's Digital Education Resource Sharing Platform Based on artificial intelligence Algorithm

Design of Children's Digital Education Resource Sharing Plat...

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2023 IEEE International Conference on Electrical, Automation and Computer Engineering, ICEACE 2023

作者： Wang, Yibo School of Literature and Media Chongqing Second Normal University Chongqing China

ISBN: (纸本)9798350309614

With the rapid development of digital technology, the application of digital educational resources in children's education is becoming increasingly widespread. This paper aims to design a children's digital educational resource sharing platform based on artificial intelligence algorithms to provide high-quality educational resources and personalized learning methods through deep learning algorithms. Firstly, the paper introduces the basic knowledge of deep learning and common convolutional neural network architectures. Then, it describes in detail the technical design of the platform, including the application of HTML5, PHP language, and the relational database MySQL. Finally, the paper designs and implements the children's digital educational resource sharing platform based on artificial intelligence algorithms, and describes the system architecture and major functional implementation of the platform. In addition, the paper discusses the possibility of further development of the platform in the future, and emphasizes the importance of the children's digital educational resource sharing platform in improving educational quality and meeting the needs of personalized learning. © 2023 IEEE.

关键词： artificial intelligence algorithms children's education deep learning algorithms resource sharing platforms

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Analysis of Rural Tourism Route Planning System Based on artificial intelligence Algorithm 3

Analysis of Rural Tourism Route Planning System Based on Art...

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3rd International Conference on artificial intelligence and Autonomous Robot Systems, AIARS 2024

作者： Feng, Xiumei Qi, Haixia Guo, Lei Northeast Petroleum University Department of Management Qinhuangdao Hebei066000 China

ISBN: (纸本)9798350376173

Under the background of the era of tourism informatization and artificial intelligence (AI), higher requirements are adopted for the route planning of scenic spots. In this paper, in the rural tourism route planning system based on artificial intelligence algorithm, the rural tourism route planning system based on artificial intelligence algorithm is registered, and the information of scenic spots and users is saved. The tourism planning route selection module is used to select one from at least one tourism planning route, generate the text of travel plan and plan it intelligently. In the comparison of per capita tourism consumption of tourists of different ages before and after adopting this system, before adopting this system, the per capita tourism consumption of 18-30 years old was 2500 yuan, and after adopting this system, the per capita tourism consumption of 18-30 years old was 2000 yuan. This method can give full play to the advantages of rural areas, promote the development of rural tourism, and at the same time effectively promote the local economy, thus achieving the goal of rural revitalization. © 2024 IEEE.

关键词： artificial intelligence algorithms percapita tourism consumption route planning systems Rural tourism tourist attributes

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Leveraging artificial intelligence to Improve Voice Disorder Identification Through the Use of a Reliable Mobile App

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IEEE ACCESS 2019年 7卷 124048-124054页

作者： Verde, Laura De Pietro, Giuseppe Alrashoud, Mubarak Ghoneim, Ahmed Al-Mutib, Khaled N. Sannino, Giovanna CNR Inst High Performance Comp & Networking ICAR I-80131 Naples Italy King Saud Univ CCIS Dept Software Engn SWE Riyadh 11543 Saudi Arabia

The evolution of the Internet of Things, cloud computing and wireless communication has contributed to an advance in the interconnectivity, efficiency and data accessibility in smart cities, improving environmental sustainability, quality of life and well-being, knowledge and intellectual capital. In this scenario, the satisfaction of security and privacy requirements to preserve data integrity, confidentiality and authentication is of fundamental importance. In particular, this is essential in the healthcare sector, where health-related data are considered sensitive information able to reveal confidential details about the subject. In this regard, to limit the possibility of security attacks or privacy violations, we present a reliable mobile voice disorder detection system capable of distinguishing between healthy and pathological voices by using a machine learning algorithm. This latter is totally embedded in the mobile application, so it is able to classify the voice without the necessity of transmitting user data to or storing user data on any server. A Boosted Trees algorithm was used as the classifier, opportunely trained and validated on a dataset composed of 2003 voices. The most frequently considered acoustic parameters constituted the inputs of the classifier, estimated and analyzed in real time by the mobile application.

关键词： Voice disorders smart healthcare monitoring artificial intelligence algorithms smart cities security privacy

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Social entertainment robot based on artificial intelligence algorithm application in interactive mode of music classroom

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ENTERTAINMENT COMPUTING 2024年 51卷

作者： Song, Qianwen Xianyang Normal Univ Sch Mus Xianyang 712000 Shanxi Peoples R China

With the rapid development of artificial intelligence technology, in-depth research on the application of social entertainment robots in the field of education has become increasingly important. Therefore, this study aims to explore how to use social entertainment robots based on artificial intelligence algorithms to improve the interactive mode in music classrooms, in order to enhance learning effectiveness and classroom atmosphere. The study introduced the detection algorithm of social entertainment robots and designed a complete detection process for accurately locating and identifying social entertainment robots in music classrooms. A machine data classification detection algorithm has been proposed to accurately determine the behavior and function of social entertainment robots. The social entertainment robot teaching module guides students to actively participate in music classroom activities through simulated conversations and interactive demonstrations. Interactive tests were conducted in actual music classrooms to evaluate the effectiveness of social entertainment robots in the classroom and student feedback. Through experiments, it has been proven that social entertainment robots based on artificial intelligence algorithms can effectively enhance the interactivity and fun of music classrooms. It not only promotes communication and cooperation among students, but also enhances learning participation.

关键词： artificial intelligence algorithms Social entertainment robots Music classroom Classroom interaction

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Assessment of the Potential of Indirect Measurement for Sap Flow Using Environmental Factors and artificial intelligence Approach: A Case Study of Magnolia denudata in Shanghai Urban Green Spaces

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FORESTS 2023年第9期14卷 1768-1768页

作者： Zhang, Biao Zhang, Dongmei Feng, Zhongke Zhang, Lang Zhang, Mingjuan Fu, Renjie Wang, Zhichao Beijing Forestry Univ Precis Forestry Key Lab Beijing Tsinghua East Rd Beijing 100083 Peoples R China Shanghai Acad Landscape Architecture Sci & Plannin 899 Longwu Rd Shanghai 200232 Peoples R China

The measurement of plant sap flow has long been a traditional method for quantifying transpiration. However, conventional direct measurement methods are often costly and complex, thereby limiting the widespread application of tree sap flow monitoring techniques. The concept of a Virtual Measurement Instrument (VMI) has emerged in response to this challenge by combining simple instruments with artificial intelligence (AI) algorithms to indirectly assess specific measurement objects. This study proposes a tree sap flow estimation method based on environmental factors and AI algorithms. Through the acquisition of environmental factor data and the integration of AI algorithms, we successfully achieved indirect measurement of tree sap flow. Accounting for the time lag response of the flow to environmental factors, we constructed the Magnolia denudata sap flow estimation model using the K-Nearest Neighbor (KNN), Random Forest (RF), Backpropagation Neural Network (BPNN), and Long Short-Term Memory network (LSTM) algorithms. The research results showed that the LSTM model demonstrated greater reliability in predicting sap flow velocity, with R-2 of 0.957, MAE of 0.189, MSE of 0.059, and RMSE of 0.243. The validation of the target tree yielded an R-2 of 0.821 and an error rate of only 4.89% when applying the model. In summary, this sap flow estimation method based on environmental factors and AI provides new insights and has practical value in the field of tree sap flow monitoring.

关键词： artificial intelligence algorithms computational virtual measurement environmental factors sap flow virtual measuring instrument

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artificial intelligence Applied to Drone Control: A State of the Art

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DRONES 2024年第7期8卷 296-296页

作者： Caballero-Martin, Daniel Lopez-Guede, Jose Manuel Estevez, Julian Grana, Manuel Univ Basque Country UPV EHU Grp Computat Intelligence San Sebastian 20018 Spain Univ Basque Country UPV EHU Fac Engn Alava C-Nieves Cano 12 Vitoria-gasteiz 01006 Spain Univ Basque Country UPV EHU Fac Engn Gipuzkoa Europa Plaza 1 San Sebastian 20018 Spain Univ Basque Country UPV EHU Fac Comp Sci Paseo Manuel de Lardizabal 1 Donostia San Sebastian 20018 Spain

The integration of artificial intelligence (AI) tools and techniques has provided a significant advance in drone technology. Besides the military applications, drones are being increasingly used for logistics and cargo transportation, agriculture, construction, security and surveillance, exploration, and mobile wireless communication. The synergy between drones and AI has led to notable progress in the autonomy of drones, which have become capable of completing complex missions without direct human supervision. This study of the state of the art examines the impact of AI on improving drone autonomous behavior, covering from automation to complex real-time decision making. The paper provides detailed examples of the latest developments and applications. Ethical and regulatory challenges are also considered for the future evolution of this field of research, because drones with AI have the potential to greatly change our socioeconomic landscape.

关键词： artificial intelligence algorithms drones cargo transport autonomous decisions

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Sports health monitoring management system based on artificial intelligence algorithm

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FRONTIERS IN PHYSICS 2023年 11卷

作者： Tong, Yunlong Ye, Lina Jilin Normal Univ Inst Phys Educ Siping Peoples R China Jilin Normal Univ Coll Math & Comp Siping Peoples R China

With the improvement of people's material living standards, more and more people start to pay attention to health issues. This paper takes the health field as the main research object, and discusses the current development and status quo of the health field. Through literature review, it is found that the current health field mainly focuses on the single monitoring of a certain organ or body function, and there are limitations in systematic health monitoring research, and most of the research stays at the stage of human body monitoring. Therefore, this paper intends to design a sports health monitoring and management system based on artificial intelligence. The system is mainly divided into a body temperature monitoring module, a blood pressure monitoring module and an exercise monitoring module, through which the user's health data is monitored. In order to ensure the practicability of the system, this paper selects three common life states in daily life for experimental testing, namely exercise state, rest state and sick state. The experimental test results show that each monitoring module can operate correctly and normally under three different states. The lowest temperature was 36.5 degrees and the highest temperature was 37.1 degrees under the exercise state. The lowest blood pressure is 70 in the resting state, and the highest blood pressure is 80. In the sick state, the maximum value of motor threshold is 0.2, the minimum value is 0.1, and the threshold difference is 0.1. Each module reads and backs up relevant data, and sends it to the platform for intelligent analysis. The platform will analyze and compare the data of different modules at the same time, judge the health status of the user at that time, choose whether to issue a health alert for the user, and finally complete the entire system process of the health monitoring management system. This proves that the sports health monitoring management system based on artificial intelligence algorithm designed

关键词： sports health monitoring and management system artificial intelligence algorithms body temperature monitoring monitoring of blood pressure artificial intelligence

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Hybrid artificial intelligence Based Automatic Determination of Travel Preferences of Chinese Tourists

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IEEE ACCESS 2019年 7卷 162530-162548页

作者： Topal, Ibrahim Ucar, Muhammed Kursad Natl Def Univ Dept Comp Technol TR-77720 Yalova Turkey Natl Def Univ Vocat Sch TR-77720 Yalova Turkey Sakarya Univ Fac Engn Dept Elect & Elect Engn TR-54050 Sakarya Turkey

Background and Objective: Tourism and travel sector continues to grow by gaining an important place in the world economy and many countries want to increase their share in this sector. At the same time, it is known that today's consumer tourism and travel purchase decisions are influenced by social media. By examining the data of consumers on social media, it is possible for businesses to reach the right person and get more efficiency from high-cost promotion activities. The study aims to analyze the historical data of users on TripAdvisor with artificial intelligence methods to reveal a profile of consumers who might prefer Turkey. Methods: In this context, TripAdvisor, which is one of the best-known websites in the tourism sector, is an important source of data for countries to increase their share in the tourism market. Inferences can be made by using artificial intelligence methods and the data in TripAdvisor together. In this study, as a case study, the potentials of Chinese tourists to prefer Turkey are dealt because Turkey has increased its tourism targets ten folds for China and the year 2018 was declared as "Turkey Tourism Year" in China. In this context, this study aims to determine the potentials of Chinese tourists to prefer Turkey, by processing travel data histories obtained from TripAdvisor with artificial intelligence methods. It is expected that the study will contribute to the tourism sector as well as the academic literature. The study used the travel data history of Chinese tourists taken from TripAdvisor. Significant travel histories were selected by the F-score method. Depending on the selected and all travel histories of users, their travel preferences (Turkey/France) were classified by artificial intelligence algorithms. The developed model was tested with performance criteria. Results: At the end of the study, it was ensured that the Chinese, who would prefer Turkey, were determined with an accuracy rate of 75.25% and sensitivity rate of 0.7

关键词： Marketing tourism travel user profile turkey tourism year Chinese tourism tripadvisor artificial intelligence algorithms ensemble classification

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Ambient Assisted Living: Scoping Review of artificial intelligence Models, Domains, Technology, and Concerns

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JOURNAL OF MEDICAL INTERNET RESEARCH 2022年第11期24卷 e36553页

作者： Jovanovic, Mladjan Mitrov, Goran Zdravevski, Eftim Lameski, Petre Colantonio, Sara Kampel, Martin Tellioglu, Hilda Florez-Revuelta, Francisco Singidunum Univ Dept Comp Sci Danijelova 32 Belgrade 11000 Serbia Univ St Cyril & Methodius Fac Comp Sci & Engn Skopje North Macedonia Natl Res Council Italy Inst Informat Sci & Technol Signals & Images Lab Pisa Italy Vienna Univ Technol Fac Informat Vienna Austria Univ Alicante Dept Comp Technol Alicante Spain

Background: Ambient assisted living (AAL) is a common name for various artificial intelligence (AI)-infused applications and platforms that support their users in need in multiple activities, from health to daily living. These systems use different approaches to learn about their users and make automated decisions, known as AI models, for personalizing their services and increasing outcomes. Given the numerous systems developed and deployed for people with different needs, health conditions, and dispositions toward the technology, it is critical to obtain clear and comprehensive insights concerning AI models used, along with their domains, technology, and concerns, to identify promising directions for future work. Objective: This study aimed to provide a scoping review of the literature on AI models in AAL. In particular, we analyzed specific AI models used in A.L systems, the target domains of the models, the technology using the models, and the major concerns from the end-user perspective. Our goal was to consolidate research on this topic and inform end users, health care professionals and providers, researchers, and practitioners in developing, deploying, and evaluating future intelligent AAL systems. Methods: This study was conducted as a scoping review to identify, analyze, and extract the relevant literature. It used a natural language processing toolkit to retrieve the article corpus for an efficient and comprehensive automated literature search. Relevant articles were then extracted from the corpus and analyzed manually. This review included 5 digital libraries: IEEE, PubMed, Springer, Elsevier, and MDPI. Results: We included a total of 108 articles. The annual distribution of relevant articles showed a growing trend for all categories from January 2010 to July 2022. The AI models mainly used unsupervised and semisupervised approaches. The leading models are deep learning, natural language processing, instance-based learning, and clustering. Activity assist

关键词： ambient assisted living AAL assisted living active living digital health digital well-being automated learning approach artificial intelligence algorithms human-centered AI review implications artificial intelligence mobile phone

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