Similarity calculation is the most important basic algorithm in collaborative filtering recommendation. It plays an important role in calculating the similarity between users (items), finding nearest neighbors, and predicting scores. However, the existing similarity calculation is affected by over reliance on item scores and data sparsity, resulting in low accuracy of recommendation results. This paper proposes a personalized recommendation algorithm based on information entropy and particle swarm optimization, which takes into account the similarity of users’ score and preference characteristics. It uses random particle swarm optimization to optimize their weights to obtain the comprehensive similarity value. Experimental results on public data sets show that the proposed method can effectively improve the accuracy of recommendation results on the premise of ensuring recommendation coverage.
{"title":"A Personalized Recommendation Algorithm Based on Weighted Information Entropy and Particle Swarm Optimization","authors":"Shuhao Jiang, Jincheng Ding, Liyi Zhang","doi":"10.1155/2021/3209140","DOIUrl":"https://doi.org/10.1155/2021/3209140","url":null,"abstract":"Similarity calculation is the most important basic algorithm in collaborative filtering recommendation. It plays an important role in calculating the similarity between users (items), finding nearest neighbors, and predicting scores. However, the existing similarity calculation is affected by over reliance on item scores and data sparsity, resulting in low accuracy of recommendation results. This paper proposes a personalized recommendation algorithm based on information entropy and particle swarm optimization, which takes into account the similarity of users’ score and preference characteristics. It uses random particle swarm optimization to optimize their weights to obtain the comprehensive similarity value. Experimental results on public data sets show that the proposed method can effectively improve the accuracy of recommendation results on the premise of ensuring recommendation coverage.","PeriodicalId":18790,"journal":{"name":"Mob. Inf. Syst.","volume":"49 1","pages":"3209140:1-3209140:9"},"PeriodicalIF":0.0,"publicationDate":"2021-12-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"79125428","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Unmanned aerial vehicle (UAV) technique with flexible deployment has enabled the development of Internet of Things (IoT) applications. However, it is difficult to guarantee the freshness of information delivery for the energy-limited UAV. Thus, we study the trajectory design in the multiple-UAV communication system, in which the massive ground devices send the individual information to mobile UAV base stations under the demand of information freshness. First, an energy-efficiency (EE) maximization optimization problem is formulated under the rest energy, safety distance, and age of information (AoI) constraints. However, it is difficult to solve the optimization problem due to the nonconvex objective function and unknown dynamic environment. Second, a trajectory design based on the deep Q-network method is proposed, in which the state space considering energy efficiency, rest energy, and AoI and the efficient reward function related with EE performance are constructed, respectively. Furthermore, to avoid the dependency of training data for the neural network, the experience replay and random sampling for batch are adopted. Finally, we validate the system performance of the proposed scheme. Simulation results show that the proposed scheme can achieve a better EE performance compared with the benchmark scheme.
{"title":"Energy-Efficient UAV Trajectory Design with Information Freshness Constraint via Deep Reinforcement Learning","authors":"Xinmin Li, Jiahui Li, Dandan Liu","doi":"10.1155/2021/1430512","DOIUrl":"https://doi.org/10.1155/2021/1430512","url":null,"abstract":"Unmanned aerial vehicle (UAV) technique with flexible deployment has enabled the development of Internet of Things (IoT) applications. However, it is difficult to guarantee the freshness of information delivery for the energy-limited UAV. Thus, we study the trajectory design in the multiple-UAV communication system, in which the massive ground devices send the individual information to mobile UAV base stations under the demand of information freshness. First, an energy-efficiency (EE) maximization optimization problem is formulated under the rest energy, safety distance, and age of information (AoI) constraints. However, it is difficult to solve the optimization problem due to the nonconvex objective function and unknown dynamic environment. Second, a trajectory design based on the deep Q-network method is proposed, in which the state space considering energy efficiency, rest energy, and AoI and the efficient reward function related with EE performance are constructed, respectively. Furthermore, to avoid the dependency of training data for the neural network, the experience replay and random sampling for batch are adopted. Finally, we validate the system performance of the proposed scheme. Simulation results show that the proposed scheme can achieve a better EE performance compared with the benchmark scheme.","PeriodicalId":18790,"journal":{"name":"Mob. Inf. Syst.","volume":"17 1","pages":"1430512:1-1430512:9"},"PeriodicalIF":0.0,"publicationDate":"2021-12-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"82025869","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Globally, it is widely accepted that the physical health of the young generation is continuously declining which remained unnoticed in many countries including China. Therefore, it is very important to scientifically investigate the evaluation index system and effectively interrogate the current health position of the young generation especially students. The results regarding health issues will be further investigated in terms of finding the optimal solutions for improving the status quo. Considering adolescent physical health evaluation indicators of Chinese students, this paper introduces the new era of adolescent physical health evaluation which should focus on “health quality indicators” for analyzing the objectivity and applicability of the indicators through testing and research methods. The method of simulation experiment research is used to demonstrate the scientificity and validity of the index. The optimization of the physical health evaluation indicators of adolescent students helps in assessing the health quality of adolescents, scientifically and accurately. In addition, it can effectively improve the physical health problems faced by adolescents. The proposed model achieves the evaluation indicators of adolescent health quality, collects physical health information and exercise data of adolescent students in a certain area of the northwest through big data, and conducts research as the research object. Furthermore, through the collation and analysis of the correlation data of the aerobic capacity evaluation indicators, the results show that the mid-run test value currently used in China is negatively correlated with the relative value of the measured maximum oxygen uptake on the treadmill.
{"title":"The Physical Health Evaluation of Adolescent Students Based on Big Data","authors":"Chunyan Fan","doi":"10.1155/2021/2356869","DOIUrl":"https://doi.org/10.1155/2021/2356869","url":null,"abstract":"Globally, it is widely accepted that the physical health of the young generation is continuously declining which remained unnoticed in many countries including China. Therefore, it is very important to scientifically investigate the evaluation index system and effectively interrogate the current health position of the young generation especially students. The results regarding health issues will be further investigated in terms of finding the optimal solutions for improving the status quo. Considering adolescent physical health evaluation indicators of Chinese students, this paper introduces the new era of adolescent physical health evaluation which should focus on “health quality indicators” for analyzing the objectivity and applicability of the indicators through testing and research methods. The method of simulation experiment research is used to demonstrate the scientificity and validity of the index. The optimization of the physical health evaluation indicators of adolescent students helps in assessing the health quality of adolescents, scientifically and accurately. In addition, it can effectively improve the physical health problems faced by adolescents. The proposed model achieves the evaluation indicators of adolescent health quality, collects physical health information and exercise data of adolescent students in a certain area of the northwest through big data, and conducts research as the research object. Furthermore, through the collation and analysis of the correlation data of the aerobic capacity evaluation indicators, the results show that the mid-run test value currently used in China is negatively correlated with the relative value of the measured maximum oxygen uptake on the treadmill.","PeriodicalId":18790,"journal":{"name":"Mob. Inf. Syst.","volume":"10 1","pages":"2356869:1-2356869:6"},"PeriodicalIF":0.0,"publicationDate":"2021-12-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"89283141","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Although the research results of mobile teaching mode at home and abroad have been involved in all aspects of education and teaching and provided a lot of useful reference for subsequent researchers, the lack of research on WeChat interactive translation teaching mode makes the practical research in this field urgent. As China’s education industry continues to pursue international development, it is necessary to train a large number of international talents who have an international perspective, are familiar with international rules, and can participate in international affairs and international competition. However, to become an international talent, you must first have superior English communication skills and be able to deal with various international situations proficiently. The English education goals at the basic education stage are simply beyond reach and can only be cultivated through professional and systematic college English courses. This shows that college English education is at a crucial position in the future development of education. This study attempts to explore how to apply the interactive teaching mode supported by WeChat network platform in translation teaching and English learning of high school students, so as to improve students’ autonomy in translation practice, promote students’ personalized learning, and improve students’ interest and ability in English learning. Based on the investigation of a senior high school in our city, the school began to implement the interactive translation mobile teaching mode based on WeChat in September 2018. The experiment selected the change of students’ English learning achievements in a certain semester and judged whether the mobile teaching mode was conducive to the improvement of learning performance based on t-test. We also need to collect the needs of teachers and parents for the WeChat based mobile teaching mode and judge whether the mode can be promoted. The experimental results show that this teaching mode has an obvious effect on the improvement of students’ English scores, especially in the eighth grade, whose scores have increased from 72.6 to 75. Through the construction of WeChat based interactive translation mobile teaching mode, parents can fully understand the key points of English learning and make English tutoring more targeted and timely. This teaching mode is worthy of promotion in senior high school English course learning.
{"title":"WeChat-Based Interactive Translation Mobile Teaching Model","authors":"Fachang Wang, Qingling Wang, Cuifang Du","doi":"10.1155/2021/7054016","DOIUrl":"https://doi.org/10.1155/2021/7054016","url":null,"abstract":"Although the research results of mobile teaching mode at home and abroad have been involved in all aspects of education and teaching and provided a lot of useful reference for subsequent researchers, the lack of research on WeChat interactive translation teaching mode makes the practical research in this field urgent. As China’s education industry continues to pursue international development, it is necessary to train a large number of international talents who have an international perspective, are familiar with international rules, and can participate in international affairs and international competition. However, to become an international talent, you must first have superior English communication skills and be able to deal with various international situations proficiently. The English education goals at the basic education stage are simply beyond reach and can only be cultivated through professional and systematic college English courses. This shows that college English education is at a crucial position in the future development of education. This study attempts to explore how to apply the interactive teaching mode supported by WeChat network platform in translation teaching and English learning of high school students, so as to improve students’ autonomy in translation practice, promote students’ personalized learning, and improve students’ interest and ability in English learning. Based on the investigation of a senior high school in our city, the school began to implement the interactive translation mobile teaching mode based on WeChat in September 2018. The experiment selected the change of students’ English learning achievements in a certain semester and judged whether the mobile teaching mode was conducive to the improvement of learning performance based on t-test. We also need to collect the needs of teachers and parents for the WeChat based mobile teaching mode and judge whether the mode can be promoted. The experimental results show that this teaching mode has an obvious effect on the improvement of students’ English scores, especially in the eighth grade, whose scores have increased from 72.6 to 75. Through the construction of WeChat based interactive translation mobile teaching mode, parents can fully understand the key points of English learning and make English tutoring more targeted and timely. This teaching mode is worthy of promotion in senior high school English course learning.","PeriodicalId":18790,"journal":{"name":"Mob. Inf. Syst.","volume":"361 1","pages":"7054016:1-7054016:9"},"PeriodicalIF":0.0,"publicationDate":"2021-12-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"89055753","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
In order to standardize public resource trading activities and improve the operating efficiency of public resource trading platforms, this paper conducts research on the performance of public resource trading platforms. A three-level and 28-dimension performance evaluation index system for public resource trading platform is established by considering the four levels of “input-process-output-effect.” Besides, entropy weight method, gray clustering, and fuzzy comprehensive evaluation are integrated on this basis. Entropy weight method is used to determine the index weight, and the degree value of membership for indexes on gray class is determined based on gray clustering method and converted into a matrix. Then, fuzzy comprehensive evaluation method is used to determine the evaluation value and finally carry out the platform performance evaluation, which provides theoretical support for academic researchers to conduct follow-up research on the performance evaluation of public resource trading platforms.
{"title":"Performance Evaluation Model of Public Resource Trading Platform Using Entropy-Based Gray Clustering Method","authors":"Jian Wang, Jun Fang, Ling Dai, Jun Hu","doi":"10.1155/2021/7950466","DOIUrl":"https://doi.org/10.1155/2021/7950466","url":null,"abstract":"In order to standardize public resource trading activities and improve the operating efficiency of public resource trading platforms, this paper conducts research on the performance of public resource trading platforms. A three-level and 28-dimension performance evaluation index system for public resource trading platform is established by considering the four levels of “input-process-output-effect.” Besides, entropy weight method, gray clustering, and fuzzy comprehensive evaluation are integrated on this basis. Entropy weight method is used to determine the index weight, and the degree value of membership for indexes on gray class is determined based on gray clustering method and converted into a matrix. Then, fuzzy comprehensive evaluation method is used to determine the evaluation value and finally carry out the platform performance evaluation, which provides theoretical support for academic researchers to conduct follow-up research on the performance evaluation of public resource trading platforms.","PeriodicalId":18790,"journal":{"name":"Mob. Inf. Syst.","volume":"10 1","pages":"7950466:1-7950466:14"},"PeriodicalIF":0.0,"publicationDate":"2021-12-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"79102638","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Due to the rise of many fields such as e-commerce platforms, a large number of stream data has emerged. The incomplete labeling problem and concept drift problem of these data pose a huge challenge to the existing stream data classification methods. In this respect, a dynamic stream data classification algorithm is proposed for the stream data. For the incomplete labeling problem, this method introduces randomization and iterative strategy based on the very fast decision tree VFDT algorithm to design an iterative integration algorithm, and the algorithm uses the previous model classification result as the next model input and implements the voting mechanism for new data classification. At the same time, the window mechanism is used to store data and calculate the data distribution characteristics in the window, then, combined with the calculated result and the predicted amount of data to adjust the size of the sliding window. Experiments show the superiority of the algorithm in classification accuracy. The aim of the study is to compare different algorithms to evaluate whether classification model adapts to the current data environment.
{"title":"Stream Classification Algorithm Based on Decision Tree","authors":"Jinlin Guo, Haoran Wang, Xinwei Li, Li Zhang","doi":"10.1155/2021/3103053","DOIUrl":"https://doi.org/10.1155/2021/3103053","url":null,"abstract":"Due to the rise of many fields such as e-commerce platforms, a large number of stream data has emerged. The incomplete labeling problem and concept drift problem of these data pose a huge challenge to the existing stream data classification methods. In this respect, a dynamic stream data classification algorithm is proposed for the stream data. For the incomplete labeling problem, this method introduces randomization and iterative strategy based on the very fast decision tree VFDT algorithm to design an iterative integration algorithm, and the algorithm uses the previous model classification result as the next model input and implements the voting mechanism for new data classification. At the same time, the window mechanism is used to store data and calculate the data distribution characteristics in the window, then, combined with the calculated result and the predicted amount of data to adjust the size of the sliding window. Experiments show the superiority of the algorithm in classification accuracy. The aim of the study is to compare different algorithms to evaluate whether classification model adapts to the current data environment.","PeriodicalId":18790,"journal":{"name":"Mob. Inf. Syst.","volume":"57 5","pages":"3103053:1-3103053:11"},"PeriodicalIF":0.0,"publicationDate":"2021-12-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"72610727","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
This paper studies the competitiveness of listed companies in high-end equipment manufacturing industry by using random forest. Random forest is a supervised machine learning algorithm that is actually based on the regression and classification. It takes some important decisions that are always based upon the set of samples. It counts majority for the classification purposes while it takes an average for the regression. For empirical analysis, 88 listed companies are selected. It is found that there are great differences in comprehensive competitiveness among industries. Enterprise scale accounts for a high proportion in the comprehensive competitiveness, and its score often affects the comprehensive strength; and the gap between companies in the same industry is also obvious. The empirical evaluation results of this paper provide three enlightenments for enterprises to improve their comprehensive competitiveness, such as seizing the strategic opportunity to expand the market, expand the scale of enterprises, improve asset management, and narrow the industry gap.
{"title":"Prediction Algorithm of Collaborative Innovation Capability of High-End Equipment Manufacturing Enterprises Based on Random Forest","authors":"Zhen-Hong Xiao, Jianbang Shi, Rui Tan, Jun-wu Shen","doi":"10.1155/2021/8378274","DOIUrl":"https://doi.org/10.1155/2021/8378274","url":null,"abstract":"This paper studies the competitiveness of listed companies in high-end equipment manufacturing industry by using random forest. Random forest is a supervised machine learning algorithm that is actually based on the regression and classification. It takes some important decisions that are always based upon the set of samples. It counts majority for the classification purposes while it takes an average for the regression. For empirical analysis, 88 listed companies are selected. It is found that there are great differences in comprehensive competitiveness among industries. Enterprise scale accounts for a high proportion in the comprehensive competitiveness, and its score often affects the comprehensive strength; and the gap between companies in the same industry is also obvious. The empirical evaluation results of this paper provide three enlightenments for enterprises to improve their comprehensive competitiveness, such as seizing the strategic opportunity to expand the market, expand the scale of enterprises, improve asset management, and narrow the industry gap.","PeriodicalId":18790,"journal":{"name":"Mob. Inf. Syst.","volume":"18 1","pages":"8378274:1-8378274:6"},"PeriodicalIF":0.0,"publicationDate":"2021-12-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"85333022","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Lattice gas automaton is a mathematical model that is used to simulate the horizontal uniform evacuation behaviour of a group. However, extended lattice gas automata model is proposed to examine marine evacuation behaviour, which is subject to deck heeling. The application of distance accumulation algorithm and the conversion probability mostly make the extended model, while the approach deals with the most complicated ship evacuation. Moreover, the suggested model is expected to enhance the safety and efficiency of evacuation. The distance accumulation lattice gas automata model considers multiple movement behaviours, flow density, deck heeling, counterflow, and congestion. Movement behaviour will be severely affected in deck heeling process where people may walk normally, walk while bent over, or crawl. To verify the proposed model, 11 test scenarios and several emergency evacuation scenarios are demonstrated. The simulation results explain the validity of another experimental model. The number of people in counterflow, deck heeling, and difference in movement have a direct effect on evacuation, which is as discussed in results. This research article provides a brief study on ship design and crew response behaviour in case of mishap/accident.
{"title":"Application of Extended Lattice Gas Automata Model in Ship Evacuation Simulation","authors":"Haoyang Han, Jun-dong Zhang, Ruizheng Jiang","doi":"10.1155/2021/6335388","DOIUrl":"https://doi.org/10.1155/2021/6335388","url":null,"abstract":"Lattice gas automaton is a mathematical model that is used to simulate the horizontal uniform evacuation behaviour of a group. However, extended lattice gas automata model is proposed to examine marine evacuation behaviour, which is subject to deck heeling. The application of distance accumulation algorithm and the conversion probability mostly make the extended model, while the approach deals with the most complicated ship evacuation. Moreover, the suggested model is expected to enhance the safety and efficiency of evacuation. The distance accumulation lattice gas automata model considers multiple movement behaviours, flow density, deck heeling, counterflow, and congestion. Movement behaviour will be severely affected in deck heeling process where people may walk normally, walk while bent over, or crawl. To verify the proposed model, 11 test scenarios and several emergency evacuation scenarios are demonstrated. The simulation results explain the validity of another experimental model. The number of people in counterflow, deck heeling, and difference in movement have a direct effect on evacuation, which is as discussed in results. This research article provides a brief study on ship design and crew response behaviour in case of mishap/accident.","PeriodicalId":18790,"journal":{"name":"Mob. Inf. Syst.","volume":"2 1","pages":"6335388:1-6335388:13"},"PeriodicalIF":0.0,"publicationDate":"2021-12-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"87987250","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
The dual attributes of artificial intelligence AlphaGd production, combined with modern social culture, industrial economy, and other factors, show rich connotation and extension in the development process of film and television animation production from the perspective of artificial intelligence AlphaGd. This paper first discusses and analyzes the practical significance and points out that AI AlphaGd has powerful functions, can greatly improve the sense of animation, and can effectively promote the technological innovation of animation production, then introduces the role modeling ideas of AI AlphaGd, and describes the modeling steps. Finally, the application of AI AlphaGd works produced after the use of artificial intelligence AlphaGd is more lifelike and specific in both the embodiment of the character image and the basic picture effect, which can make the audience have a more comfortable and perfect viewing experience. After summarizing, this paper puts forward the shortcomings of perspective artificial intelligence AlphaGd. Artificial intelligence may be useful in key decision-making processes, but it may negate the need for humans to be involved in these discussions. In view of these shortcomings, further research and discussion are made to accumulate new experience for product development and production from the perspective of artificial intelligence AlphaGd.
{"title":"Film and TV Animation Production Based on Artificial Intelligence AlphaGd","authors":"Yu-ning Li","doi":"10.1155/2021/1104248","DOIUrl":"https://doi.org/10.1155/2021/1104248","url":null,"abstract":"The dual attributes of artificial intelligence AlphaGd production, combined with modern social culture, industrial economy, and other factors, show rich connotation and extension in the development process of film and television animation production from the perspective of artificial intelligence AlphaGd. This paper first discusses and analyzes the practical significance and points out that AI AlphaGd has powerful functions, can greatly improve the sense of animation, and can effectively promote the technological innovation of animation production, then introduces the role modeling ideas of AI AlphaGd, and describes the modeling steps. Finally, the application of AI AlphaGd works produced after the use of artificial intelligence AlphaGd is more lifelike and specific in both the embodiment of the character image and the basic picture effect, which can make the audience have a more comfortable and perfect viewing experience. After summarizing, this paper puts forward the shortcomings of perspective artificial intelligence AlphaGd. Artificial intelligence may be useful in key decision-making processes, but it may negate the need for humans to be involved in these discussions. In view of these shortcomings, further research and discussion are made to accumulate new experience for product development and production from the perspective of artificial intelligence AlphaGd.","PeriodicalId":18790,"journal":{"name":"Mob. Inf. Syst.","volume":"2 1","pages":"1104248:1-1104248:8"},"PeriodicalIF":0.0,"publicationDate":"2021-12-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"87984012","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
The purpose of this study is to conduct a mixed research from the perspective of customers perceived value and objective situational factors. The online learning platform for middle school students has a special situation of users (students) using and customers (parents) paying. When it studies the influencing factors of customers (parents) willingness to pay, it puts aside the interference of users’ using influencing factors and conducts a separate study. Firstly, the exploratory research based on the grounded theory carries out category extraction and model construction. Secondly, through empirical research to identify the specific relationship between the variables, we finally get the specific influencing factors of perceived value that affect customers’ willingness to pay. In objective situations, social influence directly affects customers’ willingness to pay. Online comments play a positive moderating role in the impact of perceived value on willingness to pay.
{"title":"A Study on Parents' Willingness to Pay for Online Learning of Middle School Students Based on Perceived Value","authors":"Guo-Wei Chen, Xiao-Fang Zhou, Ying Jin, Yang Liu","doi":"10.1155/2021/4300434","DOIUrl":"https://doi.org/10.1155/2021/4300434","url":null,"abstract":"The purpose of this study is to conduct a mixed research from the perspective of customers perceived value and objective situational factors. The online learning platform for middle school students has a special situation of users (students) using and customers (parents) paying. When it studies the influencing factors of customers (parents) willingness to pay, it puts aside the interference of users’ using influencing factors and conducts a separate study. Firstly, the exploratory research based on the grounded theory carries out category extraction and model construction. Secondly, through empirical research to identify the specific relationship between the variables, we finally get the specific influencing factors of perceived value that affect customers’ willingness to pay. In objective situations, social influence directly affects customers’ willingness to pay. Online comments play a positive moderating role in the impact of perceived value on willingness to pay.","PeriodicalId":18790,"journal":{"name":"Mob. Inf. Syst.","volume":"2 1","pages":"4300434:1-4300434:15"},"PeriodicalIF":0.0,"publicationDate":"2021-12-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"79010502","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
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