Pub Date : 2022-11-01DOI: 10.26599/IJCS.2022.9100025
Yutao Yang;Yuxuan Shi;Tianmei Wang
With the deepening application of blockchain technology, exaggerating its empowering effects has become common. In recent years, the rational assessment of the maturity of blockchain technology applications in digital projects in different fields has been the focus of attention and identified as the key to improving the implementation effect of various digital projects. Although some studies have obtained substantial research results on technology maturity and its derivative applications, which can be used to predict the overall trend of a technology or guide the implementation of the technology on the ground, few studies have evaluated the maturity of blockchain technology in combination with different application scenarios. Our study combines application scenarios and the technical characteristics of blockchain technology and proposes an evaluation system for blockchain technology application maturity consisting of five primary indicators, that is, key application requirements, data security, process complexity, application ecological completeness, and technical performance requirements, and their corresponding secondary indicators. In addition, we take digital government public service projects as application scenarios and use the analytic hierarchy process (AHP) entropy method and expert scoring method to determine the weights corresponding to each index in the assessment system and construct a blockchain technology application maturity assessment model. Moreover, we apply the model to ten typical digital government public service projects to conduct a comprehensive assessment and analysis. By comparing the indicator scores of the different projects, we analyze the project characteristics influencing blockchain technology application maturity and provide suggestions for applying “blockchain + digital government public services”.
{"title":"Blockchain Technology Application Maturity Assessment Model for Digital Government Public Service Projects","authors":"Yutao Yang;Yuxuan Shi;Tianmei Wang","doi":"10.26599/IJCS.2022.9100025","DOIUrl":"https://doi.org/10.26599/IJCS.2022.9100025","url":null,"abstract":"With the deepening application of blockchain technology, exaggerating its empowering effects has become common. In recent years, the rational assessment of the maturity of blockchain technology applications in digital projects in different fields has been the focus of attention and identified as the key to improving the implementation effect of various digital projects. Although some studies have obtained substantial research results on technology maturity and its derivative applications, which can be used to predict the overall trend of a technology or guide the implementation of the technology on the ground, few studies have evaluated the maturity of blockchain technology in combination with different application scenarios. Our study combines application scenarios and the technical characteristics of blockchain technology and proposes an evaluation system for blockchain technology application maturity consisting of five primary indicators, that is, key application requirements, data security, process complexity, application ecological completeness, and technical performance requirements, and their corresponding secondary indicators. In addition, we take digital government public service projects as application scenarios and use the analytic hierarchy process (AHP) entropy method and expert scoring method to determine the weights corresponding to each index in the assessment system and construct a blockchain technology application maturity assessment model. Moreover, we apply the model to ten typical digital government public service projects to conduct a comprehensive assessment and analysis. By comparing the indicator scores of the different projects, we analyze the project characteristics influencing blockchain technology application maturity and provide suggestions for applying “blockchain + digital government public services”.","PeriodicalId":32381,"journal":{"name":"International Journal of Crowd Science","volume":"6 4","pages":"184-194"},"PeriodicalIF":0.0,"publicationDate":"2022-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://ieeexplore.ieee.org/iel7/9736195/9969528/09969575.pdf","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"50407173","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2022-11-01DOI: 10.26599/IJCS.2022.9100021
Fatima Isiaka;Zainab Adamu;Muhammad A. Adamu
In a video game review, the main focus is the narratives, characters, graphics, and mechanics in the gameplay. Some recent research mentions the user interface only when it comes into light as a creative platform for simple interactive narratives from a technical point of view; this narrative is mainly a software tool that requires traditionally modernized inputs from the user. The user needs to interact with the navigational controls or menus in order to start a basic game play. A complex game interface as stimulus is generally considered as having a feeling of immersion that allows for visual tracking of user behavioural patterns and use it to predict the next strategy of the user using robust computational models. A number of users have limited sensory perception in a gameplay and hence rely on complex game stimulus and an adaptive model is paramount when considering behavioural expectations that place the user in a digital environment with more expressive perceptions. We developed a custom based eye tracking and 3D object detection algorithm which was utilised by recruiting users to interact with visual 3D objects and trace their eye movement behaviour to generated data. We then applied the use of recurrent neural network (RNN) for direct tracing of user behavioural activities in a sequential manner to predict their behaviour for interface adaptation. Result indicates that redundant user attributes are flexible and flawless for identifying predicted response of the user in a controlled environment. This would lead to prototypical representation of user behavioural analytics as an embedded platform in the confined digital environment. One of the limitations of the project is its inability to basically specify the 3D gaze point at the inner boundaries of the visual field. Data visualisation is strictly based on combined object flow detection. The originality of the work is its ability to redefine fixation point to a rendered cascaded 3D gaze point and space-defined saccade which is indicated by the distance between one gaze points to the other. The 3D gaze point would be well suited for fixation generalisation on 3D as well as on 2D digital oriented environment.
{"title":"User Experience Adaptation of Complex Game Interface for User Behaviour Modeling Using RNN","authors":"Fatima Isiaka;Zainab Adamu;Muhammad A. Adamu","doi":"10.26599/IJCS.2022.9100021","DOIUrl":"10.26599/IJCS.2022.9100021","url":null,"abstract":"In a video game review, the main focus is the narratives, characters, graphics, and mechanics in the gameplay. Some recent research mentions the user interface only when it comes into light as a creative platform for simple interactive narratives from a technical point of view; this narrative is mainly a software tool that requires traditionally modernized inputs from the user. The user needs to interact with the navigational controls or menus in order to start a basic game play. A complex game interface as stimulus is generally considered as having a feeling of immersion that allows for visual tracking of user behavioural patterns and use it to predict the next strategy of the user using robust computational models. A number of users have limited sensory perception in a gameplay and hence rely on complex game stimulus and an adaptive model is paramount when considering behavioural expectations that place the user in a digital environment with more expressive perceptions. We developed a custom based eye tracking and 3D object detection algorithm which was utilised by recruiting users to interact with visual 3D objects and trace their eye movement behaviour to generated data. We then applied the use of recurrent neural network (RNN) for direct tracing of user behavioural activities in a sequential manner to predict their behaviour for interface adaptation. Result indicates that redundant user attributes are flexible and flawless for identifying predicted response of the user in a controlled environment. This would lead to prototypical representation of user behavioural analytics as an embedded platform in the confined digital environment. One of the limitations of the project is its inability to basically specify the 3D gaze point at the inner boundaries of the visual field. Data visualisation is strictly based on combined object flow detection. The originality of the work is its ability to redefine fixation point to a rendered cascaded 3D gaze point and space-defined saccade which is indicated by the distance between one gaze points to the other. The 3D gaze point would be well suited for fixation generalisation on 3D as well as on 2D digital oriented environment.","PeriodicalId":32381,"journal":{"name":"International Journal of Crowd Science","volume":"6 4","pages":"159-166"},"PeriodicalIF":0.0,"publicationDate":"2022-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://ieeexplore.ieee.org/iel7/9736195/9969528/09969550.pdf","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"46567670","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2022-11-01DOI: 10.26599/IJCS.2022.9100027
Wengxiang Dong;H. Vicky Zhao
In this paper, we provide a detailed review of two categories of the literature: the spontaneous protective behaviors of individuals during disease spread and the mandatory measures to control the disease spread. In the literature, the models of individual protective behaviors can be divided into two parts: the environment-induced protective behaviors and the information-induced protective behaviors. And the mandatory measures of disease control can be divided into two parts: the macro-based control methods and the micro-based control methods. We provide a detailed review to the various categories of research. Then we compare the effects of different control methods through simulation. Among the micro-based control methods, the method based on minimizing the largest eigenvalue has the best effect. This review is of crucial importance to summarize the studies of the spontaneous protective behaviors during disease spread and the mandatory measures to control the disease spread.
{"title":"Individual Behavior Modeling and Transmission Control During Disease Spread: A Review","authors":"Wengxiang Dong;H. Vicky Zhao","doi":"10.26599/IJCS.2022.9100027","DOIUrl":"10.26599/IJCS.2022.9100027","url":null,"abstract":"In this paper, we provide a detailed review of two categories of the literature: the spontaneous protective behaviors of individuals during disease spread and the mandatory measures to control the disease spread. In the literature, the models of individual protective behaviors can be divided into two parts: the environment-induced protective behaviors and the information-induced protective behaviors. And the mandatory measures of disease control can be divided into two parts: the macro-based control methods and the micro-based control methods. We provide a detailed review to the various categories of research. Then we compare the effects of different control methods through simulation. Among the micro-based control methods, the method based on minimizing the largest eigenvalue has the best effect. This review is of crucial importance to summarize the studies of the spontaneous protective behaviors during disease spread and the mandatory measures to control the disease spread.","PeriodicalId":32381,"journal":{"name":"International Journal of Crowd Science","volume":"6 4","pages":"223-229"},"PeriodicalIF":0.0,"publicationDate":"2022-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://ieeexplore.ieee.org/iel7/9736195/9969528/09969551.pdf","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"44523977","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Human society is evolving toward the future network information society. In this paper, we identify the interconnected level as the key factor driving the evolution of human society and incorporate it into our proposed evolutionary model of social formation. We show the entire process of social formation evolution at the interconnected level through theoretical analysis and simulation. Our result is consistent with what human beings have gone through. By contrast, the result presents the following four characteristics of the future network information society: the personalization of goods or services, the downsizing of enterprises or organizations, the decentralization of production or life, and the sharing of production or living tools. We regard the future network information society as a deeply interconnected “Primitive Society”.
{"title":"Future of Networked Information Society: A Deeply Interconnected “Primitive Society”","authors":"Xiao Sun;Jun Qian;Ziyang Wang;Jinwei Miao;Yueting Chai","doi":"10.26599/IJCS.2022.9100023","DOIUrl":"10.26599/IJCS.2022.9100023","url":null,"abstract":"Human society is evolving toward the future network information society. In this paper, we identify the interconnected level as the key factor driving the evolution of human society and incorporate it into our proposed evolutionary model of social formation. We show the entire process of social formation evolution at the interconnected level through theoretical analysis and simulation. Our result is consistent with what human beings have gone through. By contrast, the result presents the following four characteristics of the future network information society: the personalization of goods or services, the downsizing of enterprises or organizations, the decentralization of production or life, and the sharing of production or living tools. We regard the future network information society as a deeply interconnected “Primitive Society”.","PeriodicalId":32381,"journal":{"name":"International Journal of Crowd Science","volume":"6 4","pages":"178-183"},"PeriodicalIF":0.0,"publicationDate":"2022-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://ieeexplore.ieee.org/iel7/9736195/9969528/09969548.pdf","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"46916710","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
With the mutual interaction and dependence of several intelligent services, a crowd intelligence service network has been formed, and a service ecosystem has gradually emerged. Such a development produces an ever-increasing effect on our lives and the functioning of the whole society. These facts call for research on these phenomena with a new theory or perspective, including what a smart society looks like, how it functions and evolves, and where its boundaries and challenges are. However, the research on service ecosystems is distributed in many disciplines and fields, including computer science, artificial intelligence, complex theory, social network, biological ecosystem, and network economics, and there is still no unified research framework. The researchers always have a restricted view of the research process. Under this context, this paper summarizes the research status and future developments of service ecosystems, including their conceptual origin, evolutionary logic, research topic and scale, challenges, and opportunities. We hope to provide a roadmap for the research in this field and promote sound development.
{"title":"Research Roadmap of Service Ecosystems: A Crowd Intelligence Perspective","authors":"Xiao Xue;Guanding Li;Deyu Zhou;Yepeng Zhang;Lu Zhang;Yang Zhao;Zhiyong Feng;Lizhen Cui;Zhangbing Zhou;Xiao Sun;Xudong Lu;Shizhan Chen","doi":"10.26599/IJCS.2022.9100026","DOIUrl":"https://doi.org/10.26599/IJCS.2022.9100026","url":null,"abstract":"With the mutual interaction and dependence of several intelligent services, a crowd intelligence service network has been formed, and a service ecosystem has gradually emerged. Such a development produces an ever-increasing effect on our lives and the functioning of the whole society. These facts call for research on these phenomena with a new theory or perspective, including what a smart society looks like, how it functions and evolves, and where its boundaries and challenges are. However, the research on service ecosystems is distributed in many disciplines and fields, including computer science, artificial intelligence, complex theory, social network, biological ecosystem, and network economics, and there is still no unified research framework. The researchers always have a restricted view of the research process. Under this context, this paper summarizes the research status and future developments of service ecosystems, including their conceptual origin, evolutionary logic, research topic and scale, challenges, and opportunities. We hope to provide a roadmap for the research in this field and promote sound development.","PeriodicalId":32381,"journal":{"name":"International Journal of Crowd Science","volume":"6 4","pages":"195-222"},"PeriodicalIF":0.0,"publicationDate":"2022-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://ieeexplore.ieee.org/iel7/9736195/9969528/09969552.pdf","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"50407174","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2022-08-09DOI: 10.26599/IJCS.2022.9100002
Linzhi Shan;Hongbo Sun
In this paper, the Crowd Intelligence Network Model is applied to the simulation of epidemic spread. This model combines the multi-layer coupling network model and the two-stage feedback member model to study the epidemic spread mechanisms under multiple-scene intervention. First, this paper establishes a multi-layer coupled network structure based on the characteristic of Social Network, Information Network, and Monitor Network, namely, the Crowd Intelligence Network structure. Then, based on this structure, the digital-self model, which has a multiple-scene effect and two-stage feedback structure, is designed. It has an emotional state and infection state quantified by using attitude and self-protection levels. This paper uses the attitude level and self-protection level to quantify individual emotions and immune levels, and discusses the impact of individual emotions on epidemic prevention and control. Finally, the availability of the Crowd Intelligence Network Model on the epidemic spread is verified by comparing the simulation trend with the actual spread trend of COVID-19.
{"title":"COVID-19 Spread Simulation in a Crowd Intelligence Network","authors":"Linzhi Shan;Hongbo Sun","doi":"10.26599/IJCS.2022.9100002","DOIUrl":"10.26599/IJCS.2022.9100002","url":null,"abstract":"In this paper, the Crowd Intelligence Network Model is applied to the simulation of epidemic spread. This model combines the multi-layer coupling network model and the two-stage feedback member model to study the epidemic spread mechanisms under multiple-scene intervention. First, this paper establishes a multi-layer coupled network structure based on the characteristic of Social Network, Information Network, and Monitor Network, namely, the Crowd Intelligence Network structure. Then, based on this structure, the digital-self model, which has a multiple-scene effect and two-stage feedback structure, is designed. It has an emotional state and infection state quantified by using attitude and self-protection levels. This paper uses the attitude level and self-protection level to quantify individual emotions and immune levels, and discusses the impact of individual emotions on epidemic prevention and control. Finally, the availability of the Crowd Intelligence Network Model on the epidemic spread is verified by comparing the simulation trend with the actual spread trend of COVID-19.","PeriodicalId":32381,"journal":{"name":"International Journal of Crowd Science","volume":"6 3","pages":"117-127"},"PeriodicalIF":0.0,"publicationDate":"2022-08-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://ieeexplore.ieee.org/iel7/9736195/9853235/09853239.pdf","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"48535004","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2022-08-09DOI: 10.26599/IJCS.2022.9100014
Yizhan Fan;Zhenchao Tao;Jun Lin;Huanhuan Chen
Cervical cancer is a common gynecological cancer, and its common treatment method radiotherapy depends on target area delineation. The manual delineation work takes a long time and has low accuracy, so automating such delineation is important. At present, some traditional image segmentation algorithms for target area delineation have low accuracy rates. Deep learning algorithms also face some difficulties, such as insufficient data and long training time. As the popular network used in medical image segmentation, U-net still has several disadvantages when handling small targets with unclear boundaries. According to the characteristics of the clinical target volume target segmentation task of cervical cancer, this study modified the U-net structure and optimized the training loss to improve the accuracy of small target detection. The modified structure could handle target boundaries well with operations such as bilinear upsampling. Finally, the proposed algorithm was evaluated on the dataset and compared with several deep learning-based algorithms. Results indicate that the proposed approach has certain superiority.
{"title":"An Encoder-Decoder Network for Automatic Clinical Target Volume Target Segmentation of Cervical Cancer in CT Images","authors":"Yizhan Fan;Zhenchao Tao;Jun Lin;Huanhuan Chen","doi":"10.26599/IJCS.2022.9100014","DOIUrl":"10.26599/IJCS.2022.9100014","url":null,"abstract":"Cervical cancer is a common gynecological cancer, and its common treatment method radiotherapy depends on target area delineation. The manual delineation work takes a long time and has low accuracy, so automating such delineation is important. At present, some traditional image segmentation algorithms for target area delineation have low accuracy rates. Deep learning algorithms also face some difficulties, such as insufficient data and long training time. As the popular network used in medical image segmentation, U-net still has several disadvantages when handling small targets with unclear boundaries. According to the characteristics of the clinical target volume target segmentation task of cervical cancer, this study modified the U-net structure and optimized the training loss to improve the accuracy of small target detection. The modified structure could handle target boundaries well with operations such as bilinear upsampling. Finally, the proposed algorithm was evaluated on the dataset and compared with several deep learning-based algorithms. Results indicate that the proposed approach has certain superiority.","PeriodicalId":32381,"journal":{"name":"International Journal of Crowd Science","volume":"6 3","pages":"111-116"},"PeriodicalIF":0.0,"publicationDate":"2022-08-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://ieeexplore.ieee.org/iel7/9736195/9853235/09853238.pdf","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"45937418","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2022-08-09DOI: 10.26599/IJCS.2022.9100016
Zhishuo Liu;Fang Tian;Lida Li;Zhuonan Han;Yuqing Li
The crowd intelligence-based e-commerce transaction network (CleTN) is a distributed and unstructured network structure. Smart individuals, such as buyers, sellers, and third-party organizations, can store information in local nodes and connect and share information via moments. The purpose of this study is to design a product search algorithm on the basis of ant colony optimization (ACO) to achieve an efficient and accurate search for the product demand of a node in the network. We introduce the improved ideas of maximum and minimum ants to design a set of heuristic search algorithms on the basis of ACO. To reduce search blindness, additional relevant heuristic factors are selected to define the heuristic calculation equation. The pheromone update mechanism integrating into the product matching factor and forwarding probability is used to design the network search rules among nodes in the search algorithm. Finally, the search algorithm is facilitated by Java language programming and PeerSim software. Experimental results show that the algorithm has significant advantages over the flooding method and the random walk method in terms of search success rate, search time, product matching, search network consumption, and scalability. The search algorithm introduces the idea of improving the maximum and minimum ant colony system and proposes new ideas in the design of heuristic factors in the heuristic equation and the pheromone update strategy. The search algorithm can search for product information effectively.
{"title":"Product Search Algorithm Based on Improved Ant Colony Optimization in a Distributed Network","authors":"Zhishuo Liu;Fang Tian;Lida Li;Zhuonan Han;Yuqing Li","doi":"10.26599/IJCS.2022.9100016","DOIUrl":"10.26599/IJCS.2022.9100016","url":null,"abstract":"The crowd intelligence-based e-commerce transaction network (CleTN) is a distributed and unstructured network structure. Smart individuals, such as buyers, sellers, and third-party organizations, can store information in local nodes and connect and share information via moments. The purpose of this study is to design a product search algorithm on the basis of ant colony optimization (ACO) to achieve an efficient and accurate search for the product demand of a node in the network. We introduce the improved ideas of maximum and minimum ants to design a set of heuristic search algorithms on the basis of ACO. To reduce search blindness, additional relevant heuristic factors are selected to define the heuristic calculation equation. The pheromone update mechanism integrating into the product matching factor and forwarding probability is used to design the network search rules among nodes in the search algorithm. Finally, the search algorithm is facilitated by Java language programming and PeerSim software. Experimental results show that the algorithm has significant advantages over the flooding method and the random walk method in terms of search success rate, search time, product matching, search network consumption, and scalability. The search algorithm introduces the idea of improving the maximum and minimum ant colony system and proposes new ideas in the design of heuristic factors in the heuristic equation and the pheromone update strategy. The search algorithm can search for product information effectively.","PeriodicalId":32381,"journal":{"name":"International Journal of Crowd Science","volume":"6 3","pages":"128-134"},"PeriodicalIF":0.0,"publicationDate":"2022-08-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://ieeexplore.ieee.org/iel7/9736195/9853235/09853240.pdf","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"48805989","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2022-08-09DOI: 10.26599/IJCS.2022.9100019
Huisheng Wang;Yuejiang Li;H. Vicky Zhao
Accurate caseload prediction is of considerable importance for the regulation and control of government agencies. Many studies on the environmental factor of caseload using time series analysis (TSA) are available. However, minimal attention has been provided to the interaction factor, which is substantially complex at the microlevel of social networks. A new model, graphical evolution game theory model (GEGT) is proposed in this paper to describe case formation based on the graphical evolutionary game theory. A parameter estimation method is developed on the basis of the GEGT model, and the estimated parameters are used for prediction. Furthermore, a fusion algorithm (GETS) that combines the predictions given by the proposed GEGT and TSA models is introduced to improve the caseload prediction accuracy. The fusion algorithm GETS highlights the accuracy of the GEGT model in the early stage of prediction. This algorithm integrates the precision of the TSA model in the later stage, thus balancing model strengths. The contribution of this paper lies in its proposed caseload prediction method based on the GEGT model to analyze the interaction factor and design a novel fusion algorithm GETS. The proposed model in this work is more accurate than the existing model on the actual dataset.
{"title":"Caseload Prediction Using Graphical Evolutionary Game Theory and Time Series Analysis","authors":"Huisheng Wang;Yuejiang Li;H. Vicky Zhao","doi":"10.26599/IJCS.2022.9100019","DOIUrl":"10.26599/IJCS.2022.9100019","url":null,"abstract":"Accurate caseload prediction is of considerable importance for the regulation and control of government agencies. Many studies on the environmental factor of caseload using time series analysis (TSA) are available. However, minimal attention has been provided to the interaction factor, which is substantially complex at the microlevel of social networks. A new model, graphical evolution game theory model (GEGT) is proposed in this paper to describe case formation based on the graphical evolutionary game theory. A parameter estimation method is developed on the basis of the GEGT model, and the estimated parameters are used for prediction. Furthermore, a fusion algorithm (GETS) that combines the predictions given by the proposed GEGT and TSA models is introduced to improve the caseload prediction accuracy. The fusion algorithm GETS highlights the accuracy of the GEGT model in the early stage of prediction. This algorithm integrates the precision of the TSA model in the later stage, thus balancing model strengths. The contribution of this paper lies in its proposed caseload prediction method based on the GEGT model to analyze the interaction factor and design a novel fusion algorithm GETS. The proposed model in this work is more accurate than the existing model on the actual dataset.","PeriodicalId":32381,"journal":{"name":"International Journal of Crowd Science","volume":"6 3","pages":"142-149"},"PeriodicalIF":0.0,"publicationDate":"2022-08-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://ieeexplore.ieee.org/iel7/9736195/9853235/09853243.pdf","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"47858531","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
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