Pub Date : 2017-08-01DOI: 10.1109/GSIS.2017.8077699
Yingying Su, Yijing Wang, Chuanmin Mi
According to the status quo that China's cross-border e-commerce is expanding rapidly, we selected the total imports and exports of China's cross-border e-commerce from 2008 to 2015 with a view to make some predictions. Firstly, using Grey System Theory, we partly establish GM(1,1) model and DGM(1,1) model to forecast and analyze the next five years' total imports and exports of China's cross-border e-commerce. Secondly, we compare the two types of models with the actual values and calculate the residual difference. Finally, we choose the one whose residual difference is smaller as the better model which could lead to more valid and precise prediction results in order to deepen people's understanding about the current situation and development prospects of China's cross-border e-commerce.
{"title":"The forecast of development prospects of China's cross-border E-commerce based on grey system theory","authors":"Yingying Su, Yijing Wang, Chuanmin Mi","doi":"10.1109/GSIS.2017.8077699","DOIUrl":"https://doi.org/10.1109/GSIS.2017.8077699","url":null,"abstract":"According to the status quo that China's cross-border e-commerce is expanding rapidly, we selected the total imports and exports of China's cross-border e-commerce from 2008 to 2015 with a view to make some predictions. Firstly, using Grey System Theory, we partly establish GM(1,1) model and DGM(1,1) model to forecast and analyze the next five years' total imports and exports of China's cross-border e-commerce. Secondly, we compare the two types of models with the actual values and calculate the residual difference. Finally, we choose the one whose residual difference is smaller as the better model which could lead to more valid and precise prediction results in order to deepen people's understanding about the current situation and development prospects of China's cross-border e-commerce.","PeriodicalId":425920,"journal":{"name":"2017 International Conference on Grey Systems and Intelligent Services (GSIS)","volume":"30 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2017-08-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"127879900","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}
Pub Date : 2017-08-01DOI: 10.1109/GSIS.2017.8077665
Nanlei Chen, Nai-ming Xie, Bentao Su
Based on the idea of grey theory, the uncertain duration with clear extension but unclear intension in project scheduling can be characterized as the grey number. However, the operations of the grey number borrowed from other uncertainty theory had long puzzled scholars. This paper address grey project scheduling based on grey linear space. The grey linear operation based on grey linear space and comparison method based on the information background were proposed. Then grey project scheduling problem was studied. And the critical path method under grey linear space was developed. Finally, a numerical case was adopted to test effectiveness of proposed method. Results show grey project scheduling and grey critical path method could be established under grey linear space.
{"title":"Grey linear space based grey project scheduling","authors":"Nanlei Chen, Nai-ming Xie, Bentao Su","doi":"10.1109/GSIS.2017.8077665","DOIUrl":"https://doi.org/10.1109/GSIS.2017.8077665","url":null,"abstract":"Based on the idea of grey theory, the uncertain duration with clear extension but unclear intension in project scheduling can be characterized as the grey number. However, the operations of the grey number borrowed from other uncertainty theory had long puzzled scholars. This paper address grey project scheduling based on grey linear space. The grey linear operation based on grey linear space and comparison method based on the information background were proposed. Then grey project scheduling problem was studied. And the critical path method under grey linear space was developed. Finally, a numerical case was adopted to test effectiveness of proposed method. Results show grey project scheduling and grey critical path method could be established under grey linear space.","PeriodicalId":425920,"journal":{"name":"2017 International Conference on Grey Systems and Intelligent Services (GSIS)","volume":"24 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2017-08-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"115387257","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}
Pub Date : 2017-08-01DOI: 10.1109/GSIS.2017.8077671
Hong Liu, Qishan Zhang, Kuaisheng Zheng, Xiaoxiao Wang, Chuyue Lin
Fuel and exhaust gas emission is one of the main causes of environmental pollution due to transportation. In the logistics distribution network, considering customer satisfaction and three-dimensional container loading restraint and energy consumption, a multiobjection optimization model of vehicle routing is constructed in this paper, which is complex NP-Hard problem. A novel hybrid particle swarm optimization algorithm is proposed for solving the multiobjection optimization model, which can give a Pareto solution set. In order to help the decision makers in choosing a balanced optimal reference solution from Pareto, grey relation analysis is introduced to evaluate Pareto solutions, and the three dimensional container loading vehicle routing optimization scheme with soft window constraint is obtained. The research results show that the optimization and the algorithm are feasible.
{"title":"Ax three dimensional packing vehicle routing problem based on grey relation analysis","authors":"Hong Liu, Qishan Zhang, Kuaisheng Zheng, Xiaoxiao Wang, Chuyue Lin","doi":"10.1109/GSIS.2017.8077671","DOIUrl":"https://doi.org/10.1109/GSIS.2017.8077671","url":null,"abstract":"Fuel and exhaust gas emission is one of the main causes of environmental pollution due to transportation. In the logistics distribution network, considering customer satisfaction and three-dimensional container loading restraint and energy consumption, a multiobjection optimization model of vehicle routing is constructed in this paper, which is complex NP-Hard problem. A novel hybrid particle swarm optimization algorithm is proposed for solving the multiobjection optimization model, which can give a Pareto solution set. In order to help the decision makers in choosing a balanced optimal reference solution from Pareto, grey relation analysis is introduced to evaluate Pareto solutions, and the three dimensional container loading vehicle routing optimization scheme with soft window constraint is obtained. The research results show that the optimization and the algorithm are feasible.","PeriodicalId":425920,"journal":{"name":"2017 International Conference on Grey Systems and Intelligent Services (GSIS)","volume":"2 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2017-08-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"125289118","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}
Pub Date : 2017-08-01DOI: 10.1109/GSIS.2017.8077670
Dafang Li, Qingchun Wu
This paper tries to obtain the main factors influencing quality and safety of dairy products by using grey relation analysis model. We select 11 sub factors from four fields and confirm the system behavior character by applying principal component analysis. Finally, we find cow's milk yields, proportion of urban population, qualified rate of veterinary drug, qualified feed rate and the proportion of the population with College degree or above are the main factors influencing the quality and safety of dairy products. In light of the results, the paper concludes with some suggestions for local government to improve the quality and safety of dairy products.
{"title":"Applying principal component analysis and grey relation analysis to analyze the influence factors of quality and safety of dairy products in China","authors":"Dafang Li, Qingchun Wu","doi":"10.1109/GSIS.2017.8077670","DOIUrl":"https://doi.org/10.1109/GSIS.2017.8077670","url":null,"abstract":"This paper tries to obtain the main factors influencing quality and safety of dairy products by using grey relation analysis model. We select 11 sub factors from four fields and confirm the system behavior character by applying principal component analysis. Finally, we find cow's milk yields, proportion of urban population, qualified rate of veterinary drug, qualified feed rate and the proportion of the population with College degree or above are the main factors influencing the quality and safety of dairy products. In light of the results, the paper concludes with some suggestions for local government to improve the quality and safety of dairy products.","PeriodicalId":425920,"journal":{"name":"2017 International Conference on Grey Systems and Intelligent Services (GSIS)","volume":"107 7","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2017-08-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"120826833","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}
Pub Date : 2017-08-01DOI: 10.1109/GSIS.2017.8077685
Sheng Wang, Chen Yang, Xue An, H. Duan, Yongchang Yu
In this paper, by using grey system theory, grey relation analysis and trend prediction was carried out for the influencing factors of agricultural mechanization development levels in major granary provinces in China. At present, the total power of agricultural mechanization, total income from agricultural mechanization, fuel consumption for agricultural production have great influence on the agricultural mechanization development levels. Meanwhile, the development of agricultural machinery industry also belongs to the extensive mode of profit driven. For the next 6 years, the influencing factors were predicted by using the grey relation analysis model, and give proposals about changing the current domestic agricultural enterprises for the status of the pursuit of profit in the low-end agricultural market competition, increasing investment in R & D funding and so on.
{"title":"Grey relation analysis and trend predication for agricultural mechanization development levels in major granary provinces in China","authors":"Sheng Wang, Chen Yang, Xue An, H. Duan, Yongchang Yu","doi":"10.1109/GSIS.2017.8077685","DOIUrl":"https://doi.org/10.1109/GSIS.2017.8077685","url":null,"abstract":"In this paper, by using grey system theory, grey relation analysis and trend prediction was carried out for the influencing factors of agricultural mechanization development levels in major granary provinces in China. At present, the total power of agricultural mechanization, total income from agricultural mechanization, fuel consumption for agricultural production have great influence on the agricultural mechanization development levels. Meanwhile, the development of agricultural machinery industry also belongs to the extensive mode of profit driven. For the next 6 years, the influencing factors were predicted by using the grey relation analysis model, and give proposals about changing the current domestic agricultural enterprises for the status of the pursuit of profit in the low-end agricultural market competition, increasing investment in R & D funding and so on.","PeriodicalId":425920,"journal":{"name":"2017 International Conference on Grey Systems and Intelligent Services (GSIS)","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2017-08-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"122631721","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}
Pub Date : 2017-08-01DOI: 10.1109/GSIS.2017.8077716
N. Zhang, B. Li, Lin Liu
The study aims to research the effecting factors of the level of independent innovation ability in China, constructing innovation environment by the grey clustering model and build the national innovation capability evaluation index system, including the innovation input, innovation output and innovation potential of 4 indexes and 17 level two indexes. The related data of 26 countries was collected as sample and the center point of improved hybrid triangle whiten the function was used to divide area to four regions from the perspective of independent innovation ability based on the construction. This method provides the basis for the localization of independent innovation ability level of China, and finally finds out the reasons of China's independent innovation capacity development and puts forward relevant suggestions.
{"title":"Research on the construction of independent innovation capability in China based on grey comprehensive evaluation","authors":"N. Zhang, B. Li, Lin Liu","doi":"10.1109/GSIS.2017.8077716","DOIUrl":"https://doi.org/10.1109/GSIS.2017.8077716","url":null,"abstract":"The study aims to research the effecting factors of the level of independent innovation ability in China, constructing innovation environment by the grey clustering model and build the national innovation capability evaluation index system, including the innovation input, innovation output and innovation potential of 4 indexes and 17 level two indexes. The related data of 26 countries was collected as sample and the center point of improved hybrid triangle whiten the function was used to divide area to four regions from the perspective of independent innovation ability based on the construction. This method provides the basis for the localization of independent innovation ability level of China, and finally finds out the reasons of China's independent innovation capacity development and puts forward relevant suggestions.","PeriodicalId":425920,"journal":{"name":"2017 International Conference on Grey Systems and Intelligent Services (GSIS)","volume":"29 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2017-08-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"124896492","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}
Pub Date : 2017-08-01DOI: 10.1109/GSIS.2017.8077694
Wei Meng, B. Zeng, Hui Huang
Sulfur dioxide is an important source of atmospheric pollution. It is harmful to ecosystems, buildings and humans. Many countries are developing policies to reduce sulfur dioxide emissions. In this paper, prediction of China's sulfur dioxide emissions is studied by discrete grey model with fractional operators. The forecast result shows that the amount of sulfur dioxide emissions is steadily decreasing and the reduction policy in China is effective. According to the current trend, by 2020, the value of China's sulfur dioxide emissions will be only 86.843% of emissions in 2015.
{"title":"Forecasting of sulfur dioxide emissions in China based on optimized DGM(1,1)","authors":"Wei Meng, B. Zeng, Hui Huang","doi":"10.1109/GSIS.2017.8077694","DOIUrl":"https://doi.org/10.1109/GSIS.2017.8077694","url":null,"abstract":"Sulfur dioxide is an important source of atmospheric pollution. It is harmful to ecosystems, buildings and humans. Many countries are developing policies to reduce sulfur dioxide emissions. In this paper, prediction of China's sulfur dioxide emissions is studied by discrete grey model with fractional operators. The forecast result shows that the amount of sulfur dioxide emissions is steadily decreasing and the reduction policy in China is effective. According to the current trend, by 2020, the value of China's sulfur dioxide emissions will be only 86.843% of emissions in 2015.","PeriodicalId":425920,"journal":{"name":"2017 International Conference on Grey Systems and Intelligent Services (GSIS)","volume":"2 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2017-08-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"133813624","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}
Pub Date : 2017-08-01DOI: 10.1109/GSIS.2017.8077708
Haitao Li, Jiefang Wang, D. Luo, Dongyang Pang
In view of the uncertain multi-attribute decision-making problems when the state probabilities and options' attribute values are both three-parameter interval grey number, based on the application demand of risky investment decisions, a grey-stochastic risk dynamic multi-attribute decision making method based on Markov chain is proposed. The grey probability of state stochastic occurrence and the grey probability matrix of state stochastic transition are defined, then, the grey probability distribution of states at each future time is obtained based on the Markov chain transfer prediction method. Time weights are established by solving the optimization model, which is based on variance and time degree. Afterwards, the dynamic risk decision-making matrix is assembled into a static non-risk decision-making matrix. Finally, by means of constructing the optimal and inferior ideal projects, and based on Deng's grey relational analysis, the relative superior membership degree, which is used to measure the degree of each alternative project belonging to the optimal ideal project, can be figured out to rank the alternative projects. An example is presented to illustrate the effectiveness and feasibility of the proposed method.
{"title":"Grey random dynamic multiple-attribute decision-making method","authors":"Haitao Li, Jiefang Wang, D. Luo, Dongyang Pang","doi":"10.1109/GSIS.2017.8077708","DOIUrl":"https://doi.org/10.1109/GSIS.2017.8077708","url":null,"abstract":"In view of the uncertain multi-attribute decision-making problems when the state probabilities and options' attribute values are both three-parameter interval grey number, based on the application demand of risky investment decisions, a grey-stochastic risk dynamic multi-attribute decision making method based on Markov chain is proposed. The grey probability of state stochastic occurrence and the grey probability matrix of state stochastic transition are defined, then, the grey probability distribution of states at each future time is obtained based on the Markov chain transfer prediction method. Time weights are established by solving the optimization model, which is based on variance and time degree. Afterwards, the dynamic risk decision-making matrix is assembled into a static non-risk decision-making matrix. Finally, by means of constructing the optimal and inferior ideal projects, and based on Deng's grey relational analysis, the relative superior membership degree, which is used to measure the degree of each alternative project belonging to the optimal ideal project, can be figured out to rank the alternative projects. An example is presented to illustrate the effectiveness and feasibility of the proposed method.","PeriodicalId":425920,"journal":{"name":"2017 International Conference on Grey Systems and Intelligent Services (GSIS)","volume":"98 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2017-08-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"133337833","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}
Pub Date : 2017-08-01DOI: 10.1109/GSIS.2017.8077713
Qiuping Wang, Yiran Zhang, Yanting Xiao, Jidong Li
Fuzzy clustering has emerged as an important tool for discovering the structure of data. Kernel based clustering has emerged as an interesting and quite visible alternative in fuzzy clustering. Aimed at the problems of both a local optimum and depending on initialization strongly in the fuzzy c-means clustering algorithm (FCM), a method of kernel-based fuzzy c-means clustering based on fruit fly algorithms (FOAKFCM) is proposed in this paper. In this algorithm, the fruit fly algorithm is used to optimize the initial clustering center firstly, kernelbased fuzzy c-means clustering algorithm (KFCM) is used to classify data. At the same time we reference classification evaluation index to choose the fuzziness parameter in adaptive way. The clustering performance of FCM algorithm, KFCM algorithm, and the proposed algorithm is testified by test datasets. FCM algorithm and FOAKFCM are used for power load characteristic data classification, respectively. Experiment results show that FOAKFCM algorithm proposed overcomes FCM's defects efficiently and improves the clustering performance greatly.
{"title":"Kernel-based fuzzy C-means clustering based on fruit fly optimization algorithm","authors":"Qiuping Wang, Yiran Zhang, Yanting Xiao, Jidong Li","doi":"10.1109/GSIS.2017.8077713","DOIUrl":"https://doi.org/10.1109/GSIS.2017.8077713","url":null,"abstract":"Fuzzy clustering has emerged as an important tool for discovering the structure of data. Kernel based clustering has emerged as an interesting and quite visible alternative in fuzzy clustering. Aimed at the problems of both a local optimum and depending on initialization strongly in the fuzzy c-means clustering algorithm (FCM), a method of kernel-based fuzzy c-means clustering based on fruit fly algorithms (FOAKFCM) is proposed in this paper. In this algorithm, the fruit fly algorithm is used to optimize the initial clustering center firstly, kernelbased fuzzy c-means clustering algorithm (KFCM) is used to classify data. At the same time we reference classification evaluation index to choose the fuzziness parameter in adaptive way. The clustering performance of FCM algorithm, KFCM algorithm, and the proposed algorithm is testified by test datasets. FCM algorithm and FOAKFCM are used for power load characteristic data classification, respectively. Experiment results show that FOAKFCM algorithm proposed overcomes FCM's defects efficiently and improves the clustering performance greatly.","PeriodicalId":425920,"journal":{"name":"2017 International Conference on Grey Systems and Intelligent Services (GSIS)","volume":"43 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2017-08-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"133406728","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}
Pub Date : 2017-08-01DOI: 10.1109/GSIS.2017.8077672
Yong Liu, Hui Li, Xi Chen, B. Cao
With the accelerating process of urbanization, rural migrant workers flood into the cities. Research projects that aim at resettlement and employment promotion of these workers, social stability, as well as economic development have drawn attention of government and scholars alike. With respect to the matching problems of urban employment of rural migrant workers, grey incidence analysis and two-sided matching theory is exploited to establish a novel two-sided matching decision-making model between rural workers and their jobs. In this paper, first, grey incidence analysis is used to describe and measure the preference information and satisfaction degree of both rural workers and their jobs; from the perspective of satisfaction degree of matching subjects, stability of the matching plan and equality, a multi-objective optimization model for two-sided matching decision-making problem between rural workers and their jobs was constructed, based on minimum matching distance and minimum deviation of matching distance; then linear weighting method is exploited to convert the multi-objective matching model into a single-objective optimization model to determine the two-sided matching plan between rural workers and their jobs; finally, the real problem of urban employment of rural migrant workers is discussed.
{"title":"The urban employment matching decision-making of rural migrant workers based on grey incidence analysis","authors":"Yong Liu, Hui Li, Xi Chen, B. Cao","doi":"10.1109/GSIS.2017.8077672","DOIUrl":"https://doi.org/10.1109/GSIS.2017.8077672","url":null,"abstract":"With the accelerating process of urbanization, rural migrant workers flood into the cities. Research projects that aim at resettlement and employment promotion of these workers, social stability, as well as economic development have drawn attention of government and scholars alike. With respect to the matching problems of urban employment of rural migrant workers, grey incidence analysis and two-sided matching theory is exploited to establish a novel two-sided matching decision-making model between rural workers and their jobs. In this paper, first, grey incidence analysis is used to describe and measure the preference information and satisfaction degree of both rural workers and their jobs; from the perspective of satisfaction degree of matching subjects, stability of the matching plan and equality, a multi-objective optimization model for two-sided matching decision-making problem between rural workers and their jobs was constructed, based on minimum matching distance and minimum deviation of matching distance; then linear weighting method is exploited to convert the multi-objective matching model into a single-objective optimization model to determine the two-sided matching plan between rural workers and their jobs; finally, the real problem of urban employment of rural migrant workers is discussed.","PeriodicalId":425920,"journal":{"name":"2017 International Conference on Grey Systems and Intelligent Services (GSIS)","volume":"8 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2017-08-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"114481323","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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