The distribution of data has a significant impact on the results of classification.When the distribution of one class is insignificant compared to the distribution of another class,data imbalance occurs.This will resu...The distribution of data has a significant impact on the results of classification.When the distribution of one class is insignificant compared to the distribution of another class,data imbalance occurs.This will result in rising outlier values and noise.Therefore,the speed and performance of classification could be greatly affected.Given the above problems,this paper starts with the motivation and mathematical representing of classification,puts forward a new classification method based on the relationship between different classification formulations.Combined with the vector characteristics of the actual problem and the choice of matrix characteristics,we firstly analyze the orderly regression to introduce slack variables to solve the constraint problem of the lone point.Then we introduce the fuzzy factors to solve the problem of the gap between the isolated points on the basis of the support vector machine.We introduce the cost control to solve the problem of sample skew.Finally,based on the bi-boundary support vector machine,a twostep weight setting twin classifier is constructed.This can help to identify multitasks with feature-selected patterns without the need for additional optimizers,which solves the problem of large-scale classification that can’t deal effectively with the very low category distribution gap.展开更多
In ultra-dense networks(UDNs), large-scale deployment of femto base stations is an important technique for improving the network throughput and quality of service(QoS). In this paper, a multidimensional resource alloc...In ultra-dense networks(UDNs), large-scale deployment of femto base stations is an important technique for improving the network throughput and quality of service(QoS). In this paper, a multidimensional resource allocation algorithm based on noncooperation game theory is proposed to manage the resource allocation in UDNs, including transmission point association, user channels, and power. The algorithm derives a multidimensional resource optimization model and converts into a noncooperation game model according to the analysis of transmission point association user channel and power allocation. The algorithm includes two phases: transmission point association, and channel and power allocation. Then, feasible domain and discrete variables relaxation approaches are introduced to derive an approximate optimal multidimensional resource allocation solution with low complexity. Simulation results show that this method has some advantages in suppressing interference and improves the overall system throughput, while ensuring the QoS of femtocell users.展开更多
基金Hebei Province Key Research and Development Project(No.20313701D)Hebei Province Key Research and Development Project(No.19210404D)+13 种基金Mobile computing and universal equipment for the Beijing Key Laboratory Open Project,The National Social Science Fund of China(17AJL014)Beijing University of Posts and Telecommunications Construction of World-Class Disciplines and Characteristic Development Guidance Special Fund “Cultural Inheritance and Innovation”Project(No.505019221)National Natural Science Foundation of China(No.U1536112)National Natural Science Foundation of China(No.81673697)National Natural Science Foundation of China(61872046)The National Social Science Fund Key Project of China(No.17AJL014)“Blue Fire Project”(Huizhou)University of Technology Joint Innovation Project(CXZJHZ201729)Industry-University Cooperation Cooperative Education Project of the Ministry of Education(No.201902218004)Industry-University Cooperation Cooperative Education Project of the Ministry of Education(No.201902024006)Industry-University Cooperation Cooperative Education Project of the Ministry of Education(No.201901197007)Industry-University Cooperation Collaborative Education Project of the Ministry of Education(No.201901199005)The Ministry of Education Industry-University Cooperation Collaborative Education Project(No.201901197001)Shijiazhuang science and technology plan project(236240267A)Hebei Province key research and development plan project(20312701D)。
文摘The distribution of data has a significant impact on the results of classification.When the distribution of one class is insignificant compared to the distribution of another class,data imbalance occurs.This will result in rising outlier values and noise.Therefore,the speed and performance of classification could be greatly affected.Given the above problems,this paper starts with the motivation and mathematical representing of classification,puts forward a new classification method based on the relationship between different classification formulations.Combined with the vector characteristics of the actual problem and the choice of matrix characteristics,we firstly analyze the orderly regression to introduce slack variables to solve the constraint problem of the lone point.Then we introduce the fuzzy factors to solve the problem of the gap between the isolated points on the basis of the support vector machine.We introduce the cost control to solve the problem of sample skew.Finally,based on the bi-boundary support vector machine,a twostep weight setting twin classifier is constructed.This can help to identify multitasks with feature-selected patterns without the need for additional optimizers,which solves the problem of large-scale classification that can’t deal effectively with the very low category distribution gap.
基金supported by Natural Science Foundation of China (61372125)973 project (2013CB329104)+1 种基金Natural Science Foundation of the Higher Education Institutions of Jiangsu Province (16KJA510005)the open research fund of National Mobile Communications Research Laboratory, Southeast University (2013D01, 2015D10)
文摘In ultra-dense networks(UDNs), large-scale deployment of femto base stations is an important technique for improving the network throughput and quality of service(QoS). In this paper, a multidimensional resource allocation algorithm based on noncooperation game theory is proposed to manage the resource allocation in UDNs, including transmission point association, user channels, and power. The algorithm derives a multidimensional resource optimization model and converts into a noncooperation game model according to the analysis of transmission point association user channel and power allocation. The algorithm includes two phases: transmission point association, and channel and power allocation. Then, feasible domain and discrete variables relaxation approaches are introduced to derive an approximate optimal multidimensional resource allocation solution with low complexity. Simulation results show that this method has some advantages in suppressing interference and improves the overall system throughput, while ensuring the QoS of femtocell users.
