为解决影响装备健康状态参数的权重分配及各参数评估值的融合问题,根据装备特点和其自身延寿需求,提出基于区间直觉模糊集(interval-valued intuitionistic fuzzy,IVIF)和融合逼近理想解排序法(technique for order preference by simil...为解决影响装备健康状态参数的权重分配及各参数评估值的融合问题,根据装备特点和其自身延寿需求,提出基于区间直觉模糊集(interval-valued intuitionistic fuzzy,IVIF)和融合逼近理想解排序法(technique for order preference by similarity to an ideal solution,TOPSIS)与秩和比法(ranksum ratio,RSR)的装备健康状态评估方法。引入IVIF确定决策专家自身权重,根据其评估犹豫度及相似度综合确定指标权重,获取加权规范化矩阵;建立TOPSIS-RSR的评估框架实现对装备的健康状态评估及决策;利用仿真案例对多个同型号装备健康状态进行评估排序分级,对比2种已知评估方法验证方法了的可行性。展开更多
Network selection and resource allocation( NS-RA) are the processes of determining network and radio resource which provide the service to user. Optimizing these processes is an important step towards maximizing the u...Network selection and resource allocation( NS-RA) are the processes of determining network and radio resource which provide the service to user. Optimizing these processes is an important step towards maximizing the utilization of current and future networks. In this paper,we proposed a preference value-based network selection and resource allocation,in which the NS scheme was performed by the joint radio resource management( JRRM) entity and the RA scheme was performed by the network. In the NS step,the JRRM entity selected the preferable network for users according to the preference value of each network,which took the load balance,the received signal strength( RSS) and the relative position between the user and the network into account. In the second step,the network allocated the optimal sub-carrier to user for the downlink transmission each round according to the preference value of each user and the maximum reachable data rate calculated by users' perceived channel information,maximizing the spectrum efficiency as well as guaranteeing the fairness. The simulation results showed that the proposed NS-RA scheme achieves better performance in terms of load distribution,spectrum efficiency and user fairness,compared to the conventional strategies.展开更多
In many practical situation, some of the attribute values for an object may be interval and set-valued. This paper introduces the interval and set-valued information systems and decision systems. According to the sema...In many practical situation, some of the attribute values for an object may be interval and set-valued. This paper introduces the interval and set-valued information systems and decision systems. According to the semantic relation of attribute values, interval and set-valued information systems can be classified into two categories: disjunctive (Type 1) and conjunctive (Type 2) systems. In this paper, we mainly focus on semantic interpretation of Type 1. Then, we define a new fuzzy preference relation and construct a fuzzy rough set model for interval and set-valued information systems. Moreover, based on the new fuzzy preference relation, the concepts of the significance measure of condition attributes and the relative significance measure of condition attributes are given in interval and set-valued decision information systems by the introduction of fuzzy positive region and the dependency degree. And on this basis, a heuristic algorithm for calculating fuzzy positive region reduction in interval and set-valued decision information systems is given. Finally, we give an illustrative example to substantiate the theoretical arguments. The results will help us to gain much more insights into the meaning of fuzzy rough set theory. Furthermore, it has provided a new perspective to study the attribute reduction problem in decision systems.展开更多
文摘为解决影响装备健康状态参数的权重分配及各参数评估值的融合问题,根据装备特点和其自身延寿需求,提出基于区间直觉模糊集(interval-valued intuitionistic fuzzy,IVIF)和融合逼近理想解排序法(technique for order preference by similarity to an ideal solution,TOPSIS)与秩和比法(ranksum ratio,RSR)的装备健康状态评估方法。引入IVIF确定决策专家自身权重,根据其评估犹豫度及相似度综合确定指标权重,获取加权规范化矩阵;建立TOPSIS-RSR的评估框架实现对装备的健康状态评估及决策;利用仿真案例对多个同型号装备健康状态进行评估排序分级,对比2种已知评估方法验证方法了的可行性。
基金Sponsored by the National Natural Science Funds of China(Grant No.61271182)the National High Technology Research and Development Program of China(Grant No.2012AA01A508)the Fundamental Research Funds for the Central Universities of China(Grant No.2013RC0112)
文摘Network selection and resource allocation( NS-RA) are the processes of determining network and radio resource which provide the service to user. Optimizing these processes is an important step towards maximizing the utilization of current and future networks. In this paper,we proposed a preference value-based network selection and resource allocation,in which the NS scheme was performed by the joint radio resource management( JRRM) entity and the RA scheme was performed by the network. In the NS step,the JRRM entity selected the preferable network for users according to the preference value of each network,which took the load balance,the received signal strength( RSS) and the relative position between the user and the network into account. In the second step,the network allocated the optimal sub-carrier to user for the downlink transmission each round according to the preference value of each user and the maximum reachable data rate calculated by users' perceived channel information,maximizing the spectrum efficiency as well as guaranteeing the fairness. The simulation results showed that the proposed NS-RA scheme achieves better performance in terms of load distribution,spectrum efficiency and user fairness,compared to the conventional strategies.
文摘In many practical situation, some of the attribute values for an object may be interval and set-valued. This paper introduces the interval and set-valued information systems and decision systems. According to the semantic relation of attribute values, interval and set-valued information systems can be classified into two categories: disjunctive (Type 1) and conjunctive (Type 2) systems. In this paper, we mainly focus on semantic interpretation of Type 1. Then, we define a new fuzzy preference relation and construct a fuzzy rough set model for interval and set-valued information systems. Moreover, based on the new fuzzy preference relation, the concepts of the significance measure of condition attributes and the relative significance measure of condition attributes are given in interval and set-valued decision information systems by the introduction of fuzzy positive region and the dependency degree. And on this basis, a heuristic algorithm for calculating fuzzy positive region reduction in interval and set-valued decision information systems is given. Finally, we give an illustrative example to substantiate the theoretical arguments. The results will help us to gain much more insights into the meaning of fuzzy rough set theory. Furthermore, it has provided a new perspective to study the attribute reduction problem in decision systems.
