Many isolation approaches, such as zoning search, have been proposed to preserve the diversity in the decision space of multimodal multi-objective optimization(MMO). However, these approaches allocate the same computi...Many isolation approaches, such as zoning search, have been proposed to preserve the diversity in the decision space of multimodal multi-objective optimization(MMO). However, these approaches allocate the same computing resources for subspaces with different difficulties and evolution states. In order to solve this issue, this paper proposes a dynamic resource allocation strategy(DRAS)with reinforcement learning for multimodal multi-objective optimization problems(MMOPs). In DRAS, relative contribution and improvement are utilized to define the aptitude of subspaces, which can capture the potentials of subspaces accurately. Moreover, the reinforcement learning method is used to dynamically allocate computing resources for each subspace. In addition, the proposed DRAS is applied to zoning searches. Experimental results demonstrate that DRAS can effectively assist zoning search in finding more and better distributed equivalent Pareto optimal solutions in the decision space.展开更多
Aiming to provide a measurable service Quality of Service （ QoS） evaluating method for service inventory management, this paper proposes a new mobile Service Utility Model （SUM）, considers the service and business...Aiming to provide a measurable service Quality of Service （ QoS） evaluating method for service inventory management, this paper proposes a new mobile Service Utility Model （SUM）, considers the service and business layer elements into the service utility influence profile, and proposes an self-adaptive service inventory management algorithm as a QoS control scheme based on SUM. It can be concluded from the simulation result that the service inventory utility can be fully reflected by SUM and the whole system efficiency is greatly increased by using SUM as the adaptive rule.展开更多
In the scenario of downlink multicell processing with finite backhaul capacity in the case of two base stations and two mobile users, by regarding the channel as a multiple access diamond channel with two destinations...In the scenario of downlink multicell processing with finite backhaul capacity in the case of two base stations and two mobile users, by regarding the channel as a multiple access diamond channel with two destinations, an achievability scheme that sends correlated codewords through the multiple access channel with common data is proposed. By considering the superposition structure, fully correlated codewords can be supported by the proposed scheme, which can benefit the system throughput in the case of a relatively-large-capacity backhaul. First, an achievable region for the achievable theory is given and it is proved from the perspective of information theory. Then, in the Gaussian scenario, a simulation combining dirty-paper coding and power allocating is provided for the achievable region. Simulation results demonstrate that when the backhaul capacity is relatively large, the proposed scheme outperforms the existing achievability scheme without the superposition structure.展开更多
In this paper, we propose a new online system that can quickly detect malicious spam emails and adapt to the changes in the email contents and the Uniform Resource Locator (URL) links leading to malicious websites by ...In this paper, we propose a new online system that can quickly detect malicious spam emails and adapt to the changes in the email contents and the Uniform Resource Locator (URL) links leading to malicious websites by updating the system daily. We introduce an autonomous function for a server to generate training examples, in which double-bounce emails are automatically collected and their class labels are given by a crawler-type software to analyze the website maliciousness called SPIKE. In general, since spammers use botnets to spread numerous malicious emails within a short time, such distributed spam emails often have the same or similar contents. Therefore, it is not necessary for all spam emails to be learned. To adapt to new malicious campaigns quickly, only new types of spam emails should be selected for learning and this can be realized by introducing an active learning scheme into a classifier model. For this purpose, we adopt Resource Allocating Network with Locality Sensitive Hashing (RAN-LSH) as a classifier model with a data selection function. In RAN-LSH, the same or similar spam emails that have already been learned are quickly searched for a hash table in Locally Sensitive Hashing (LSH), in which the matched similar emails located in “well-learned” are discarded without being used as training data. To analyze email contents, we adopt the Bag of Words (BoW) approach and generate feature vectors whose attributes are transformed based on the normalized term frequency-inverse document frequency (TF-IDF). We use a data set of double-bounce spam emails collected at National Institute of Information and Communications Technology (NICT) in Japan from March 1st, 2013 until May 10th, 2013 to evaluate the performance of the proposed system. The results confirm that the proposed spam email detection system has capability of detecting with high detection rate.展开更多
Referring to a set of real time tasks with arriving time,executing time and deadline,this paperdiscusses the problem of polynomial time initial-allocating approximation algorithms in a distributedsystem and five new r...Referring to a set of real time tasks with arriving time,executing time and deadline,this paperdiscusses the problem of polynomial time initial-allocating approximation algorithms in a distributedsystem and five new results are gained which provide a theory for the designing of initial-allocating algorithmsof real time tasks.展开更多
河流生态系统的生物组成、结构和功能依赖于河流水流的天然动态变化特征,即河流水文情势。变异性范围法(Range of Variability Approach,RAV)被广泛应用于评估河流生态系统是否得到维护。将RVA法的思路扩展到生态流量的计算,提出了一种...河流生态系统的生物组成、结构和功能依赖于河流水流的天然动态变化特征,即河流水文情势。变异性范围法(Range of Variability Approach,RAV)被广泛应用于评估河流生态系统是否得到维护。将RVA法的思路扩展到生态流量的计算,提出了一种简便、立足整体河流水文情势的生态流量估算方法。该方法使用均值与RVA阈值差计算了生态流量值,为维持河流健康生态系统提供支持。将该方法应用于南水北调西线一期工程中泥曲河的生态流量估算,得到引水坝址仁达处年可调径流量为6.44亿m3,与其他生态需水估算方法的结论基本一致。另提出了可支配系数反映河流流量可调用状况。南水北调西线一期工程计划从泥曲调水8亿m3·a-1,从RVA法的理念来看,该方案对仁达至朱巴河段的生态系统将构成威胁,需谨慎实施。展开更多
文摘Many isolation approaches, such as zoning search, have been proposed to preserve the diversity in the decision space of multimodal multi-objective optimization(MMO). However, these approaches allocate the same computing resources for subspaces with different difficulties and evolution states. In order to solve this issue, this paper proposes a dynamic resource allocation strategy(DRAS)with reinforcement learning for multimodal multi-objective optimization problems(MMOPs). In DRAS, relative contribution and improvement are utilized to define the aptitude of subspaces, which can capture the potentials of subspaces accurately. Moreover, the reinforcement learning method is used to dynamically allocate computing resources for each subspace. In addition, the proposed DRAS is applied to zoning searches. Experimental results demonstrate that DRAS can effectively assist zoning search in finding more and better distributed equivalent Pareto optimal solutions in the decision space.
基金The workis supported by National Science Foundation of China(60372098) .
文摘Aiming to provide a measurable service Quality of Service （ QoS） evaluating method for service inventory management, this paper proposes a new mobile Service Utility Model （SUM）, considers the service and business layer elements into the service utility influence profile, and proposes an self-adaptive service inventory management algorithm as a QoS control scheme based on SUM. It can be concluded from the simulation result that the service inventory utility can be fully reflected by SUM and the whole system efficiency is greatly increased by using SUM as the adaptive rule.
基金The National Natural Science Foundation of China(No.61571123,61521061)the Research Fund of National Mobile Communications Research Laboratory of Southeast University(No.2017A03)Qing Lan Project
文摘In the scenario of downlink multicell processing with finite backhaul capacity in the case of two base stations and two mobile users, by regarding the channel as a multiple access diamond channel with two destinations, an achievability scheme that sends correlated codewords through the multiple access channel with common data is proposed. By considering the superposition structure, fully correlated codewords can be supported by the proposed scheme, which can benefit the system throughput in the case of a relatively-large-capacity backhaul. First, an achievable region for the achievable theory is given and it is proved from the perspective of information theory. Then, in the Gaussian scenario, a simulation combining dirty-paper coding and power allocating is provided for the achievable region. Simulation results demonstrate that when the backhaul capacity is relatively large, the proposed scheme outperforms the existing achievability scheme without the superposition structure.
文摘In this paper, we propose a new online system that can quickly detect malicious spam emails and adapt to the changes in the email contents and the Uniform Resource Locator (URL) links leading to malicious websites by updating the system daily. We introduce an autonomous function for a server to generate training examples, in which double-bounce emails are automatically collected and their class labels are given by a crawler-type software to analyze the website maliciousness called SPIKE. In general, since spammers use botnets to spread numerous malicious emails within a short time, such distributed spam emails often have the same or similar contents. Therefore, it is not necessary for all spam emails to be learned. To adapt to new malicious campaigns quickly, only new types of spam emails should be selected for learning and this can be realized by introducing an active learning scheme into a classifier model. For this purpose, we adopt Resource Allocating Network with Locality Sensitive Hashing (RAN-LSH) as a classifier model with a data selection function. In RAN-LSH, the same or similar spam emails that have already been learned are quickly searched for a hash table in Locally Sensitive Hashing (LSH), in which the matched similar emails located in “well-learned” are discarded without being used as training data. To analyze email contents, we adopt the Bag of Words (BoW) approach and generate feature vectors whose attributes are transformed based on the normalized term frequency-inverse document frequency (TF-IDF). We use a data set of double-bounce spam emails collected at National Institute of Information and Communications Technology (NICT) in Japan from March 1st, 2013 until May 10th, 2013 to evaluate the performance of the proposed system. The results confirm that the proposed spam email detection system has capability of detecting with high detection rate.
文摘Referring to a set of real time tasks with arriving time,executing time and deadline,this paperdiscusses the problem of polynomial time initial-allocating approximation algorithms in a distributedsystem and five new results are gained which provide a theory for the designing of initial-allocating algorithmsof real time tasks.
文摘河流生态系统的生物组成、结构和功能依赖于河流水流的天然动态变化特征,即河流水文情势。变异性范围法(Range of Variability Approach,RAV)被广泛应用于评估河流生态系统是否得到维护。将RVA法的思路扩展到生态流量的计算,提出了一种简便、立足整体河流水文情势的生态流量估算方法。该方法使用均值与RVA阈值差计算了生态流量值,为维持河流健康生态系统提供支持。将该方法应用于南水北调西线一期工程中泥曲河的生态流量估算,得到引水坝址仁达处年可调径流量为6.44亿m3,与其他生态需水估算方法的结论基本一致。另提出了可支配系数反映河流流量可调用状况。南水北调西线一期工程计划从泥曲调水8亿m3·a-1,从RVA法的理念来看,该方案对仁达至朱巴河段的生态系统将构成威胁,需谨慎实施。
