Intrusion detection systems provide additional defense capacity to a networked information system in addition to the security measures provided by the firewalls. This paper proposes an active rule based enhancement to...Intrusion detection systems provide additional defense capacity to a networked information system in addition to the security measures provided by the firewalls. This paper proposes an active rule based enhancement to the C4.5 algorithm for network intrusion detection in order to detect misuse behaviors of internal attackers through effective classification and decision making in computer networks. This enhanced C4.5 algorithm derives a set of classification rules from network audit data and then the generated rules are used to detect network intrusions in a real-time environment. Unlike most existing decision tree based approaches, the spawned rules generated and fired in this work are more effective because the information-theoretic approach minimizes the expected number of tests needed to classify an object and guarantees that a simple (but not necessarily the simplest) tree is found. The main advantage of this proposed algorithm is that the generalization ability of enhanced C4.5 decision trees is better than that of C4.5 decision trees. We have employed data from the third international knowledge discovery and data mining tools competition (KDDcup’99) to train and test the feasibility of this proposed model. By applying the enhanced C4.5 algorithm an average detection rate of 93.28 percent and a false positive rate of 0.7 percent have respectively been obtained in this work.展开更多
This paper proposes a novel cargo loading algorithm applicable to automated conveyor-type loading systems.The algorithm offers improvements in computational efficiency and robustness by utilizing the concept of discre...This paper proposes a novel cargo loading algorithm applicable to automated conveyor-type loading systems.The algorithm offers improvements in computational efficiency and robustness by utilizing the concept of discrete derivatives and introducing logistics-related constraints.Optional consideration of the rotation of the cargoes was made to further enhance the optimality of the solutions,if possible to be physically implemented.Evaluation metrics were developed for accurate evaluation and enhancement of the algorithm’s ability to efficiently utilize the loading space and provide a high level of dynamic stability.Experimental results demonstrate the extensive robustness of the proposed algorithm to the diversity of cargoes present in Business-to-Consumer environments.This study contributes practical advancements in both cargo loading optimization and automation of the logistics industry,with potential applications in last-mile delivery services,warehousing,and supply chain management.展开更多
As a distributed computing platform, Hadoop provides an effective way to handle big data. In Hadoop, the completion time of job will be delayed by a straggler. Although the definitive cause of the straggler is hard to...As a distributed computing platform, Hadoop provides an effective way to handle big data. In Hadoop, the completion time of job will be delayed by a straggler. Although the definitive cause of the straggler is hard to detect, speculative execution is usually used for dealing with this problem, by simply backing up those stragglers on alternative nodes. In this paper, we design a new Speculative Execution algorithm based on C4.5 Decision Tree, SECDT, for Hadoop. In SECDT, we speculate completion time of stragglers and also of backup tasks, based on a kind of decision tree method: C4.5 decision tree. After we speculate the completion time, we compare the completion time of stragglers and of the backup tasks, calculating their differential value, and selecting the straggler with the maximum differential value to start the backup task.Experiment result shows that the SECDT can predict execution time more accurately than other speculative execution methods, hence reduce the job completion time.展开更多
Association rules and C4.5 rules can overcome the shortage of the traditional land evaluation methods and improve the intelligibility and efficiency of the land evaluation knowledge.In order to compare these two kinds...Association rules and C4.5 rules can overcome the shortage of the traditional land evaluation methods and improve the intelligibility and efficiency of the land evaluation knowledge.In order to compare these two kinds of classification rules in the application,two fuzzy classifiers were established by combining with fuzzy decision algorithm especially based on Second General Soil Survey of Guangdong Province.The results of experiments demonstrated that the fuzzy classifier based on association rules obtain a higher accuracy rate,but with more complex calculation process and more computational overhead;the fuzzy classifier based on C4.5 rules obtain a slightly lower accuracy,but with fast computation and simpler calculation.展开更多
针对新能源电力系统中源荷不确定性导致的系统调度灵活性严重不足问题,文中提出了一种考虑源荷不确定性的电力系统两阶段鲁棒优化模型。根据源荷不确定性特征,结合K-means法和鲁棒优化理论,在多时间尺度对电力系统灵活性需求进行量化。...针对新能源电力系统中源荷不确定性导致的系统调度灵活性严重不足问题,文中提出了一种考虑源荷不确定性的电力系统两阶段鲁棒优化模型。根据源荷不确定性特征,结合K-means法和鲁棒优化理论,在多时间尺度对电力系统灵活性需求进行量化。首先,建立日前鲁棒调度模型,充分挖掘火电机组、抽水蓄能等资源的灵活调节潜力,将火电灵活改造及抽水蓄能抽发状态作为模型的第一阶段决策变量,各灵活资源的出力作为第二阶段决策变量,并以灵活改造成本、碳排放成本及运行成本最小为优化目标。其次,在模型求解中,将所建立的两阶段鲁棒模型转化为相对独立的主问题和子问题,并采用列与约束生成(column and constraint generation,C&CG)算法和强对偶理论反复迭代,以逼近最优解。最后,通过算例验证,所提出的优化调度策略在满足灵活性需求的基础上,统筹各类资源,实现了系统中经济性、环保性、灵活性的均衡,并增强了对源荷不确定性风险的抵御能力。展开更多
[Objective]The aim was to overcome the shortage of being difficult to build land evaluation model when the impact factors had continuous value in the traditional land evaluation process,as well as to improve the intel...[Objective]The aim was to overcome the shortage of being difficult to build land evaluation model when the impact factors had continuous value in the traditional land evaluation process,as well as to improve the intelligibility of the land evaluation knowledge.[Method] The land evaluation method combining classification rule extracted by C4.5 algorithm with fuzzy decision was proposed in this study.[Result] The result of Second General Soil Survey of Guangdong Province had demonstrated that the method was convenient to extract classification rules,and by using only 100 rules,quantity correct rate 86.67% and area correct rate 84.80% of land evaluation could be obtained.[Conclusions] The use of C4.5 algorithm to obtain the rules,combined with fuzzy decision algorithm to build classifiers had got satisfactory results,which provided a practical algorithm for the land evaluation.展开更多
文摘Intrusion detection systems provide additional defense capacity to a networked information system in addition to the security measures provided by the firewalls. This paper proposes an active rule based enhancement to the C4.5 algorithm for network intrusion detection in order to detect misuse behaviors of internal attackers through effective classification and decision making in computer networks. This enhanced C4.5 algorithm derives a set of classification rules from network audit data and then the generated rules are used to detect network intrusions in a real-time environment. Unlike most existing decision tree based approaches, the spawned rules generated and fired in this work are more effective because the information-theoretic approach minimizes the expected number of tests needed to classify an object and guarantees that a simple (but not necessarily the simplest) tree is found. The main advantage of this proposed algorithm is that the generalization ability of enhanced C4.5 decision trees is better than that of C4.5 decision trees. We have employed data from the third international knowledge discovery and data mining tools competition (KDDcup’99) to train and test the feasibility of this proposed model. By applying the enhanced C4.5 algorithm an average detection rate of 93.28 percent and a false positive rate of 0.7 percent have respectively been obtained in this work.
基金supported by the BK21 FOUR funded by the Ministry of Education of Korea and National Research Foundation of Korea,a Korea Agency for Infrastructure Technology Advancement(KAIA)grant funded by the Ministry of Land,Infrastructure,and Transport(Grant 1615013176)IITP(Institute of Information&Coummunications Technology Planning&Evaluation)-ICAN(ICT Challenge and Advanced Network of HRD)grant funded by the Korea government(Ministry of Science and ICT)(RS-2024-00438411).
文摘This paper proposes a novel cargo loading algorithm applicable to automated conveyor-type loading systems.The algorithm offers improvements in computational efficiency and robustness by utilizing the concept of discrete derivatives and introducing logistics-related constraints.Optional consideration of the rotation of the cargoes was made to further enhance the optimality of the solutions,if possible to be physically implemented.Evaluation metrics were developed for accurate evaluation and enhancement of the algorithm’s ability to efficiently utilize the loading space and provide a high level of dynamic stability.Experimental results demonstrate the extensive robustness of the proposed algorithm to the diversity of cargoes present in Business-to-Consumer environments.This study contributes practical advancements in both cargo loading optimization and automation of the logistics industry,with potential applications in last-mile delivery services,warehousing,and supply chain management.
文摘As a distributed computing platform, Hadoop provides an effective way to handle big data. In Hadoop, the completion time of job will be delayed by a straggler. Although the definitive cause of the straggler is hard to detect, speculative execution is usually used for dealing with this problem, by simply backing up those stragglers on alternative nodes. In this paper, we design a new Speculative Execution algorithm based on C4.5 Decision Tree, SECDT, for Hadoop. In SECDT, we speculate completion time of stragglers and also of backup tasks, based on a kind of decision tree method: C4.5 decision tree. After we speculate the completion time, we compare the completion time of stragglers and of the backup tasks, calculating their differential value, and selecting the straggler with the maximum differential value to start the backup task.Experiment result shows that the SECDT can predict execution time more accurately than other speculative execution methods, hence reduce the job completion time.
基金Supported by Science and Technology Plan Project of Guangdong Province (2009B010900026,2009CD058,2009CD078,2009CD079,2009CD080)Special Funds for Support Program of Development of Modern Information Service Industry of Guangdong Province(06120840B0370124)Funded Fund Project of South China Agricultural University (2007K017)~~
文摘Association rules and C4.5 rules can overcome the shortage of the traditional land evaluation methods and improve the intelligibility and efficiency of the land evaluation knowledge.In order to compare these two kinds of classification rules in the application,two fuzzy classifiers were established by combining with fuzzy decision algorithm especially based on Second General Soil Survey of Guangdong Province.The results of experiments demonstrated that the fuzzy classifier based on association rules obtain a higher accuracy rate,but with more complex calculation process and more computational overhead;the fuzzy classifier based on C4.5 rules obtain a slightly lower accuracy,but with fast computation and simpler calculation.
文摘针对新能源电力系统中源荷不确定性导致的系统调度灵活性严重不足问题,文中提出了一种考虑源荷不确定性的电力系统两阶段鲁棒优化模型。根据源荷不确定性特征,结合K-means法和鲁棒优化理论,在多时间尺度对电力系统灵活性需求进行量化。首先,建立日前鲁棒调度模型,充分挖掘火电机组、抽水蓄能等资源的灵活调节潜力,将火电灵活改造及抽水蓄能抽发状态作为模型的第一阶段决策变量,各灵活资源的出力作为第二阶段决策变量,并以灵活改造成本、碳排放成本及运行成本最小为优化目标。其次,在模型求解中,将所建立的两阶段鲁棒模型转化为相对独立的主问题和子问题,并采用列与约束生成(column and constraint generation,C&CG)算法和强对偶理论反复迭代,以逼近最优解。最后,通过算例验证,所提出的优化调度策略在满足灵活性需求的基础上,统筹各类资源,实现了系统中经济性、环保性、灵活性的均衡,并增强了对源荷不确定性风险的抵御能力。
基金Supported by Science and Technology Plan Project of Guangdong Province (2009B010900026,2009CD058,2009CD078,2009CD079,2009CD080)Special Funds for Support Program of Development of Modern Information Service Industry of Guangdong Province(06120840B0370124 )Fund Project of South China Agricultural University (2007K017)~~
文摘[Objective]The aim was to overcome the shortage of being difficult to build land evaluation model when the impact factors had continuous value in the traditional land evaluation process,as well as to improve the intelligibility of the land evaluation knowledge.[Method] The land evaluation method combining classification rule extracted by C4.5 algorithm with fuzzy decision was proposed in this study.[Result] The result of Second General Soil Survey of Guangdong Province had demonstrated that the method was convenient to extract classification rules,and by using only 100 rules,quantity correct rate 86.67% and area correct rate 84.80% of land evaluation could be obtained.[Conclusions] The use of C4.5 algorithm to obtain the rules,combined with fuzzy decision algorithm to build classifiers had got satisfactory results,which provided a practical algorithm for the land evaluation.
