In real-world many internet-based service companies need to closely monitor large amounts of data in order to ensure stable operation of their business.However,anomaly detection for these data with various patterns an...In real-world many internet-based service companies need to closely monitor large amounts of data in order to ensure stable operation of their business.However,anomaly detection for these data with various patterns and data quality has been a great challenge,especially without labels.In this paper,we adopt an anomaly detection algorithm based on Long Short-Term Memory(LSTM)Network in terms of reconstructing KPIs and predicting KPIs.They use the reconstruction error and prediction error respectively as the criteria for judging anomalies,and we test our method with real data from a company in the insurance industry and achieved good performance.展开更多
For many Internet companies,a huge amount of KPIs(e.g.,server CPU usage,network usage,business monitoring data)will be generated every day.How to closely monitor various KPIs,and then quickly and accurately detect ano...For many Internet companies,a huge amount of KPIs(e.g.,server CPU usage,network usage,business monitoring data)will be generated every day.How to closely monitor various KPIs,and then quickly and accurately detect anomalies in such huge data for troubleshooting and recovering business is a great challenge,especially for unlabeled data.The generated KPIs can be detected by supervised learning with labeled data,but the current problem is that most KPIs are unlabeled.That is a time-consuming and laborious work to label anomaly for company engineers.Build an unsupervised model to detect unlabeled data is an urgent need at present.In this paper,unsupervised learning DBSCAN combined with feature extraction of data has been used,and for some KPIs,its best F-Score can reach about 0.9,which is quite good for solving the current problem.展开更多
Most of the isolated electrical systems throughout the world suffer from similar problems of fragility and high dependence on external resources to generate energy. Smart Grid solutions and integration of renewable en...Most of the isolated electrical systems throughout the world suffer from similar problems of fragility and high dependence on external resources to generate energy. Smart Grid solutions and integration of renewable energies in order to solve their problems have increased, although it is necessary to know their specific characteristics to select the optimal solutions for each case. Therefore, as the overall objective of INSULAE Project, the development of an Investment Planning Tool, IPT, is on the way. This paper provides a view on a characterization methodology developed for the set of Reference Islands and how it will help to exploit the IPT developed. For that, characterization vectors have been defined based on a selection of Key Performance Indicators (KPIs). And Reference Islands have been obtained from the analysis of KPIs data gathered from EU islands considering the vectors formed. The linkage of new islands to reference islands helps provide the new islands with an assessment on the possibility space of their investment plans with the aim of being a decarbonization plan considering the demonstrations already evaluated.展开更多
This paper builds a self-adaptive management process in the power system dispatching area, aiming to effectively monitor the grid operation, dynamically adjust control strategy, optimize working process and ensure the...This paper builds a self-adaptive management process in the power system dispatching area, aiming to effectively monitor the grid operation, dynamically adjust control strategy, optimize working process and ensure the continuous improvement of operational performance. By building a negative feedback and dynamic balanced management mechanism, ECPRCB （East China Power Regulation Center Branch） is able to keenly sense the internal and external changes, efficiently coordinate all kinds of resources and improve the operational performance. As a result, self-adaptive management effectively boosts ECPRCB to reach the goal of being a world-class dispatching center with high operational performance, competent internal operation, adequate resources support and strong growth motion.展开更多
当今世界经济发展格局错综复杂,全球经济复苏进程缓慢,这一背景给全球制造企业供应链的发展带来了一定的冲击。在这样一个多变、不确定、复杂且模糊的时代,制造型企业面临着巨大的盈利能力挑战,亟须通过革新管理理念、提升内部管理效率...当今世界经济发展格局错综复杂,全球经济复苏进程缓慢,这一背景给全球制造企业供应链的发展带来了一定的冲击。在这样一个多变、不确定、复杂且模糊的时代,制造型企业面临着巨大的盈利能力挑战,亟须通过革新管理理念、提升内部管理效率来增强自身的核心竞争力。目前,在制造型企业中,大多数企业仍主要采用目标管理法、KPI考核、平衡计分卡、360度考核等绩效管理手段,整体上偏重结果导向,而对过程管理有所忽视,导致员工自驱力不足,难以适应当前快速变化的产业环境。在此背景下,通过对比分析不同绩效管理方法的优劣势,深入研究制造型企业如何高效运用OKR(Objectives and Key Results,目标与关键结果)管理法理念,以期打破现有的绩效管理思维局限,激发员工的自驱潜能,为新时代下的制造型企业提供敏捷创新的绩效管理思路。展开更多
文摘In real-world many internet-based service companies need to closely monitor large amounts of data in order to ensure stable operation of their business.However,anomaly detection for these data with various patterns and data quality has been a great challenge,especially without labels.In this paper,we adopt an anomaly detection algorithm based on Long Short-Term Memory(LSTM)Network in terms of reconstructing KPIs and predicting KPIs.They use the reconstruction error and prediction error respectively as the criteria for judging anomalies,and we test our method with real data from a company in the insurance industry and achieved good performance.
文摘For many Internet companies,a huge amount of KPIs(e.g.,server CPU usage,network usage,business monitoring data)will be generated every day.How to closely monitor various KPIs,and then quickly and accurately detect anomalies in such huge data for troubleshooting and recovering business is a great challenge,especially for unlabeled data.The generated KPIs can be detected by supervised learning with labeled data,but the current problem is that most KPIs are unlabeled.That is a time-consuming and laborious work to label anomaly for company engineers.Build an unsupervised model to detect unlabeled data is an urgent need at present.In this paper,unsupervised learning DBSCAN combined with feature extraction of data has been used,and for some KPIs,its best F-Score can reach about 0.9,which is quite good for solving the current problem.
文摘Most of the isolated electrical systems throughout the world suffer from similar problems of fragility and high dependence on external resources to generate energy. Smart Grid solutions and integration of renewable energies in order to solve their problems have increased, although it is necessary to know their specific characteristics to select the optimal solutions for each case. Therefore, as the overall objective of INSULAE Project, the development of an Investment Planning Tool, IPT, is on the way. This paper provides a view on a characterization methodology developed for the set of Reference Islands and how it will help to exploit the IPT developed. For that, characterization vectors have been defined based on a selection of Key Performance Indicators (KPIs). And Reference Islands have been obtained from the analysis of KPIs data gathered from EU islands considering the vectors formed. The linkage of new islands to reference islands helps provide the new islands with an assessment on the possibility space of their investment plans with the aim of being a decarbonization plan considering the demonstrations already evaluated.
文摘This paper builds a self-adaptive management process in the power system dispatching area, aiming to effectively monitor the grid operation, dynamically adjust control strategy, optimize working process and ensure the continuous improvement of operational performance. By building a negative feedback and dynamic balanced management mechanism, ECPRCB （East China Power Regulation Center Branch） is able to keenly sense the internal and external changes, efficiently coordinate all kinds of resources and improve the operational performance. As a result, self-adaptive management effectively boosts ECPRCB to reach the goal of being a world-class dispatching center with high operational performance, competent internal operation, adequate resources support and strong growth motion.
文摘当今世界经济发展格局错综复杂,全球经济复苏进程缓慢,这一背景给全球制造企业供应链的发展带来了一定的冲击。在这样一个多变、不确定、复杂且模糊的时代,制造型企业面临着巨大的盈利能力挑战,亟须通过革新管理理念、提升内部管理效率来增强自身的核心竞争力。目前,在制造型企业中,大多数企业仍主要采用目标管理法、KPI考核、平衡计分卡、360度考核等绩效管理手段,整体上偏重结果导向,而对过程管理有所忽视,导致员工自驱力不足,难以适应当前快速变化的产业环境。在此背景下,通过对比分析不同绩效管理方法的优劣势,深入研究制造型企业如何高效运用OKR(Objectives and Key Results,目标与关键结果)管理法理念,以期打破现有的绩效管理思维局限,激发员工的自驱潜能,为新时代下的制造型企业提供敏捷创新的绩效管理思路。
