New energy vehicles(NEVs) are gaining wider acceptance as the transportation sector is developing more environmentally friendly and sustainable technology. To solve problems of complex application scenarios and multi-...New energy vehicles(NEVs) are gaining wider acceptance as the transportation sector is developing more environmentally friendly and sustainable technology. To solve problems of complex application scenarios and multi-sources heterogenous data for new energy vehicles and weak platform scalability,the framework of an intelligent decision support platform is proposed in this paper. The principle of software and hardware system is introduced. Hadoop is adopted as the software system architecture of the platform. Master-standby redundancy and dual-line redundancy ensure the reliability of the hardware system. In addition, the applications on the intelligent decision support platform in usage patterns recognition, energy consumption, battery state of health and battery safety analysis are also described.展开更多
The gap of energy efficiency of eastern and central mining cities in China continues to expand, getting more attention from relevant departments. In this work, 20 mining cities in Eastern and Central China from 2010 t...The gap of energy efficiency of eastern and central mining cities in China continues to expand, getting more attention from relevant departments. In this work, 20 mining cities in Eastern and Central China from 2010 to 2014 have been selected as research samples using data envelopment analysis(DEA).Research results show that the level of energy efficiency in mining cities is still low. China is in an extensive economic growth mode with high input, high consumption, low output and low efficiency. Mining cities in China have a huge potential to conserve energy and reduce emissions. China should optimize industrial structures, strengthen scientific and technological input and innovation, as well as implement energy-saving emissions reductions, and increase investment in environmental protection and ideological propaganda.展开更多
训练飞行的首要前提就是保证人机安全,通过分析飞行数据来监控和评估飞行质量成为提高安全性和训练质量的手段之一。基于Energy-Metrics(能量度量)的异常飞行数据分析方法可为分析训练飞行安全分析提供帮助。提出了一种在训练飞行进近...训练飞行的首要前提就是保证人机安全,通过分析飞行数据来监控和评估飞行质量成为提高安全性和训练质量的手段之一。基于Energy-Metrics(能量度量)的异常飞行数据分析方法可为分析训练飞行安全分析提供帮助。提出了一种在训练飞行进近着陆阶段基于能量度量的异常飞行数据识别方法,首先,通过基于能量度量指标方法为飞行数据生成特征向量,然后,借助具有噪声的基于密度的聚类方法(density-based spatial clustering of applications with noise,DBSCAN)聚类和单类支持向量机(support vector machine,SVM)方法,对能量度量的指标数据特征向量进行飞行异常检测和识别。通过将模拟异常飞行数据隐藏在实际飞行数据中进行飞行数据的检测和识别,证明该方法的异常数据检测成功率为95%以上,且使用不同能量度量指标识别出的异常飞行数据具有高达98%的一致性,证明了该方法在识别异常飞行数据上具有较强的有效性和鲁棒性,为训练飞行回顾性安全分析提供有力的帮助。展开更多
Wastewater treatment plants(WWTPs)are important and energy-intensive municipal infrastructures.High energy consumption and relatively low operating performance are major challenges from the perspective of carbon neutr...Wastewater treatment plants(WWTPs)are important and energy-intensive municipal infrastructures.High energy consumption and relatively low operating performance are major challenges from the perspective of carbon neutrality.However,water-energy nexus analysis and models for WWTPs have rarely been reported to date.In this study,a cloud-model-based energy consumption analysis(CMECA)of a WWTP was conducted to explore the relationship between influent and energy consumption by clustering its influent’s parameters.The principal component analysis(PCA)and K-means clustering were applied to classify the influent condition using water quality and volume data.The energy consumption of the WWTP is divided into five standard evaluation levels,and its cloud digital characteristics(CDCs)were extracted according to bilateral constraints and golden ratio methods.Our results showed that the energy consumption distribution gradually dispersed and deviated from the Gaussian distribution with decreased water concentration and quantity.The days with high energy efficiency were extracted via the clustering method from the influent category of excessive energy consumption,represented by a compact-type energy consumption distribution curve to identify the influent conditions that affect the steady distribution of energy consumption.The local WWTP has high energy consumption with 0.3613 kW·h·m^(-3)despite low influent concentration and volumes,across four consumption levels from low(I)to relatively high(IV),showing an unsatisfactory operation and management level.The average oxygenation capacity,internal reflux ratio,and external reflux ratio during high energy efficiency days recognized by further clustering were obtained(0.2924-0.3703 kg O_(2)·m^(-3),1.9576-2.4787,and 0.6603-0.8361,respectively),which could be used as a guide for the days with low energy efficiency.Consequently,this study offers a water-energy nexus analysis method to identify influent conditions with operational management anomalies and can be used as an empirical reference for the optimized operation of WWTPs.展开更多
基金supported by the National Key Research and Development Program of China (2019YFB1600800)。
文摘New energy vehicles(NEVs) are gaining wider acceptance as the transportation sector is developing more environmentally friendly and sustainable technology. To solve problems of complex application scenarios and multi-sources heterogenous data for new energy vehicles and weak platform scalability,the framework of an intelligent decision support platform is proposed in this paper. The principle of software and hardware system is introduced. Hadoop is adopted as the software system architecture of the platform. Master-standby redundancy and dual-line redundancy ensure the reliability of the hardware system. In addition, the applications on the intelligent decision support platform in usage patterns recognition, energy consumption, battery state of health and battery safety analysis are also described.
基金provided by the National Natural Science Foundation of China (No. 51374114)a major program of humanities and social science research in Anhui (No. sk2014zd046)
文摘The gap of energy efficiency of eastern and central mining cities in China continues to expand, getting more attention from relevant departments. In this work, 20 mining cities in Eastern and Central China from 2010 to 2014 have been selected as research samples using data envelopment analysis(DEA).Research results show that the level of energy efficiency in mining cities is still low. China is in an extensive economic growth mode with high input, high consumption, low output and low efficiency. Mining cities in China have a huge potential to conserve energy and reduce emissions. China should optimize industrial structures, strengthen scientific and technological input and innovation, as well as implement energy-saving emissions reductions, and increase investment in environmental protection and ideological propaganda.
文摘训练飞行的首要前提就是保证人机安全,通过分析飞行数据来监控和评估飞行质量成为提高安全性和训练质量的手段之一。基于Energy-Metrics(能量度量)的异常飞行数据分析方法可为分析训练飞行安全分析提供帮助。提出了一种在训练飞行进近着陆阶段基于能量度量的异常飞行数据识别方法,首先,通过基于能量度量指标方法为飞行数据生成特征向量,然后,借助具有噪声的基于密度的聚类方法(density-based spatial clustering of applications with noise,DBSCAN)聚类和单类支持向量机(support vector machine,SVM)方法,对能量度量的指标数据特征向量进行飞行异常检测和识别。通过将模拟异常飞行数据隐藏在实际飞行数据中进行飞行数据的检测和识别,证明该方法的异常数据检测成功率为95%以上,且使用不同能量度量指标识别出的异常飞行数据具有高达98%的一致性,证明了该方法在识别异常飞行数据上具有较强的有效性和鲁棒性,为训练飞行回顾性安全分析提供有力的帮助。
基金the financial support from the National Key Research and Development Program of China(2019YFD1100204)the National Natural Science Foundation of China(52091545)+2 种基金the State Key Laboratory of Urban Water Resource and Environment,Harbin Institute of Technology(2021TS03)The Important Projects in the Scientific Innovation of CECEP(cecep-zdkj-2020-009)the Open Project of Key Laboratory of Environmental Biotechnology,Chinese Academy of Sciences(kf2018002).
文摘Wastewater treatment plants(WWTPs)are important and energy-intensive municipal infrastructures.High energy consumption and relatively low operating performance are major challenges from the perspective of carbon neutrality.However,water-energy nexus analysis and models for WWTPs have rarely been reported to date.In this study,a cloud-model-based energy consumption analysis(CMECA)of a WWTP was conducted to explore the relationship between influent and energy consumption by clustering its influent’s parameters.The principal component analysis(PCA)and K-means clustering were applied to classify the influent condition using water quality and volume data.The energy consumption of the WWTP is divided into five standard evaluation levels,and its cloud digital characteristics(CDCs)were extracted according to bilateral constraints and golden ratio methods.Our results showed that the energy consumption distribution gradually dispersed and deviated from the Gaussian distribution with decreased water concentration and quantity.The days with high energy efficiency were extracted via the clustering method from the influent category of excessive energy consumption,represented by a compact-type energy consumption distribution curve to identify the influent conditions that affect the steady distribution of energy consumption.The local WWTP has high energy consumption with 0.3613 kW·h·m^(-3)despite low influent concentration and volumes,across four consumption levels from low(I)to relatively high(IV),showing an unsatisfactory operation and management level.The average oxygenation capacity,internal reflux ratio,and external reflux ratio during high energy efficiency days recognized by further clustering were obtained(0.2924-0.3703 kg O_(2)·m^(-3),1.9576-2.4787,and 0.6603-0.8361,respectively),which could be used as a guide for the days with low energy efficiency.Consequently,this study offers a water-energy nexus analysis method to identify influent conditions with operational management anomalies and can be used as an empirical reference for the optimized operation of WWTPs.
