The smart grid has been revolutionizing electrical generation and consumption through a two-way flow of power and information. As an important information source from the demand side, Advanced Metering Infrastructure ...The smart grid has been revolutionizing electrical generation and consumption through a two-way flow of power and information. As an important information source from the demand side, Advanced Metering Infrastructure （AMI） has gained increasing popularity all over the world. By making full use of the data gathered by AMI, stakeholders of the electrical industry can have a better understanding of electrical consumption behavior. This is a significant strategy to improve operation efficiency and enhance power grid reliability. To implement this strategy, researchers have explored many data mining techniques for load profiling. This paper performs a state-of-the-art, comprehensive review of these data mining techniques from the perspectives of different technical approaches including direct clustering, indirect clustering, clustering evaluation criteria, and customer segmentation. On this basis, the prospects for implementing load profiling to demand response applications, price-based and incentivebased, are further summarized. Finally, challenges and opportunities of load profiling techniques in future power industry, especially in a demand response world, are discussed.展开更多
Short-term traffic forecasting is a key element in proactive traffic management,e.g.,mitigating the negative effect of impending congestion through appropriate capacity allocation at signalized intersections.In this s...Short-term traffic forecasting is a key element in proactive traffic management,e.g.,mitigating the negative effect of impending congestion through appropriate capacity allocation at signalized intersections.In this study,we develop a data-driven methodology for reliably and robustly predicting impending stable congestion.By incorporating feature engineering techniques into an iterative machine learning process,we develop a prediction model that can be intuitively understood by traffic experts and is amenable to diagnostics during implementation.Our iterative machine learning process combines the embedded and filter approaches for feature selection with the use of expert knowledge to create aggregative input variables.The embedded approach is represented by application of a decision tree algorithm,while the filter approach is reflected in use of the mean decrease in accuracy output of a random forest algorithm for identifying expressive variables.We tested the methodology by applying it to field data from a sub-network in Tel Aviv.We demonstrated a reduction in the number of decision tree input variables from 66 raw variables to the five most effective aggregative ones,while achieving statistically significant improvement in all performance indicators.The identification rate of stable congestion increased from 65%to 74%while the robustness of the results was enhanced:the standard deviations of the identification and false alarm rates fell from 8%to 3%,respectively,to 5%and 2%.展开更多
Objective： To analyze the experience of chief physician Xiong Lu in treating metaphase and advanced lung cancer through using TCM inheritance support system （V2.5）. Methods： Collecting the prescriptions used for m...Objective： To analyze the experience of chief physician Xiong Lu in treating metaphase and advanced lung cancer through using TCM inheritance support system （V2.5）. Methods： Collecting the prescriptions used for metaphase and advanced lung cancer from November 1, 2014 to February 1, 2015, then the data were entered into the TCM inheritance support system. Based on principle analysis, revised mutual information, complex system entropy cluster and unsupervised hierarchical clustering composing principles were analyzed. Results： Based on the analysis of 228 cases of prescriptions, the frequency of each Chinese medicinal herb and association rules among herbs included in the database were computed. 15 core combinations and 2 new prescriptions were explored from the database. Conclusion： In treating metaphase and advanced lung cancer, chief physician Xiong Lu pay attention to Fuzheng Peiben （Therapy for support Zheng-qi to propup root）, according to the different situation cooperate with Tong Luo （dredging collaterals）, San Jie （Dissipating a mass）, Huo Xue （Activating blood）, Gong Du （Counteracting toxic substance） and so on. Xiong Lu is also good at using toxic drugs and incompatible medicaments.展开更多
基金supported by the National Science Fund for Distinguished Young Scholars (No. 51325702)
文摘The smart grid has been revolutionizing electrical generation and consumption through a two-way flow of power and information. As an important information source from the demand side, Advanced Metering Infrastructure （AMI） has gained increasing popularity all over the world. By making full use of the data gathered by AMI, stakeholders of the electrical industry can have a better understanding of electrical consumption behavior. This is a significant strategy to improve operation efficiency and enhance power grid reliability. To implement this strategy, researchers have explored many data mining techniques for load profiling. This paper performs a state-of-the-art, comprehensive review of these data mining techniques from the perspectives of different technical approaches including direct clustering, indirect clustering, clustering evaluation criteria, and customer segmentation. On this basis, the prospects for implementing load profiling to demand response applications, price-based and incentivebased, are further summarized. Finally, challenges and opportunities of load profiling techniques in future power industry, especially in a demand response world, are discussed.
基金Israeli Ministry of Science and Technology for funding this research(grant number 315606)。
文摘Short-term traffic forecasting is a key element in proactive traffic management,e.g.,mitigating the negative effect of impending congestion through appropriate capacity allocation at signalized intersections.In this study,we develop a data-driven methodology for reliably and robustly predicting impending stable congestion.By incorporating feature engineering techniques into an iterative machine learning process,we develop a prediction model that can be intuitively understood by traffic experts and is amenable to diagnostics during implementation.Our iterative machine learning process combines the embedded and filter approaches for feature selection with the use of expert knowledge to create aggregative input variables.The embedded approach is represented by application of a decision tree algorithm,while the filter approach is reflected in use of the mean decrease in accuracy output of a random forest algorithm for identifying expressive variables.We tested the methodology by applying it to field data from a sub-network in Tel Aviv.We demonstrated a reduction in the number of decision tree input variables from 66 raw variables to the five most effective aggregative ones,while achieving statistically significant improvement in all performance indicators.The identification rate of stable congestion increased from 65%to 74%while the robustness of the results was enhanced:the standard deviations of the identification and false alarm rates fell from 8%to 3%,respectively,to 5%and 2%.
文摘Objective： To analyze the experience of chief physician Xiong Lu in treating metaphase and advanced lung cancer through using TCM inheritance support system （V2.5）. Methods： Collecting the prescriptions used for metaphase and advanced lung cancer from November 1, 2014 to February 1, 2015, then the data were entered into the TCM inheritance support system. Based on principle analysis, revised mutual information, complex system entropy cluster and unsupervised hierarchical clustering composing principles were analyzed. Results： Based on the analysis of 228 cases of prescriptions, the frequency of each Chinese medicinal herb and association rules among herbs included in the database were computed. 15 core combinations and 2 new prescriptions were explored from the database. Conclusion： In treating metaphase and advanced lung cancer, chief physician Xiong Lu pay attention to Fuzheng Peiben （Therapy for support Zheng-qi to propup root）, according to the different situation cooperate with Tong Luo （dredging collaterals）, San Jie （Dissipating a mass）, Huo Xue （Activating blood）, Gong Du （Counteracting toxic substance） and so on. Xiong Lu is also good at using toxic drugs and incompatible medicaments.
