An agent-based simulation approach to congestion management for the Colombian electricity market

Zambrano, Cristian; Morales, Yris Olaya

doi:10.1007/s10479-016-2222-4

Cited by 5 publications

(1 citation statement)

References 38 publications

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“…Group virtual or physical datasets, with the purpose of compiling datasets from similar data objects. ese data object groups created by the cluster analysis process are called clusters [18], which are a set of data objects.…”

Section: Cluster Analysis Technologymentioning

confidence: 99%

Application of Data Mining Technology in Public Welfare Sports Education in the Era of Artificial Intelligence

Dong

Huang

Lin³

2021

Mobile Information Systems

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Data mining refers to extracting the implicit prediction information from a massive dataset. It has very application prospects. Some data mining tools can develop things. The purpose of this article mainly discusses the public welfare sports education in the artificial intelligence era. The article discusses the research background and significance, development of education data mining, and decision tree technology and enumerates the application of education data mining in real life. The concept of educational data mining is given, and several common typical decision tree algorithms and their connections and differences are described; then, the concepts of multivalue decision tables and decision trees are discussed in detail. This article aims to build a nonprofit physical education system to manage and analyze the attendance data of students’ physical health assessment, so as to improve the enthusiasm of students to exercise, such as BP neural network, decision tree classification algorithm, and cluster analysis, discusses the calculation and analysis process of the relevant body side data of the sports teaching platform, and emphatically discusses and analyzes the application effect of data mining technology in public welfare sports teaching. In addition, this article has built a public welfare physical education system, allowing us to clearly understand various factors that affect students’ exercise and the relationship between various project indicators. Based on these data, educators can adjust technical means. Experimental results can efficiently and conveniently understand the pass rate of students in various sports. The pass rates of students in the six tests, grip strength, and sitting forward bending were 58%, 65%, 78%, 78%, 85%, and 65%, respectively. Using mathematical methods and computer technology, we can dig out valuable education management information from massive education data, so as to provide a reference for improving school enrollment.

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Section: Cluster Analysis Technologymentioning

confidence: 99%

Application of Data Mining Technology in Public Welfare Sports Education in the Era of Artificial Intelligence

Dong

Huang

Lin³

2021

Mobile Information Systems

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Optimal storage and transmission investments in a bilevel electricity market model

Weibelzahl

Märtz

2018

Ann Oper Res

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Exploring the financial risk of a temperature index: a fractional integrated approach

2018

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This paper introduces a new temperature index, which can suitably represent the underlying of a weather derivative. Such an index is defined as the weighted mean of daily average temperatures measured in different locations. It may be used to hedge volumetric risk, that is the effect of unexpected fluctuations in the demand/supply for some specific commodities-of agricultural or energy type, for exampledue to unfavorable temperature conditions. We aim at exploring the long term memory property of the volatility of such an index, in order to assess whether there exist some long-run paths and regularities in its riskiness. The theoretical part of the paper proceeds in a stepwise form: first, the daily average temperatures are modeled through autoregressive dynamics with seasonality in mean and volatility; second, the assessment of the distributional hypotheses on the parameters of the model is carried out for analyzing the long term memory property of the volatility of the index. The theoretical results suggest that the single terms of the index drive the long memory of the overall aggregation; moreover, interestingly, the proper selection of the parameters of the model might lead both to cases of persistence and antipersistence. The applied part of the paper provides some insights on the behaviour of the volatility of the proposed index, which is built starting from single daily average temperature time series.

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An agent-based simulation approach to congestion management for the Colombian electricity market

Cited by 5 publications

References 38 publications

Application of Data Mining Technology in Public Welfare Sports Education in the Era of Artificial Intelligence

Application of Data Mining Technology in Public Welfare Sports Education in the Era of Artificial Intelligence

Optimal storage and transmission investments in a bilevel electricity market model

Exploring the financial risk of a temperature index: a fractional integrated approach

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