A reverse engineering algorithm for mining a causal system model from system data

Ye, Nong

doi:10.1080/00207543.2016.1213913

Cited by 11 publications

(4 citation statements)

References 37 publications

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“…The PVAD algorithm was developed as a new system modeling technique [49][50][51] to overcome the above shortcomings. Variable value associations can be used to construct associative networks as multi-layer structural system models.…”

Section: Shortcomings Of Existing Techniques Of System Modeling From mentioning

confidence: 99%

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Modeling an Energy Consumption System with Partial-Value Data Associations

Ye¹,

Fok

Chong³

2018

Adv. sci. technol. eng. syst. j.

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Many existing system modeling techniques based on statistical modeling, data mining and machine learning have a shortcoming of building variable relations for the full ranges of variable values using one model, although certain variable relations may hold for only some but not all variable values. This shortcoming is overcome by the Partial-Value Association Discovery (PVAD) algorithm that is a new multivariate analysis algorithm to learn both full-value and partial-value relations of system variables from system data. Our research used the PVAD algorithm to model variable relations of energy consumption from data by learning full-and partial-value variable relations of energy consumption. The PVAD algorithm was applied to data of energy consumption obtained from a building at Arizona State University (ASU). Full-and partial-value variable associations of building energy consumption from the PVAD algorithm are compared with variable relations from a decision tree algorithm applied to the same data to show advantages of the PVAD algorithm in modeling the energy consumption system.

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Section: Shortcomings Of Existing Techniques Of System Modeling From mentioning

confidence: 99%

“…The PVAD algorithm is presented in detail in [49][50][51]. This section shows the PVAD application to data of energy consumption collected from an ASU building in January 2013 for modeling energy consumption.…”

Section: The Energy Consumption Data and The Pvad Applicationmentioning

confidence: 99%

Modeling an Energy Consumption System with Partial-Value Data Associations

Ye¹,

Fok

Chong³

2018

Adv. sci. technol. eng. syst. j.

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“…In recent years, our country has vigorously promoted educational reform and educational technology application [1,2]. e application of new technologies such as computer technology, information technology, and network technology has given a more positive development to the prospects of higher education [3,4]. rough the survey, it is found that the application of most of the network platforms of colleges and universities is relatively single, and most of the network platforms have become educational affairs' platforms or network library platforms of major universities, and the teaching tasks are not completed as expected [5].…”

Section: Introductionmentioning

confidence: 99%

Cloud Classroom Design for English Education Based on Internet of Things and Data Mining

Luo

2021

Mobile Information Systems

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The Informa ionization of social life and the globalization of economy have made the importance of English increasingly prominent. Building an information-based teaching platform for supplementary teaching under the network environment has become a mainstream teaching method in various basic schools. How to integrate various types of multimedia teaching resources into English classroom teaching has become the main goal of the current college teaching reform. Aiming at the shortcomings of the current English education classroom, this paper designs and develops an English education cloud classroom based on the Internet of Things and data mining methods. First of all, the system adopts a three-tier B/S model, the development platform chooses, NET, the development language, uses ASP.NET, and the database chooses SQL server. Secondly, the data mining method is used to clean and organize the data in the cloud classroom background to explore the course education status behind the data. Finally, the simulation test analysis verifies the efficiency of the English education cloud classroom established in this article.

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“…The PVAD (Partial-Value Association Discovery) algorithm [38] - [41] was chosen to perform the multivariate analysis of data in this study because each data set has both categorical data variables and numeric data variables and the PVAD algorithm was developed recently to handle both categorical data and numeric data together and uncover multivariate data associations from data. The PVAD algorithm was used to obtain data associations.…”

Section: Data Analyses To Identify Common Characteristics Of Engineering Retentionmentioning

confidence: 99%

Common and Uncommon Characteristics of Engineering Student Retention After the First Year in University

Fok

Collofello

et al.

2021 ASEE Virtual Annual Conference Content Access Proceedings

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A reverse engineering algorithm for mining a causal system model from system data

Cited by 11 publications

References 37 publications

Modeling an Energy Consumption System with Partial-Value Data Associations

Modeling an Energy Consumption System with Partial-Value Data Associations

Cloud Classroom Design for English Education Based on Internet of Things and Data Mining

Common and Uncommon Characteristics of Engineering Student Retention After the First Year in University

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