Recognizing occupant presence status in residential buildings from environment sensing data by data mining approach

2021 ◽  
Vol 252 ◽  
pp. 111432
Author(s):  
Hao Zhou ◽  
Juan Yu ◽  
Yang Zhao ◽  
Chenchen Chang ◽  
Jiajun Li ◽  
...  
Keyword(s):  
Data Mining ◽  
Residential Buildings ◽  
Sensing Data ◽  
Data Mining Approach

Data Mining Approach for Feature Reduction Using Fuzzy Association Rule

2017 ◽  
Vol 5 (11) ◽  
pp. 44-49
Author(s):  
Siji P D ◽  
◽  
◽  
M.L.Valarmathi .
Keyword(s):  
Data Mining ◽  
Association Rule ◽  
Feature Reduction ◽  
Data Mining Approach ◽  
Fuzzy Association Rule

Klasifikasi pada Tempat Tinggal Menurut Provinsi dan Jenis Kepemilikan Berdasarkan Algoritma K-Means

2020 ◽  
Vol 4 (3) ◽  
pp. 247
Author(s):  
Dwi Swasono Rachmad
Keyword(s):  
Data Mining ◽  
Unsupervised Learning ◽  
Residential Buildings ◽  
Government Agency ◽  
Role Of Government ◽  
The Republic ◽  
Household Processing ◽  
Central Statistics

<p><em>H</em><em>ousing is derived from the word house</em><em> which means</em><em> a place that has a place to live which will stay or stop in a certain time. Housing is a residence that has been grouped into a place that has facilities and infrastructure. The problem in this study focuses on the type of residential ownership in the form of SHM ART, SHM Non ART, NON SHM and others. </em><em>T</em><em>hese four types</em><em> can be used</em><em> to know the percentage of ownership in all provinces in Indonesia. Due to the fact that there is still a lot of information about the type of certificate ownership, there is still not much ownership. Therefore, the use of the k-Means algorithm as a data mining concept in the form of clusters, where the data already has parameters or values that fall into the category of unsupervised learning. That data produced the best. The data was obtained from published sources of the Republic of Indonesia government agency, namely the Central Statistics Agency data with the category of household processing with self-owned residential buildings purchased from developers or non-developers by province and type of ownership in 2016 throughout Indonesia. In conducting the dataset, researchers used the RapidMiner application as a clustering process application. This research </em><em>shows that</em><em> there are more types of ownership in the SHM ART, but for other values it is still smaller than the value in other types of ownership which is the second largest value. So</em><em>,</em><em> in this case, the role of government in providing assistance in the process of ownership in order to become SHM ART</em><em> is very important</em><em>.</em></p>

A Data-Mining Approach for Energy Behavioural Analysis to Ease Predictive Modelling for the Smart City

2018 ◽  
Author(s):  
Lavinia Chiara Tagliabue ◽  
Stefano Rinaldi ◽  
Mario Favalli Ragusini ◽  
Giovanni Tardioli ◽  
Angelo Luigi Camillo Ciribini
Keyword(s):  
Data Mining ◽  
Smart City ◽  
Predictive Modelling ◽  
Data Mining Approach ◽  
Behavioural Analysis

Data mining approach to construction productivity prediction for cutter suction dredgers

2019 ◽  
Vol 105 ◽  
pp. 102833 ◽  
Author(s):  
Shuo Bai ◽  
Mingchao Li ◽  
Rui Kong ◽  
Shuai Han ◽  
Heng Li ◽  
...  
Keyword(s):  
Data Mining ◽  
Construction Productivity ◽  
Data Mining Approach ◽  
Productivity Prediction

Data mining approach for improving the optimal control of HVAC systems: An event-driven strategy

2021 ◽  
Vol 39 ◽  
pp. 102246
Author(s):  
Junqi Wang ◽  
Jin Hou ◽  
Jianping Chen ◽  
Qiming Fu ◽  
Gongsheng Huang
Keyword(s):  
Data Mining ◽  
Optimal Control ◽  
Hvac Systems ◽  
Data Mining Approach ◽  
Event Driven
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