scholarly journals Determination and Classification of Crew Productivity with Data Mining Methods

Data Mining ◽  
2018 ◽  
Author(s):  
Abdullah Emre Keleş ◽  
Mümine Kaya Keleş
Keyword(s):  
Data Mining ◽  
Mining Methods

A data mining approach to the diagnosis of failure modes for two serial fastened sandwich composite plates

2016 ◽  
Vol 51 (20) ◽  
pp. 2853-2862 ◽  
Author(s):  
Serkan Ballı
Keyword(s):  
Data Mining ◽  
Random Forest ◽  
Failure Modes ◽  
Composite Plates ◽  
Study Data ◽  
Sandwich Composite ◽  
Support Vector ◽  
Geometrical Parameters ◽  
Mining Methods

The aim of this study is to diagnose and classify the failure modes for two serial fastened sandwich composite plates using data mining techniques. The composite material used in the study was manufactured using glass fiber reinforced layer and aluminum sheets. Obtained results of previous experimental study for sandwich composite plates, which were mechanically fastened with two serial pins or bolts were used for classification of failure modes. Furthermore, experimental data from previous study consists of different geometrical parameters for various applied preload moments as 0 (pinned), 2, 3, 4, and 5 Nm (bolted). In this study, data mining methods were applied by using these geometrical parameters and pinned/bolted joint configurations. Therefore, three geometrical parameters and 100 test data were used for classification by utilizing support vector machine, Naive Bayes, K-Nearest Neighbors, Logistic Regression, and Random Forest methods. According to experiments, Random Forest method achieved better results than others and it was appropriate for diagnosing and classification of the failure modes. Performances of all data mining methods used were discussed in terms of accuracy and error ratios.

Data mining methods for the classification of high-resolution electrocardiograms

2011 ◽  
Vol 44 (2) ◽  
pp. e39-e40
Author(s):  
Maik Götze ◽  
Christian Wolff ◽  
Bernd Krause ◽  
Dietrich Romberg
Keyword(s):  
Data Mining ◽  
High Resolution ◽  
Mining Methods

Classification of primary progressive aphasia: Do unsupervised data mining methods support a logopenic variant?

2015 ◽  
Vol 16 (3-4) ◽  
pp. 147-159 ◽  
Author(s):  
Carolina Maruta ◽  
Telma Pereira ◽  
Sara C. Madeira ◽  
Alexandre De Mendonça ◽  
Manuela Guerreiro
Keyword(s):  
Data Mining ◽  
Primary Progressive Aphasia ◽  
Progressive Aphasia ◽  
Primary Progressive ◽  
Mining Methods ◽  
Unsupervised Data Mining

scholarly journals CLASSIFICATION OF ENGINEERING STUDENTS' SELF-EFFICACY TOWARDS VISUAL-VERBAL PREFERENCES USING DATA MINING METHODS

2019 ◽  
Vol 77 (3) ◽  
pp. 349-363
Author(s):  
Citra Kurniawan ◽  
Punaji Setyosari ◽  
Waras Kamdi ◽  
Saida Ulfa
Keyword(s):  
Data Mining ◽  
Self Efficacy ◽  
Engineering Students ◽  
Classification Model ◽  
Linear Projection ◽  
Initial Learning ◽  
Mining Methods ◽  
Using Data ◽  
Method Approach

The purpose of this research was to build a classification model and to measure the correlation of self-efficacy with visual-verbal preferences using data mining methods. This research used the J48 classifier and linear projection method as an approach to see patterns of data distribution between self-efficacy and visual-verbal preferences. The measurement of the correlation of engineering students' self-efficacy with visual-verbal preferences using the data mining method approach gets the result that self-efficacy does not correlate with visual-verbal preferences. However, engineering students' self-efficacy influences the achievement of initial learning outcomes. Visual-verbal preference is more influenced by students' interest in images so it can be concluded that self-efficacy affects the initial results of learning but does not have a correlation with visual-verbal preferences. The results of the decision tree provide the results that are easily understood and present a correlation between self-efficacy and visual-verbal preferences in a visual form. Keywords: self-efficacy, visual-verbal preferences, data mining.

scholarly journals Inventory, Conservation Statement and Classification of Bird Trade in Cianjur based on Data Mining Methods

2019 ◽  
Vol 8 (2S7) ◽  
pp. 22-24
Keyword(s):  
Data Mining ◽  
Conservation Status ◽  
Bird Species ◽  
Dominance Status ◽  
Rule Based ◽  
Search Results ◽  
The Status ◽  
Mining Methods ◽  
Total Species

Currently in the community many who keep birds. To get the birds people are looking for in the bird market. Total species of birds traded (Kabupaten Cianjur) as many as 46 types of 23 tribes. From the search results were found by IUCN endangered bird species but by law in Indonesia excluding protected ones such as the species of ekelgeling (Cissathalassina) whose conservation status is highly endangered. The excavation of the rule based on available data using the c45 algorithm shows that the dominance status of bird species in the Cipanas area has a significant influence on the status of the dominance of bird species for the entire Cianjur region.

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