An Assessment of the Impact of Rheological Properties on Rate of Penetration Using Data Mining Techniques

2019 ◽  
Author(s):  
Abo Taleb T. Al-Hameedi ◽  
Husam H. Alkinani ◽  
Shari Dunn-Norman ◽  
Ralph E. Flori ◽  
Mortadha T. Alsaba ◽  
...  
Keyword(s):  
Data Mining ◽  
Rheological Properties ◽  
Rate Of Penetration ◽  
Data Mining Techniques ◽  
Using Data ◽  
The Impact

An Assessment of the Impact of Rheological Properties on Rate of Penetration Using Data Mining Techniques

2019 ◽  
Author(s):  
Abo Taleb T. Al-Hameedi ◽  
Husam H. Alkinani ◽  
Shari Dunn-Norman ◽  
Ralph E. Flori ◽  
Mortadha T. Alsaba ◽  
...  
Keyword(s):  
Data Mining ◽  
Rheological Properties ◽  
Rate Of Penetration ◽  
Data Mining Techniques ◽  
Using Data ◽  
The Impact

scholarly journals Investigation on the Impact of Leadership Styles Using Data Mining Techniques

Leadership ◽  
2018 ◽  
Author(s):  
Waseem Ahmad ◽  
Muhammad Akhtaruzamman ◽  
Uswa Zahra ◽  
Chandan Ohri ◽  
Binu Ramakrishnan
Keyword(s):  
Data Mining ◽  
Leadership Styles ◽  
Data Mining Techniques ◽  
Using Data ◽  
The Impact

scholarly journals An Analysis of Students’ Academic Record Using Data Mining Techniques and Identification of Key Factors to Aid Students’ Performance

2018 ◽  
Vol 5 (1) ◽  
pp. 45-50
Author(s):  
Md Ashaduzzaman ◽  
Shihabuzzaman ◽  
Md Hasanur Rahman Sagor ◽  
Md Mizanur Rahman ◽  
Ahmed Iqbal Pritom
Keyword(s):  
Data Mining ◽  
Educational Institutions ◽  
Classification Algorithms ◽  
Key Factors ◽  
Science And Engineering ◽  
Data Mining Techniques ◽  
Using Data ◽  
The University ◽  
Academic Record ◽  
The Impact

With the improvement of information technology, presently educational institutions generally store and compile a huge volume of students’ data. This huge volume of data can be analyzed using different data mining techniques and extract hidden relation between students’ result with other academic attributes. The main objective of this paper is to evaluate the impact of different academic attributes on the students’ final result using data mining techniques. We used different data mining techniques to analyze students data collected from Green University of Bangladesh. We applied three well-known classification algorithms namely Decision Tree, Naïve Bayes, and SVM to develop a prediction model that can suggest probable grade by analyzing parameters like the midterm, attendance, assignment, presentation, class test, final, and CT marks. Our goal is to find out the key factors playing as a catalyst for getting good or bad CGPA. Through this research, the university authority will get the knowledge about key factors playing significant role in students’ result that will help them to take proper decisions to improve students’ grade that in turns will reduce students’ dropout. GUB JOURNAL OF SCIENCE AND ENGINEERING, Vol 5(1), Dec 2018 P 45-50

Analysis of Crop Yield Prediction of Kharif & Rabi Jowar Crops Using Data Mining Techniques

2017 ◽  
Vol 7 (11) ◽  
pp. 79
Author(s):  
Sujata Mulik
Keyword(s):  
Data Mining ◽  
Crop Yield ◽  
Crop Production ◽  
Climatic Factors ◽  
Crop Productivity ◽  
Yield Prediction ◽  
Data Mining Techniques ◽  
Agriculture Sector ◽  
Using Data ◽  
Rabi Crops

Agriculture sector in India is facing rigorous problem to maximize crop productivity. More than 60 percent of the crop still depends on climatic factors like rainfall, temperature, humidity. This paper discusses the use of various Data Mining applications in agriculture sector. Data Mining is used to solve various problems in agriculture sector. It can be used it to solve yield prediction.  The problem of yield prediction is a major problem that remains to be solved based on available data. Data mining techniques are the better choices for this purpose. Different Data Mining techniques are used and evaluated in agriculture for estimating the future year's crop production. In this paper we have focused on predicting crop yield productivity of kharif & Rabi Crops. 

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