scholarly journals Improving Ammonia Emission Modeling and Inventories by Data Mining and Intelligent Interpretation of the National Air Emission Monitoring Study Database

Atmosphere ◽  
2011 ◽  
Vol 2 (2) ◽  
pp. 110-128 ◽  
Author(s):  
Ji-Qin Ni ◽  
Erin L. Cortus ◽  
Albert J. Heber
2018 ◽  
Vol 52 (19) ◽  
pp. 11223-11231 ◽  
Author(s):  
Cheng Huang ◽  
Qingyao Hu ◽  
Shengrong Lou ◽  
Junjie Tian ◽  
Ruining Wang ◽  
...  

1997 ◽  
Vol 36 (5) ◽  
pp. 1675-1685 ◽  
Author(s):  
S. Joe Qin ◽  
Hongyu Yue ◽  
Ricardo Dunia

2007 ◽  
Author(s):  
Maira F.P Amaral ◽  
Richard S Gates ◽  
Douglas G Overhults ◽  
Ilda F.F Tinôco ◽  
Erin G Wilkerson ◽  
...  

2017 ◽  
Vol 2 (1) ◽  
pp. 29-36
Author(s):  
Bintang Dewi Fajar Kurniatullah ◽  
Yuventius Tyas Catur Pramudi

Utilization of students’ academic data to produce information used by management in monitoring students’ study period on Information System Department. Multiple linier regression method will produce multiple linier regression equation used for estimating students’ graduation equipped with prototype. According to analysis carried out by using nine variable SKS1, SKS2, SKS3, SKS4, IPS1, IPS2, IPS3, IPS4, and the number of repeated courses of 2008 to 2012 the multiple linier regression equation is Y = 13.49  +  0.099 X1  + (-0.068) X2 + 0.025 X3 + (-0.059) X4 + (-0.585) X5 + (-0.443) X6 + (-0.155) X7 + (-0.368) X8 + (-0.082) X9. From the equation there is an error of MSE and RMSE that is equal to 0.1168 and 0.3418. The prototype uses a PHP-based program using sublime text and XAMPP. The prototype monitoring the students’ study time in this research is very helpful if supported by management. Keywords: Data mining, multiple linear regression, estimation, monitoring, study time


2006 ◽  
Vol 2006 (5) ◽  
pp. 6685-6694
Author(s):  
David Moye ◽  
Victor Boero ◽  
Everett Gill

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