Haque, M. E. (2012, June), Effect of Class Absenteeism on Grade Performance: A Probabilistic Neural Net (PNN)-based GA-trained Model  Paper presented at 2012 ASEE Annual Conference & Exposition, San Antonio, Texas. 10.18260/1-2--21256

\bibitem{asee_peer_21256}
  Haque, M. E. (2012, June), \emph{Effect of Class Absenteeism on Grade Performance: A Probabilistic Neural Net (PNN)-based GA-trained Model}
  Paper presented at 2012 ASEE Annual Conference \& Exposition, San Antonio, Texas.
  10.18260/1-2--21256

Mohammed E. Haque P.E..  "Effect of Class Absenteeism on Grade Performance: A Probabilistic Neural Net (PNN)-based GA-trained Model".  2012 ASEE Annual Conference & Exposition, San Antonio, Texas, 2012, June.  ASEE Conferences, 2012.  https://peer.asee.org/21256 Internet.  16 Apr, 2024

\bibitem{asee_peer_21256}
  Mohammed E. Haque P.E..
  "Effect of Class Absenteeism on Grade Performance: A Probabilistic Neural Net (PNN)-based GA-trained Model".
  \emph{2012 ASEE Annual Conference \& Exposition, San Antonio, Texas, 2012, June}.
  ASEE Conferences, 2012.
  https://peer.asee.org/21256 Internet.  16 Apr, 2024

@INPROCEEDINGS{asee_peer_21256
author = "Mohammed E. Haque P.E."
title = "Effect of Class Absenteeism on Grade Performance: A Probabilistic Neural Net (PNN)-based GA-trained Model"
booktitle = "2012 ASEE Annual Conference \& Exposition"
year = "2012"
month = "June"
address = "San Antonio, Texas"
publisher = "ASEE Conferences"
note = {https://peer.asee.org/21256}
number = {10.18260/1-2--21256}
}

TY  - CPAPER
AB  - Effect of Class Absenteeism on Grade Performance: A ProbabilisticNeural Net (PNN) based GA trained model                                        AbstractMost faculty inherently believe that students who frequently miss class significantlyincrease their likelihood of poor grades by doing so. The purpose of this research was todevelop a Probabilistic Neural Net (PNN) based Genetic Algorithm to assess therelationship between absenteeism and student grade performance in a structural systemscourse taught by the author. The model was trained to classify the outcomes (pass/fail) of130 students using records of class attendance and end-of-course final grades. Therelative importance/weight of attendance on final grades was then determined. It wasfound that course attendance and grade performance were positively correlated. Themodel was then used to accurately predict the success rate of a new group of 80 studentsbased on provided attendance records. Overall, this research shows that the developedPNN based GA model can be used to predict the outcome of student performance in thestructural systems class based on anticipated class absence patterns.
AU  - Mohammed E. Haque P.E.
CY  - San Antonio, Texas
DA  - 2012/06/10
PB  - ASEE Conferences
TI  - Effect of Class Absenteeism on Grade Performance: A Probabilistic Neural Net (PNN)-based GA-trained Model
UR  - https://peer.asee.org/21256
DO  - 10.18260/1-2--21256
ER  -