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Search: "[ keyword: Prediction Model ]" (11)
An Experimental Study of Generality of Software Defects Prediction Models based on Object Oriented Metrics
Tae Yeon Kim , Yun Kyu Kim , Heung Seok Chae The KIPS Transactions:PartD,
Vol. 16, No. 3, pp. 407-416,
Jun.
2009
10.3745/KIPSTD.2009.16.3.407
10.3745/KIPSTD.2009.16.3.407
Cox Model Improvement Using Residual Blocks in Neural Networks: A Study on the Predictive Model of Cervical Cancer Mortality
Nang Kyeong Lee, Joo Young Kim, Ji Soo Tak, Hyeong Rok Lee, Hyun Ji Jeon, Jee Myung Yang, Seung Won Lee The Transactions of the Korea Information Processing Society,
Vol. 13, No. 6, pp. 260-268,
Jun.
2024
https://doi.org/10.3745/TKIPS.2024.13.6.260
Keywords: Cervical cancer, Survival Prediction Model, Cox Proportional Hazards, Machine Learning, Deep Neural Networks, ResNet
https://doi.org/10.3745/TKIPS.2024.13.6.260
Keywords: Cervical cancer, Survival Prediction Model, Cox Proportional Hazards, Machine Learning, Deep Neural Networks, ResNet
Data Communication Prediction Model in Multiprocessors based on Robust Estimation
Jang Hwan Jun , Kang Woo Lee The KIPS Transactions:PartA,
Vol. 12, No. 3, pp. 243-252,
Jun.
2005
10.3745/KIPSTA.2005.12.3.243
10.3745/KIPSTA.2005.12.3.243
Comparison of Machine Learning-Based Greenhouse VPD Prediction Models
Jang Kyeong Min, Lee Myeong Bae, Lim Jong Hyun, Oh Han Byeol, Shin Chang Sun, Park Jang Woo KIPS Transactions on Software and Data Engineering,
Vol. 12, No. 3, pp. 125-132,
Mar.
2023
https://doi.org/10.3745/KTSDE.2023.12.3.125
Keywords: Machine Learning, Vapor Pressure Deficit(VPD), Prediction Model, Smart Farm, Light Gradient Boosting Machine(LGBM), RandomForest
https://doi.org/10.3745/KTSDE.2023.12.3.125
Keywords: Machine Learning, Vapor Pressure Deficit(VPD), Prediction Model, Smart Farm, Light Gradient Boosting Machine(LGBM), RandomForest
Verifying Execution Prediction Model based on Learning Algorithm for Real-time Monitoring
Yoon Seok Jeong , Tae Wan Kim , Chun Hyon Chang The KIPS Transactions:PartA,
Vol. 11, No. 4, pp. 243-250,
Aug.
2004
10.3745/KIPSTA.2004.11.4.243
10.3745/KIPSTA.2004.11.4.243
Prediction Model of Hypertension Using Sociodemographic Characteristics Based on Machine Learning
Bum Ju Lee KIPS Transactions on Software and Data Engineering,
Vol. 10, No. 11, pp. 541-546,
Nov.
2021
https://doi.org/10.3745/KTSDE.2021.10.11.541
Keywords: machine leaning, Prediction Model, Hypertension, Sociodemographic Characteristics, Public Health
https://doi.org/10.3745/KTSDE.2021.10.11.541
Keywords: machine leaning, Prediction Model, Hypertension, Sociodemographic Characteristics, Public Health
A Software Quality Prediction Model Without Training Data Set
Hong Ui Seog The KIPS Transactions:PartD,
Vol. 10, No. 4, pp. 689-696,
Aug.
2003
10.3745/KIPSTD.2003.10.4.689
10.3745/KIPSTD.2003.10.4.689
A Modeling of Realtime Fuel Comsumption Prediction Using OBDII Data
Hee-Eun Yang, Do-Hyun Kim, Hoseop Choe KIPS Transactions on Software and Data Engineering,
Vol. 10, No. 2, pp. 57-64,
Feb.
2021
https://doi.org/10.3745/KTSDE.2021.10.2.57
Keywords: Fuel Consumption, Prediction Model, Stacking Ensemble, Regression Model, OBDII
https://doi.org/10.3745/KTSDE.2021.10.2.57
Keywords: Fuel Consumption, Prediction Model, Stacking Ensemble, Regression Model, OBDII
Prediction of Forest Fire Hazardous Area Using Predictive Spatial Data Mining
Jong Gyu Han , Yeon Kwang Yeon , Kwang Hoon Chi , Keun Ho Ryu The KIPS Transactions:PartD,
Vol. 9, No. 6, pp. 1119-1126,
Dec.
2002
10.3745/KIPSTD.2002.9.6.1119
10.3745/KIPSTD.2002.9.6.1119
Unsupervised Learning Model for Fault Prediction Using Representative Clustering Algorithms
Euy Seok Hong , Mi Kyeong Park KIPS Transactions on Software and Data Engineering,
Vol. 3, No. 2, pp. 57-64,
Feb.
2014
10.3745/KTSDE.2014.3.2.57
10.3745/KTSDE.2014.3.2.57