Michael M. Li

17 papers B 2C 2Misc 2Journal 9Unranked 2
YearRankTypeTitle / Venue / Authors
2024 J jnl
A Novel CNN Model for Classification of Chinese Historical Calligraphy Styles in Regular Script Font.
Sensors
Qing Huang, Michael M. Li, Dan Agustin, Lily D. Li, Meena Jha
2024 J jnl
Incorporating Socio-Economic Factors in Maximizing Two-Dimensional Demand Coverage and Minimizing Distance to Uncovered Demand: A Dual-Objective MCLP Approach for Fire Station Location Selection.
Axioms
Albertus Untadi, Lily D. Li, Michael M. Li, Roland Dodd
2023 J jnl
Modeling Socioeconomic Determinants of Building Fires through Backward Elimination by Robust Final Prediction Error Criterion.
Axioms
Albertus Untadi, Lily D. Li, Michael M. Li, Roland Dodd
2021 C conf
Developing an Online Examination Timetabling System Using Artificial Bee Colony Algorithm in Higher Education.
BROADNETS
Kaixiang Zhu, Lily D. Li, Michael M. Li
2021 J jnl
Quantitative Spectral Data Analysis Using Extreme Learning Machines Algorithm Incorporated with PCA.
Algorithms
Michael M. Li, Santoso Wibowo, Wei Li, Lily D. Li
2020 J jnl
A Novel Method of Curve Fitting Based on Optimized Extreme Learning Machine.
Appl. Artif. Intell.
Michael M. Li, Lily D. Li
2016 J jnl
Nonlinear curve fitting to stopping power data using RBF neural networks.
Expert Syst. Appl.
Michael M. Li, Brijesh K. Verma
2016 C conf
The Development of a Nonlinear Curve Fitter Using RBF Neural Networks with Hybrid Neurons.
ISNN
Michael M. Li
2015 Misc conf
A neural network based method to determine initial object positions for segmentation.
ICNC
Paul Moore, Brijesh K. Verma, Michael M. Li
2015 — conf
An Improved RBF Neural Network Approach to Nonlinear Curve Fitting.
IWANN (2)
Michael M. Li, Brijesh K. Verma
2013 B conf
Impact of variability in data on accuracy and diversity of neural network based ensemble classifiers.
IJCNN
Chien-Yuan Chiu, Brijesh K. Verma, Michael M. Li
2012 B conf
A neural networks-based fitting to high energy stopping power data for heavy ions in solid matter.
IJCNN
Michael M. Li, William W. Guo, Brijesh K. Verma, Hong Lee
2009 J jnl
Intelligent methods for solving inverse problems of backscattering spectra with noise: a comparison between neural networks and simulated annealing.
Neural Comput. Appl.
Michael M. Li, William W. Guo, Brijesh K. Verma, Kevin Tickle, John O'Connor
2009 J jnl
Mutual complement between statistical and neural network approaches for rock magnetism data analysis.
Expert Syst. Appl.
William W. Guo, Michael M. Li, Gregory K. Whymark, Zheng-Xiang Li
2008 J jnl
RBF neural networks for solving the inverse problem of backscattering spectra.
Neural Comput. Appl.
Michael M. Li, Brijesh K. Verma, Xiaolong Fan, Kevin Tickle
2006 — conf
Principal Component Analysis and Neural Networks for Analysis of Complex Spectral Data from Ion Backscattering.
Artificial Intelligence and Applications
Michael M. Li, Xiaolong Fan, Kevin Tickle
2005 Misc conf
Artificial neural network techniques for analysis of ion backscattering spectra.
IC-AI
Michael M. Li, Xiaolong Fan, Brijesh K. Verma, Ron Balsys, John O'Connor