Hiromasa Kaneko

22 papers B 1Journal 18Unranked 3
YearRankTypeTitle / Venue / Authors
2026 J jnl
Adsorption Energy Prediction Model for CO
J. Chem. Inf. Model.
Issa Onishi, Hiromasa Kaneko
2023 J jnl
Catalyst Design and Feature Engineering to Improve Selectivity and Reactivity in Two Simultaneous Cross-Coupling Reactions.
J. Chem. Inf. Model.
Kohei Motojima, Abhijit Sen, Yoichi M. A. Yamada, Hiromasa Kaneko
2023 J jnl
De Novo Direct Inverse QSPR/QSAR: Chemical Variational Autoencoder and Gaussian Mixture Regression Models.
J. Chem. Inf. Model.
Kohei Nemoto, Hiromasa Kaneko
2023 J jnl
Direct prediction of the batch time and process variable profiles using batch process data based on different batch times.
Comput. Chem. Eng.
Hiromasa Kaneko
2021 J jnl
Correlation between the Metal and Organic Components, Structure Property, and Gas-Adsorption Capacity of Metal-Organic Frameworks.
J. Chem. Inf. Model.
Shunsuke Yuyama, Hiromasa Kaneko
2018 J jnl
Discussion on Regression Methods Based on Ensemble Learning and Applicability Domains of Linear Submodels.
J. Chem. Inf. Model.
Hiromasa Kaneko
2018 J jnl
Formulation of the excess absorption in infrared spectra by numerical decomposition for effective process monitoring.
Comput. Chem. Eng.
Shojiro Shibayama, Hiromasa Kaneko, Kimito Funatsu
2018 J jnl
Sparse Generative Topographic Mapping for Both Data Visualization and Clustering.
J. Chem. Inf. Model.
Hiromasa Kaneko
2017 J jnl
On Generative Topographic Mapping and Graph Theory combined approach for unsupervised non-linear data visualization and fault identification.
Comput. Chem. Eng.
Matheus S. Escobar, Hiromasa Kaneko, Kimito Funatsu
2016 J jnl
Chemical-Space-Based de Novo Design Method To Generate Drug-Like Molecules.
J. Chem. Inf. Model.
Shunichi Takeda, Hiromasa Kaneko, Kimito Funatsu
2016 J jnl
Inverse QSPR/QSAR Analysis for Chemical Structure Generation (from
J. Chem. Inf. Model.
Tomoyuki Miyao, Hiromasa Kaneko, Kimito Funatsu
2016 J jnl
Ring system-based chemical graph generation for de novo molecular design.
J. Comput. Aided Mol. Des.
Tomoyuki Miyao, Hiromasa Kaneko, Kimito Funatsu
2014 J jnl
Applicability Domain Based on Ensemble Learning in Classification and Regression Analyses.
J. Chem. Inf. Model.
Hiromasa Kaneko, Kimito Funatsu
2014 — conf
Automatic Database Monitoring for Process Control Systems.
IEA/AIE (1)
Hiromasa Kaneko, Kimito Funatsu
2013 B conf
Adaptive Soft Sensor Model Using Online Support Vector Regression with the Time Variable and Discussion on Appropriate Parameter Settings.
KES
Hiromasa Kaneko, Kimito Funatsu
2013 J jnl
Adaptive soft sensor model using online support vector regression with time variable and discussion of appropriate hyperparameter settings and window size.
Comput. Chem. Eng.
Hiromasa Kaneko, Kimito Funatsu
2013 J jnl
Criterion for Evaluating the Predictive Ability of Nonlinear Regression Models without Cross-Validation.
J. Chem. Inf. Model.
Hiromasa Kaneko, Kimito Funatsu
2013 J jnl
Erratum for "Development of a New Regression Analysis Method Using Independent Component Analysis".
J. Chem. Inf. Model.
Hiromasa Kaneko, Masamoto Arakawa, Kimito Funatsu
2011 — conf
Improvement and Estimation of Prediction Accuracy of Soft Sensor Models Based on Time Difference.
IEA/AIE (1)
Hiromasa Kaneko, Kimito Funatsu
2011 J jnl
Novel soft sensor method for detecting completion of transition in industrial polymer processes.
Comput. Chem. Eng.
Hiromasa Kaneko, Masamoto Arakawa, Kimito Funatsu
2009 — conf
A novel soft sensor method detecting completion of transition for industrial polymer processes.
ICONS
Hiromasa Kaneko, Masamoto Arakawa, Kimito Funatsu
2008 J jnl
Development of a New Regression Analysis Method Using Independent Component Analysis.
J. Chem. Inf. Model.
Hiromasa Kaneko, Masamoto Arakawa, Kimito Funatsu