Qsar model for predicting neuraminidase inhibitors of influenza a viruses (H1N1) based on adaptive grasshopper optimization algorithm
High-dimensionality is one of the major problems which affect the quality of the quantitative structure–activity relationship (QSAR) modelling. Obtaining a reliable QSAR model with few descriptors is an essential procedure in chemometrics. The binary grasshopper optimization algorithm (BGOA) is a ne...
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| Main Authors: | , , , |
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| Format: | Article |
| Published: |
Taylor and Francis Ltd.
2020
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| Subjects: | |
| Online Access: | http://eprints.utm.my/id/eprint/90315/ http://dx.doi.org/10.1080/1062936X.2020.1818616 |
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| Institution: | Universiti Teknologi Malaysia |