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Support vector machine based training of multilayer feedforward neural networks as optimized by particle swarm algorithm: Application in QSAR studies of bioactivity of organic compounds.

, , , , , and . J. Comput. Chem., 28 (2): 519-527 (2007)

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Support vector machine based training of multilayer feedforward neural networks as optimized by particle swarm algorithm: Application in QSAR studies of bioactivity of organic compounds., , , , , and . J. Comput. Chem., 28 (2): 519-527 (2007)TSIS: A Supplementary Algorithm to t-SMILES for Fragment-based Molecular Representation., , , , and . CoRR, (2024)Fragment-based t-SMILES for de novo molecular generation., , , , , and . CoRR, (2023)New Variable Selection Method Using Interval Segmentation Purity with Application to Blockwise Kernel Transform Support Vector Machine Classification of High-Dimensional Microarray Data., , , , , , and . Journal of Chemical Information and Modeling, 49 (8): 2002-2009 (2009)Radial Basis Function Network-Based Transform for a Nonlinear Support Vector Machine as Optimized by a Particle Swarm Optimization Algorithm with Application to QSAR Studies., , , , , , and . J. Chem. Inf. Model., 47 (4): 1438-1445 (2007)Adaptive Configuring of Radial Basis Function Network by Hybrid Particle Swarm Algorithm for QSAR Studies of Organic Compounds., , , , , , and . J. Chem. Inf. Model., 46 (6): 2494-2501 (2006)Piecewise Hypersphere Modeling by Particle Swarm Optimization in QSAR Studies of Bioactivities of Chemical Compounds., , , , , and . Journal of Chemical Information and Modeling, 45 (3): 535-541 (2005)