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A Fuzzy ARTMAP-Based Quantitative Structure−Property Relationship (QSPR) for the Henry's Law Constant of Organic Compounds
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What this work says
Outgoing claims: the papers this work cites, builds on, or argues with.
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BOND CONTRIBUTION METHOD FOR ESTIMATING HENRY'S LAW CONSTANTS
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A Shape Index from Molecular Graphs
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Molecular Connectivity in Chemistry and Drug Research
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The performance of UNIFAC and related group contribution models part II. Prediction of Henry's law constants
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A Fuzzy ARTMAP Based on Quantitative Structure−Property Relationships (QSPRs) for Predicting Aqueous Solubility of Organic Compounds
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Prediction of Henry's Law Constants by a Quantitative Structure Property Relationship and Neural Networks
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A QSPR Study of the Solubility of Gases and Vapors in Water
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QSAR model for predicting Henry's constant
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New Group-Interaction Parameters of the UNIFAC Model: Aromatic Methoxyl Binaries
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A Modified UNIFAC (Dortmund) Model. 3. Revision and Extension
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Structural effects on rates and equilibriums. XIX. Intrinsic hydrophilic character of organic compounds. Correlations in terms of structural contributions
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Ranking of strong acids via a new selectivity parameter. I
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Fuzzy ARTMAP: A neural network architecture for incremental supervised learning of analog multidimensional maps
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An improved learning algorithm for the fuzzy ARTMAP neural network
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The properties of gases and liquids
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