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Neural Network Based Quantitative Structural Property Relations (QSPRs) for Predicting Boiling Points of Aliphatic Hydrocarbons

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What this work says

Outgoing claims: the papers this work cites, builds on, or argues with.

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Correlation of activity coefficients of hydrocarbons in water at infinite dilution with molecular parameters
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Molecular Connectivity in Chemistry and Drug Research
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Neural network-molecular descriptors approach to the prediction of properties of alkenes
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New electrotopological descriptor for prediction of boiling points of alkanes and aliphatic alcohols through artificial neural network and multiple linear regression analysis
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Development and use of charged partial surface area structural descriptors in computer-assisted quantitative structure-property relationship studies
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Neural Network-Graph Theory Approach to the Prediction of the Physical Properties of Organic Compounds
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Prediction of boiling points and critical temperatures of industrially important organic compounds from molecular structure
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Correlation between Structure and Normal Boiling Points of Haloalkanes C1-C4 Using Neural Networks
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On molecular identification numbers
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Edge Adjacency Relationships and Molecular Topographic Descriptors. Definition and QSAR Applications
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A Comparative Study of Topological and Geometrical Parameters in Estimating Normal Boiling Point and Octanol/Water Partition Coefficient
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A QSPR Study of the Solubility of Gases and Vapors in Water
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Boiling Point and Critical Temperature of a Heterogeneous Data Set: QSAR with Atom Type Electrotopological State Indices Using Artificial Neural Networks
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Prediction of Chemical Biotransfer of Organic Chemicals from Cattle Diet into Beef and Milk Using the Molecular Connectivity Index
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Molecular Modeling by Linear Combinations of Connectivity Indexes
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Raman Spectra of Aqueous Solutions of Potassium Thiocyanate
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An Electrotopological-State Index for Atoms in Molecules
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The Properties of Gases and Liquids
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The simulation and interpretation of free turbulence with a cognitive neural system
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Fuzzy ARTMAP: A neural network architecture for incremental supervised learning of analog multidimensional maps
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The properties of gases and liquids

What points at this work

Incoming claims: where this work appears in other papers’ reference lists and arguments.

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Estimation of infinite dilution activity coefficients of organic compounds in water with neural classifiers
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An architecture of deep learning in QSPR modeling for the prediction of critical properties using molecular signatures
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ChemInform Abstract: Neural Network Based Quantitative Structural Property Relations (QSPRs) for Predicting Boiling Points of Aliphatic Hydrocarbons.
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An improved characteristic molecular volume parameter for linear solvation energy relationships of acyclic alkanes
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Combination of Fragmental and Topological Descriptors for QSPR Estimations of Boiling Temperature
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Artificial Neural Network‐Based Quantitative Structural Property Relationship for Predicting Boiling Points of Refrigerants
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