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Prediction of Properties of Low and High Molecular Weight Compounds - Bertinetto Carlo Giuseppe
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Bertinetto Carlo Giuseppe:
Prediction of Properties of Low and High Molecular Weight Compounds - neues Buch

2012, ISBN: 9783659271090

ID: 9200000020141103

This work describes and discusses an innovative approach for the prediction of physical, chemical and biological properties of compounds, ranging from small molecules to large polymers. It is based on the direct and adaptive treatment of molecular structure by means of a Recursive Neural Network (RNN) to derive Quantitative Structure-Property/Activity Relationships (QSPR/QSARs). Chemical compounds are represented through appropriate graphical tools that bypass the need for numerical descriptors...., This work describes and discusses an innovative approach for the prediction of physical, chemical and biological properties of compounds, ranging from small molecules to large polymers. It is based on the direct and adaptive treatment of molecular structure by means of a Recursive Neural Network (RNN) to derive Quantitative Structure-Property/Activity Relationships (QSPR/QSARs). Chemical compounds are represented through appropriate graphical tools that bypass the need for numerical descriptors. The capabilities of this methodology are investigated by applying it to different predictive problems: the melting point of ionic liquids, the glass transition temperature of polymers and the toxicity of organic molecules. The results show that the graphical molecular representation was able to effectively model each case, providing accurate predictions using practically no background knowledge. The proposed structure-based RNN approach, it is argued, can provide a simple and general prediction method with great potential in molecular design, toxicology and evaluation of other complex properties.Taal: Engels; Afmetingen: 11x229x152 mm; Gewicht: 290,00 gram; Verschijningsdatum: november 2012; ISBN10: 3659271098; ISBN13: 9783659271090; , Engelstalig | Paperback | 2012, Exacte wetenschappen, Scheikunde, Lap Lambert Academic Publishing

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Prediction of Properties of Low and High Molecular Weight Compounds - Carlo Giuseppe Bertinetto
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Carlo Giuseppe Bertinetto:
Prediction of Properties of Low and High Molecular Weight Compounds - Taschenbuch

ISBN: 3659271098

ID: 13860555347

[EAN: 9783659271090], Neubuch, [PU: LAP Lambert Academic Publishing], CARLO GIUSEPPE BERTINETTO,PHYSICAL CHEMISTRY, Paperback. 192 pages. Dimensions: 8.7in. x 5.9in. x 0.4in.This work describes and discusses an innovative approach for the prediction of physical, chemical and biological properties of compounds, ranging from small molecules to large polymers. It is based on the direct and adaptive treatment of molecular structure by means of a Recursive Neural Network (RNN) to derive Quantitative Structure-PropertyActivity Relationships (QSPRQSARs). Chemical compounds are represented through appropriate graphical tools that bypass the need for numerical descriptors. The capabilities of this methodology are investigated by applying it to different predictive problems: the melting point of ionic liquids, the glass transition temperature of polymers and the toxicity of organic molecules. The results show that the graphical molecular representation was able to effectively model each case, providing accurate predictions using practically no background knowledge. The proposed structure-based RNN approach, it is argued, can provide a simple and general prediction method with great potential in molecular design, toxicology and evaluation of other complex properties. This item ships from multiple locations. Your book may arrive from Roseburg,OR, La Vergne,TN.

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Prediction of Properties of Low and High Molecular Weight Compounds - Carlo Giuseppe Bertinetto
Vergriffenes Buch, derzeit bei uns nicht verfügbar.
(*)
Carlo Giuseppe Bertinetto:
Prediction of Properties of Low and High Molecular Weight Compounds - neues Buch

2012, ISBN: 9783659271090

ID: 322618202

This work describes and discusses an innovative approach for the prediction of physical, chemical and biological properties of compounds, ranging from small molecules to large polymers. It is based on the direct and adaptive treatment of molecular structure by means of a Recursive Neural Network (RNN) to derive Quantitative Structure-Property/Activity Relationships (QSPR/QSARs). Chemical compounds are represented through appropriate graphical tools that bypass the need for numerical descriptors. The capabilities of this methodology are investigated by applying it to different predictive problems: the melting point of ionic liquids, the glass transition temperature of polymers and the toxicity of organic molecules. The results show that the graphical molecular representation was able to effectively model each case, providing accurate predictions using practically no background knowledge. The proposed structure-based RNN approach, it is argued, can provide a simple and general prediction method with great potential in molecular design, toxicology and evaluation of other complex properties. A Structure-Based QSAR/QSPR Approach Using Recursive Neural Networks Bücher > Fremdsprachige Bücher > Englische Bücher Taschenbuch 30.11.2012 Buch (fremdspr.), LAP Lambert Academic Publishing, .201

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Prediction of Properties of Low and High Molecular Weight Compounds (Paperback) - Bertinetto Carlo Giuseppe
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Bertinetto Carlo Giuseppe:
Prediction of Properties of Low and High Molecular Weight Compounds (Paperback) - Taschenbuch

2012, ISBN: 3659271098

ID: 14610976403

[EAN: 9783659271090], Neubuch, [PU: LAP Lambert Academic Publishing, United States], Language: English . Brand New Book ***** Print on Demand *****.This work describes and discusses an innovative approach for the prediction of physical, chemical and biological properties of compounds, ranging from small molecules to large polymers. It is based on the direct and adaptive treatment of molecular structure by means of a Recursive Neural Network (RNN) to derive Quantitative Structure-Property/Activity Relationships (QSPR/QSARs). Chemical compounds are represented through appropriate graphical tools that bypass the need for numerical descriptors. The capabilities of this methodology are investigated by applying it to different predictive problems: the melting point of ionic liquids, the glass transition temperature of polymers and the toxicity of organic molecules. The results show that the graphical molecular representation was able to effectively model each case, providing accurate predictions using practically no background knowledge. The proposed structure-based RNN approach, it is argued, can provide a simple and general prediction method with great potential in molecular design, toxicology and evaluation of other complex properties.

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Prediction of Properties of Low and High Molecular Weight Compounds - Carlo Giuseppe Bertinetto
Vergriffenes Buch, derzeit bei uns nicht verfügbar.
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Carlo Giuseppe Bertinetto:
Prediction of Properties of Low and High Molecular Weight Compounds - neues Buch

ISBN: 9783659271090

ID: 06b34d2bd9996ea020c7ba98eb10f9d3

This work describes and discusses an innovative approach for the prediction of physical, chemical and biological properties of compounds, ranging from small molecules to large polymers. It is based on the direct and adaptive treatment of molecular structure by means of a Recursive Neural Network (RNN) to derive Quantitative Structure-Property/Activity Relationships (QSPR/QSARs). Chemical compounds are represented through appropriate graphical tools that bypass the need for numerical descriptors. The capabilities of this methodology are investigated by applying it to different predictive problems: the melting point of ionic liquids, the glass transition temperature of polymers and the toxicity of organic molecules. The results show that the graphical molecular representation was able to effectively model each case, providing accurate predictions using practically no background knowledge. The proposed structure-based RNN approach, it is argued, can provide a simple and general prediction method with great potential in molecular design, toxicology and evaluation of other complex properties. Bücher / Naturwissenschaften, Medizin, Informatik & Technik / Chemie / Physikalische Chemie

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