A quantitative structure−property relationship (QSPR) study was performed to develop a model for prediction of the lower flammability limit (LFL) of pure compounds. The obtained model is a four-parameter multilinear equation. These four parameters are calculated from the chemical structure of every molecule. The average absolute error, squared correlation coefficient, and root mean squares of error of the obtained model over all 1056 pure compounds used to develop the model are 7.68%, 0.9698, and 0.084, respectively
AbstractWhile flammable materials are operated in process industries, the electric equipments should...
Quantitative structure property relationships (QSPR) are increasingly used for the prediction of phy...
International audienceFor registration of a chemical, European Union REACH legislation requires info...
In this study, machine learning algorithms, such as support vector machine (SVM), k-nearest-neighbor...
Three efficient and accurate QSPR models for predicting upper flammability limits (UFLs) of hydrocar...
In the present work, a new molecular-based model is presented for estimation of the upper flammabili...
Fire and explosions are the dominant hazards in many industry sectors, especially oil and gas. The ...
The lower flammability limit (LFL) is one of the most important parameters for evaluating the fire a...
Quantitative Structure Property Relationships (QSPR) are predictive methods of macroscopic propertie...
Quantitative Structure-Property Relationship models (QSPR) are predictive methods based on correlati...
Handling and storing chemicals in the industrial world require a conscientious hazards assessment an...
Safety-related properties like lower flammable limit (LFL), upper flammable limit (UFL), auto-igniti...
[[abstract]]While flammable materials are operated in process industries, the electric equipments sh...
Due to the fast development and availability of computers, predictive approaches are increasingly us...
International audienceThe accuracy and predictability of predictive methods to determine the flammab...
AbstractWhile flammable materials are operated in process industries, the electric equipments should...
Quantitative structure property relationships (QSPR) are increasingly used for the prediction of phy...
International audienceFor registration of a chemical, European Union REACH legislation requires info...
In this study, machine learning algorithms, such as support vector machine (SVM), k-nearest-neighbor...
Three efficient and accurate QSPR models for predicting upper flammability limits (UFLs) of hydrocar...
In the present work, a new molecular-based model is presented for estimation of the upper flammabili...
Fire and explosions are the dominant hazards in many industry sectors, especially oil and gas. The ...
The lower flammability limit (LFL) is one of the most important parameters for evaluating the fire a...
Quantitative Structure Property Relationships (QSPR) are predictive methods of macroscopic propertie...
Quantitative Structure-Property Relationship models (QSPR) are predictive methods based on correlati...
Handling and storing chemicals in the industrial world require a conscientious hazards assessment an...
Safety-related properties like lower flammable limit (LFL), upper flammable limit (UFL), auto-igniti...
[[abstract]]While flammable materials are operated in process industries, the electric equipments sh...
Due to the fast development and availability of computers, predictive approaches are increasingly us...
International audienceThe accuracy and predictability of predictive methods to determine the flammab...
AbstractWhile flammable materials are operated in process industries, the electric equipments should...
Quantitative structure property relationships (QSPR) are increasingly used for the prediction of phy...
International audienceFor registration of a chemical, European Union REACH legislation requires info...