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A quantitative structure activity relationship model for predicting minimum ignition energy of organic substance

机译:预测有机物质最小点火能量的定量结构活性关系模型

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摘要

Due to the high experimental cost and the danger in conducting tests, there is a lack of information on the minimum ignition energy (MIE) of organic substances in the literature. On the other hand, MIE is essential information for the proper selection of explosion-proof equipment. Therefore, for application purposes, the MIE prediction model is needed. In this study, based on goodness-of-fit, robustness, predictive capability, and applicability domain (AD), ten quantitative structure-activity relationship (QSAR) models of MIE with different numbers of molecular descriptors were evaluated. A nine-descriptor model was found to have the best performance. The goodness-of-fit performance (R-2), robustness (Q(Loo)(2)), and predictive capability (Q(2)) of the proposed model are 0.926, 0.601, and 0.794, respectively. The average absolute error (AAE) of training data and test data is 0.080 mJ and 0.225 mJ, respectively. Compared with the existing QSAR models in the literature, this model has better performance. In addition, the AD of the proposed model is clearly discussed, which is the required element for considering the QSAR model for regulatory application purposes.
机译:由于高实验成本和导电测试中的危险,缺乏关于文献中有机物质的最小点火能(MIE)的信息。 On the other hand, MIE is essential information for the proper selection of explosion-proof equipment.因此,为了施用目的,需要MIE预测模型。在本研究中,基于适合性,鲁棒性,预测能力和适用性域(AD),评估了具有不同数量的分子描述符的MIE的10个定量结构 - 活性关系(QSAR)模型。发现九个描述符模型具有最佳性能。所提出的模型的适合性能(R-2),鲁棒性(Q(LOO)(2))和预测能力分别为0.926,0.601和0.794。培训数据和测试数据的平均绝对误差(AAE)分别为0.080 MJ和0.225 MJ。与文献中现有的QSAR模型相比,该模型具有更好的性能。此外,清楚地讨论了所提出的模型的广告,这是考虑用于监管申请目的的QSAR模型的所需元件。

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