私密直播全婐app免费大渔直播,国产av成人无码免费视频,男女同房做爰全过程高潮,国产精品自产拍在线观看

相關鏈接
聯系方式
  • 通信地址:武漢市江夏區陽光大道1號武漢紡織大學材料學院
  • 郵編:430200
  • 電話:027-59367580
  • 傳真:
  • Email:11497161@qq.com
當前位置:> 首頁 > 論文著作 > 正文
Prediction of glass transition temperatures for polystyrenes from cyclic dimer structures using artificial neural networks
作者:Jie Xu*, Ligen Zhu, Dong Fang, Li Liu, Weilin Xu, Zengchang Li
關鍵字:QSPR
論文來源:期刊
發表時間:2012年
The quantitative structure-property relationship (QSPR) was studied for the prediction of glass transition temperatures of polystyrenes on a set of 107 polystyrenes using artificial neural networks combined with genetic function approximation. Descriptors of the polymers were derived from their corresponding cyclic dimer structures. A nonlinear model with four descriptors was developed with squared correlation coefficient (R2) of 0.955 and standard error of estimation (s) of 11.2 K for the training set of 96 polystyrenes. The model obtained was further validated with Leave-One-Out cross-validation and the external test set. The cross-validated correlation coefficient R2CV = 0.953 illustrates that there seems no chance correlation to happen. The mean relative error (MRE) for the whole data set was 2.3%, indicating the reliability of the present model to estimate the glass transition temperatures for polystyrenes. The results demonstrate
the powerful ability of the cyclic dimer structures
as representative of
polymers, which could be further applied in QSPR studies on polymers.
主站蜘蛛池模板: 罗城| 闻喜县| 宁津县| 鞍山市| 昌乐县| 定边县| 寿阳县| 库伦旗| 富裕县| 龙江县| 阿克| 伽师县| 都兰县| 库尔勒市| 藁城市| 乐东| 梅州市| 镇平县| 三明市| 双鸭山市| 丰镇市| 工布江达县| 上林县| 武汉市| 南平市| 兰西县| 高雄市| 丹寨县| 无棣县| 孙吴县| 乌拉特中旗| 石泉县| 汪清县| 正宁县| 渝中区| 石首市| 皮山县| 常宁市| 平乡县| 天门市| 新营市|