Prediction of Young's modulus of weathered igneous rocks using GRNN, RVM, and MPMR models with a new index
文献类型：期刊论文
| 作者 | Ceryan, Nurcihan |
| 刊名 | JOURNAL OF MOUNTAIN SCIENCE
 |
| 出版日期 | 2021 |
| 卷号 | 18期号:1页码:233-251 |
| 关键词 | n-durability index P-wave velocity MPMR RVM GRNN Weathered rocks |
| ISSN号 | 1672-6316 |
| DOI | 10.1007/s11629-020-6331-9 |
| 英文摘要 | Young's modulus (YM) of intact rock is an important parameter in the assessment of engineering behaviours of rock masses, and it cannot always be obtained in an economical and practical manner in laboratory experiments. The main purpose of this study is to examine the capability of the minimax probability machine regression (MPMR), relevance vector machine (RVM), and generalised regression neural network (GRNN) models for the prediction of YM. The other aim is to determine the usefulness of a new index, the n-durability index (n(drb)), which is based on porosity and the slake durability index. According to the regression analysis performed in this study, the n-durability index as an explanatory parameter performs better than the P-wave velocity (V-p), porosity, and slake durability index in the models, considering the results herein as well as the existing literature. According to regression error characteristic curves, Taylor diagrams, and performance indices, the best prediction model is MPMR, while the worst is the GRNN model. Although GRNN is the worst of the soft computing models, its performance is slightly better than that of the multiple linear regression (MLR) model. According to the results of the study, the MPMR and RVM models with n(drb) and V-p are successful tools that can predict the YM of igneous rock materials to different degrees. |
| 语种 | 英语 |
| WOS记录号 | WOS:000607413000016 |
| 源URL | [http://ir.imde.ac.cn/handle/131551/57159]  |
| 专题 | Journal of Mountain Science_Journal of Mountain Science-2021_Vol18 No.1 |
| 推荐引用方式 GB/T 7714 | Ceryan, Nurcihan. Prediction of Young's modulus of weathered igneous rocks using GRNN, RVM, and MPMR models with a new index[J]. JOURNAL OF MOUNTAIN SCIENCE,2021,18(1):233-251. |
| APA | Ceryan, Nurcihan.(2021).Prediction of Young's modulus of weathered igneous rocks using GRNN, RVM, and MPMR models with a new index.JOURNAL OF MOUNTAIN SCIENCE,18(1),233-251. |
| MLA | Ceryan, Nurcihan."Prediction of Young's modulus of weathered igneous rocks using GRNN, RVM, and MPMR models with a new index".JOURNAL OF MOUNTAIN SCIENCE 18.1(2021):233-251. |
入库方式： OAI收割
来源：成都山地灾害与环境研究所
浏览0
下载0
收藏0
其他版本
除非特别说明，本系统中所有内容都受版权保护，并保留所有权利。