|
|||||
|
|
| 基于自适应神经网络模糊推理系统的竖井井斜预测 | |
| 引用本文： | 范成洲,曹钧,尹晓利. 基于自适应神经网络模糊推理系统的竖井井斜预测[J]. 矿山机械, 2011, 0(4): 23-26 |
| 作者姓名： | 范成洲 曹钧 尹晓利 |
| 作者单位： | 西北核技术研究所; |
| 摘 要： | 井斜是评价成井质量的重要指标之一,钻井工艺参数是影响竖井并斜的重要因素.基于自适应神经网络模糊推理(ANFIS,adaptive neural-network-based fuzzy inference system)建立了竖井井斜预测模型,将钻压和转速两个主要钻井工艺参数作为输入变量,并选用某竖井部分录井数据作为基础... |
| 关 键 词： | 井斜 预测 自适应 神经网络 模糊推理 |
Prediction of shaft obliquity based on adaptive neural-network-based fuzzy inference system |
|
| Abstract: | The shaft obliquity is an important evaluating indicator of shaft quality,while drilling parameters is the main factor affecting the shaft obliquity.The paper establishes the model of predicting the shaft obliquity based on ANFIS (adaptive neural-network-based fuzzy inference system).It also takes drilling pressure and rotary speed which are two main drilling parameters as input variables,and selects some drilling data of a shaft as the basic data for model training and testing.The results show that the rel... |
| Keywords: | shaft obliquity prediction adaptive neural network fuzzy inference |
| 本文献已被 CNKI 等数据库收录！ | |