Monthly groundwater level prediction using ANN and neuro-fuzzy models: a case study on Kerman plain, Iran

Amir Jalalkamali; Hossein Sedghi; Mohammad Manshouri

首页> 外文期刊>Journal of Hydroinformatics >Monthly groundwater level prediction using ANN and neuro-fuzzy models: a case study on Kerman plain, Iran

【24h】

Monthly groundwater level prediction using ANN and neuro-fuzzy models: a case study on Kerman plain, Iran

机译：基于人工神经网络和神经模糊模型的每月地下水位预测：以伊朗克尔曼平原为例

获取原文

获取原文并翻译 | 示例

掌桥外文数据库（机构版） >>

开具论文收录证明 >>

文献代查 >>

页面导航

摘要
著录项
相似文献
相关主题

摘要

The prediction of groundwater levels in a well has immense importance in the management of groundwater resources, especially in arid regions. This paper investigates the abilities of neuro-fuzzy (NF) and artificial neural network (ANN) techniques to predict the groundwater levels. Two different NF and ANN models comprise various combinations of monthly variablities, that is, air temperature, rainfall and groundwater levels in neighboring wells. The result suggests that the NF and ANN techniques are a good choice for the prediction of groundwater levels in individual wells. Also based on comparisons, it is found that the NF computing techniques have better performance than the ANN models in this case.

机译：井中地下水位的预测在地下水资源管理中尤其是在干旱地区具有极其重要的意义。本文研究了神经模糊（NF）和人工神经网络（ANN）技术预测地下水位的能力。两种不同的NF和ANN模型包括月变化的各种组合，即相邻井中的气温，降雨量和地下水位。结果表明，NF和ANN技术是预测单个井中地下水位的好选择。同样基于比较，发现在这种情况下，NF计算技术比ANN模型具有更好的性能。

著录项

来源
《Journal of Hydroinformatics》 |2011年第4期|p.867-876|共10页
作者
Amir Jalalkamali; Hossein Sedghi; Mohammad Manshouri;
展开▼
作者单位

Department of Water Sciences and Engineering, Science and Research Branch, Islamic Azad University, Tehran, Iran;

Department of Water Sciences and Engineering, Science and Research Branch, Islamic Azad University, Tehran, Iran;

Department of Water Sciences and Engineering, Science and Research Branch, Islamic Azad University, Tehran, Iran;

展开▼
收录信息美国《科学引文索引》(SCI);
原文格式 PDF
正文语种 eng
中图分类
关键词
ANN; groundwater level; kerman plain; neuro-fuzzy;

机译：人工神经网络地下水位;克曼平原神经模糊;

相似文献

外文文献
中文文献
专利

1. Monthly groundwater level prediction using ANN and neuro-fuzzy models: a case study on Kerman plain, Iran [J] . Amir Jalalkamali Hossein Sedghi and Mohammad Manshouri Journal of Hydroinformatics . 2011,第4期

机译：基于人工神经网络和神经模糊模型的每月地下水位预测：以伊朗克尔曼平原为例
2. Prediction the Groundwater Level of Bastam Plain (Iran) by Artificial Neural Network (ANN) and Adaptive Neuro-Fuzzy Inference System (ANFIS) [J] . Samad Emamgholizadeh, Khadije Moslemi, Gholamhosein Karami Water Resources Management . 2014,第15期

机译：利用人工神经网络（ANN）和自适应神经模糊推理系统（ANFIS）预测巴斯塔姆平原（伊朗）的地下水位
3. Groundwater salinity prediction using adaptive neuro-fuzzy inference system methods: a case study in Azarshahr, Ajabshir and Maragheh plains, Iran [J] . Nazari Hosnie, Taghavi Behnam, Hajizadeh Farnusch Environmental earth sciences . 2021,第4期

机译：采用自适应神经模糊推理系统方法的地下水盐度预测 - Azarshahr，Ajabshir和Maragheh Plains，伊朗的案例研究
4. Application of Back-Propagation Artificial Neural Network Models for Prediction of Groundwater Levels: Case study in Western Jilin Province, China [C] . Zhongping YANG, Wenxi LU, Yuqiao LONG, The 2nd International Conference on Bioinformatics and Biomedical Engineering(iCBBE 2008)(第二届生物信息与生物医学工程国际会议）论文集 . 2008

机译：反向传播人工神经网络模型在地下水位预测中的应用：以吉林省西部为例
5. Integrating Urban Recharge Uncertainty into Standard Groundwater Modeling Practice: A Case Study on Water Main Break Predictions for the Barton Springs Segment of the Edwards Aquifer, Austin, Texas. [D] . Sinner, Kate M.L. 2017

机译：将城市补给的不确定性纳入标准的地下水模拟实践中：以德克萨斯州奥斯丁市爱德华兹含水层的巴顿温泉段的水主中断预测为例。
6. Optimization of DRASTIC method by artificial neural network nitrate vulnerability index and composite DRASTIC models to assess groundwater vulnerability for unconfined aquifer of Shiraz Plain Iran [O] . Mohammad Ali Baghapour, Amir Fadaei Nobandegani, Nasser Talebbeydokhti, 2016

机译：通过人工神经网络硝酸盐脆弱性指数和复合DRASTIC模型优化DRASTIC方法以评估伊朗设拉子平原非承压含水层的地下水脆弱性
7. Monthly groundwater level prediction using ANN and neuro-fuzzy models: a case study on Kerman plain, Iran [O] . Amir Jalalkamali, Hossein Sedghi, Mohammad Manshouri 2010

机译：Ann和Neuro-Fuzzy模型的每月地下水位预测：伊朗克尔曼平原的案例研究

Monthly groundwater level prediction using ANN and neuro-fuzzy models: a case study on Kerman plain, Iran

摘要

著录项

相似文献

相关主题

期刊订阅