Knowledge Resource Center for Ecological Environment in Arid Area
DOI | 10.1016/j.apgeochem.2011.12.020 |
Neuro-fuzzy modeling based genetic algorithms for identification of geochemical anomalies in mining geochemistry | |
Ziaii, Mansour1; Ardejani, Faramarz Doulati2; Ziaei, Mahdi1; Soleymani, Ali A.1 | |
通讯作者 | Ziaii, Mansour |
来源期刊 | APPLIED GEOCHEMISTRY |
ISSN | 0883-2927 |
出版年 | 2012 |
卷号 | 27期号:3页码:663-676 |
英文摘要 | A genetic algorithm (GA)-based neuro-fuzzy approach is used for identification of geochemical anomalies by implementing a Takagi, Sugeno and Kang (TSK) type fuzzy inference system in a 5-layered feed-forward adaptive artificial neural network. This paper investigates the effectiveness of GA-based neuro-fuzzy for separating zone dispersed mineralization (ZDM) from blind mineralization, and its application for identification of geochemical anomalies in the arid landscape of the Lut metallogenic province in eastern Iran. Other classification algorithms such as metallometry, zonality, criteria, and back-propagation artificial neural network classifiers are also used for comparison. The genetic operators are carefully designed to optimize the artificial neural network, avoiding premature convergence and permutation problems. The results show that the GA-based hybrid neuro-fuzzy model can provide accurate results in comparison with those results obtained by other techniques. Neuro-fuzzy and GA-based neuro-fuzzy techniques appear to be well-suited for routine exploration geochemistry applications. In conjunction with statistics and conventional mathematical methods, hybrid approaches can be developed and may prove a step forward in the practice of applied geochemistry. (C) 2011 Elsevier Ltd. All rights reserved. |
类型 | Article |
语种 | 英语 |
国家 | Iran |
收录类别 | SCI-E |
WOS记录号 | WOS:000300403400012 |
WOS关键词 | MINERAL PROSPECTIVITY ; EXPLORATION ; GOLD ; AREA ; IRAN |
WOS类目 | Geochemistry & Geophysics |
WOS研究方向 | Geochemistry & Geophysics |
资源类型 | 期刊论文 |
条目标识符 | http://119.78.100.177/qdio/handle/2XILL650/171257 |
作者单位 | 1.Shahrood Univ Technol, Fac Min Petr & Geophys, Shahrood, Iran; 2.Univ Tehran, Coll Engn, Sch Min, Tehran, Iran |
推荐引用方式 GB/T 7714 | Ziaii, Mansour,Ardejani, Faramarz Doulati,Ziaei, Mahdi,et al. Neuro-fuzzy modeling based genetic algorithms for identification of geochemical anomalies in mining geochemistry[J],2012,27(3):663-676. |
APA | Ziaii, Mansour,Ardejani, Faramarz Doulati,Ziaei, Mahdi,&Soleymani, Ali A..(2012).Neuro-fuzzy modeling based genetic algorithms for identification of geochemical anomalies in mining geochemistry.APPLIED GEOCHEMISTRY,27(3),663-676. |
MLA | Ziaii, Mansour,et al."Neuro-fuzzy modeling based genetic algorithms for identification of geochemical anomalies in mining geochemistry".APPLIED GEOCHEMISTRY 27.3(2012):663-676. |
条目包含的文件 | 条目无相关文件。 |
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。