Combat modeling with imprecise data

1992 ◽  
Vol 7 (3) ◽  
pp. 277-291
Author(s):  
V. Protopopescu ◽  
R. Yager ◽  
J. Dockery
Keyword(s):  
Imprecise Data ◽  
Combat Modeling

Bootstrap approach to the multi-sample test of means with imprecise data

2006 ◽  
Vol 51 (1) ◽  
pp. 148-162 ◽  
Author(s):  
María Ángeles Gil ◽  
Manuel Montenegro ◽  
Gil González-Rodríguez ◽  
Ana Colubi ◽  
María Rosa Casals
Keyword(s):  
Imprecise Data ◽  
Bootstrap Approach ◽  
Sample Test

scholarly journals Integration of different-quality data in short-term mining planning

2015 ◽  
Vol 68 (2) ◽  
pp. 221-227 ◽  
Author(s):  
Cristina Paixão Araújo ◽  
João Felipe Coimbra Leite Costa
Keyword(s):  
Mineral Exploration ◽  
Quality Data ◽  
Imprecise Data ◽  
Short Term ◽  
Mining Operations ◽  
Different Types ◽  
Block Models ◽  
The Impact ◽  
Block Distribution ◽  
Ordinary Cokriging

AbstractDecisions, from mineral exploration to mining operations, are based on grade block models obtained from samples. This study evaluates the impact of using imprecise data in short-term planning. The exhaustive Walker Lake dataset is used and is considered as the source for obtaining the true grades. Initially, samples are obtained from the exhaustive dataset at regularly spaced grids of 20 × 20 m and 5 × 5 m. A relative error (imprecision) of ±25% and a 10% bias are added to the data spaced at 5 × 5 m (short-term geological data) in different scenarios. To combine these different types of data, two methodologies are investigated: cokriging and ordinary kriging. Both types of data are used to estimate blocks with the two methodologies. The grade tonnage curves and swath plots are used to compare the results against the true block grade distribution. In addition, the block misclassification is evaluated. The results show that standardized ordinary cokriging is a better methodology for imprecise and biased data and produces estimates closer to the true grade block distribution, reducing block misclassification.

Data envelopment analysis with imprecise data

2002 ◽  
Vol 140 (1) ◽  
pp. 24-36 ◽  
Author(s):  
Dimitris K. Despotis ◽  
Yiannis G. Smirlis
Keyword(s):  
Data Envelopment Analysis ◽  
Data Envelopment ◽  
Imprecise Data

Statistics with Imprecise Data

2009 ◽  
pp. 8679-8690 ◽  
Author(s):  
María Ángeles Gil ◽  
Olgierd Hryniewicz
Keyword(s):  
Imprecise Data
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