A Monte Carlo Approach to Estimating the Significance of Segregation

1984 ◽  
Vol 16 (2) ◽  
pp. 225-231 ◽  
Author(s):  
A Findlay ◽  
Anne Findlay
Keyword(s):  
Monte Carlo Simulation ◽  
Monte Carlo ◽  
Case Studies ◽  
Spatial Statistics ◽  
Null Hypothesis ◽  
Dissimilarity Index ◽  
Monte Carlo Approach ◽  
Simulation Methodology ◽  
Simulation Techniques ◽  
Social Segregation

Simulation techniques are not new to geography, but they have focused traditionally on attempts to replicate observed patterns rather than on seeking to assist in the formulation of a null hypothesis. The benefits and problems of a Monte Carlo simulation methodology are examined with reference to the latter objective. The flexibility of the approach in the evaluation of spatial statistics is shown to be considerable. Specific case studies are pursued which exemplify its potential in the investigation of social segregation using familiar measures such as the dissimilarity index and the P* index.

scholarly journals Practical Risk Assessment of Ground Vibrations Resulting from Blasting, Using Gene Expression Programming and Monte Carlo Simulation Techniques

2020 ◽  
Vol 10 (2) ◽  
pp. 472 ◽  
Author(s):  
Amir Mahdiyar ◽  
Danial Jahed Armaghani ◽  
Mohammadreza Koopialipoor ◽  
Ahmadreza Hedayat ◽  
Arham Abdullah ◽  
...  
Keyword(s):  
Gene Expression ◽  
Monte Carlo Simulation ◽  
Monte Carlo ◽  
Gene Expression Programming ◽  
Sensitivity Analyses ◽  
Accurate Estimation ◽  
Blasting Operation ◽  
Simulation Techniques ◽  
Input Variables ◽  
The Impact

Peak particle velocity (PPV) is a critical parameter for the evaluation of the impact of blasting operations on nearby structures and buildings. Accurate estimation of the amount of PPV resulting from a blasting operation and its comparison with the allowable ranges is an integral part of blasting design. In this study, four quarry sites in Malaysia were considered, and the PPV was simulated using gene expression programming (GEP) and Monte Carlo simulation techniques. Data from 149 blasting operations were gathered, and as a result of this study, a PPV predictive model was developed using GEP to be used in the simulation. In order to ensure that all of the combinations of input variables were considered, 10,000 iterations were performed, considering the correlations among the input variables. The simulation results demonstrate that the minimum and maximum PPV amounts were 1.13 mm/s and 34.58 mm/s, respectively. Two types of sensitivity analyses were performed to determine the sensitivity of the PPV results based on the effective variables. In addition, this study proposes a method specific to the four case studies, and presents an approach which could be readily applied to similar applications with different conditions.

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