Effective use of radiation monitoring data and dispersion calculations in an emergency

2007 ◽  
Vol 4 (3) ◽  
pp. 468 ◽  
Author(s):  
Juhani Lahtinen ◽  
Harri Toivonen ◽  
Riitta Hanninen
Keyword(s):  
Radiation Monitoring ◽  
Monitoring Data ◽  
Effective Use

Particle Swarm Optimization Least Square Support Machine Based Missing Data Imputation Algorithm in Wireless Sensor Network for Nuclear Power Plant’s Environmental Radiation Monitor

2012 ◽  
Vol 605-607 ◽  
pp. 2137-2144
Author(s):  
Song Gao ◽  
Yao Geng Tang ◽  
Xing Qu
Keyword(s):  
Missing Data ◽  
Nuclear Power ◽  
Radiation Monitoring ◽  
Gamma Dose ◽  
Monitoring Data ◽  
Wireless Sensor ◽  
Rate Data ◽  
Data Imputation ◽  
Environmental Radiation ◽  
Missing Data Imputation

In wireless sensor network for nuclear power plant’s peripheral environmental radiation monitoring the gamma dose rate data may be missed affected by various factors, which will influence the validity of environmental radiation monitoring. To solve the problem, a missing data imputation algorithm is proposed based on particle swarm optimized least squares support vector machine. This algorithm imputes missing data utilizing node’s previous monitoring data and neighbor node’s current monitoring data jointly. Experimental results using the real radiation monitoring data around a nuclear power plant show that the proposed algorithm can impute the missing gamma dose rate data accurately.

Fractal Characteristics of Motion Trace Curve of Landslide Monitoring Points

2011 ◽  
Vol 90-93 ◽  
pp. 1285-1290 ◽  
Author(s):  
Xian Ming Hu ◽  
E Chuan Yan ◽  
Kun Lv ◽  
Ting Ting Zhang
Keyword(s):  
Fractal Theory ◽  
Fractal Dimensions ◽  
Monitoring Data ◽  
Movement Direction ◽  
Landslide Monitoring ◽  
Box Dimension ◽  
Monitoring Point ◽  
Fractal Characteristics ◽  
Landslide Development ◽  
Effective Use

According to the analysis of the landslide monitoring data, it is revealed that the amount of the cumulative displacement of the landslide depends on the monitoring cycle. And the trajectory curve of monitoring point has the fractal characteristics. The fractal dimension of the landslide internal points’ movement direction is various with the landslide development, which is decreased from the generation to the deformation and then to the damage. Meanwhile, based on the fractal boxing counting theorem, the program in Matlab is created to calculate the box dimension of the curve. Take a reviving landslide in Three-Gorge as an example, the fractal dimensions of the surface GPS monitoring points’ trajectory curves from 2007 to 2009 are obtained, and the dimension of each point is close to 1. The result indicates that this landslide is in the plastic deformation stage. It is the same with the landslide actual deformation. Therefore, the fractal theory has a great significance in the effective use of the monitoring data, the reorganization of the evolving stage and the prediction of the deformation trend for the landslide.

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