Bayesian event tree for eruption forecasting (BET_EF) at Vesuvius, Italy: a retrospective forward application to the 1631 eruption

2009 ◽  
Vol 71 (7) ◽  
pp. 729-745 ◽  
Author(s):  
Laura Sandri ◽  
Emanuela Guidoboni ◽  
Warner Marzocchi ◽  
Jacopo Selva
Keyword(s):  
Event Tree ◽  
Eruption Forecasting ◽  
Bayesian Event Tree

scholarly journals Computing for Numeracy: How Safe is Your COVID-19 Social Bubble?

Numeracy ◽  
2021 ◽  
Vol 14 (1) ◽  
Author(s):  
Charles Connor
Keyword(s):  
Small Groups ◽  
Assisted Living ◽  
Event Tree ◽  
Risk Of Infection ◽  
Assisted Living Facility ◽  
Web Based ◽  
The Social ◽  
Bayesian Event Tree

The COVID-19 pandemic has led many people to form social bubbles. These social bubbles are small groups of people who interact with one another but restrict interactions with the outside world. The assumption in forming social bubbles is that risk of infection and severe outcomes, like hospitalization, are reduced. How effective are social bubbles? A Bayesian event tree is developed to calculate the probabilities of specific outcomes, like hospitalization, using example rates of infection in the greater community and example prior functions describing the effectiveness of isolation by members of the social bubble. The probabilities are solved for two contrasting examples: members of an assisted living facility and members of a classroom, including their teacher. A web-based calculator is provided so readers can experiment with the Bayesian event tree and learn more about these probabilities by modeling their own social bubble.

scholarly journals Predicting the probability of Mount Merapi eruption using Bayesian Event Tree_Eruption Forecasting

2018 ◽  
Vol 154 ◽  
pp. 01050 ◽  
Author(s):  
Dyah Ika Rinawati ◽  
Diana Puspita Sari ◽  
Naniek Utami Handayani ◽  
Bramasta Raga Siwi
Keyword(s):  
Disaster Management ◽  
Probabilistic Model ◽  
Disaster Mitigation ◽  
Event Tree ◽  
Volcanic Event ◽  
Volcanic Explosivity Index ◽  
Bayesian Event Tree ◽  
Phase Prediction ◽  
Main Crater ◽  
Logical Information

Mount Merapi is one of the active volcanoes in Indonesia that had varied eruption periods from two to eight years. Due to the density of the population living around the slopes of Mount Merapi, its eruptions caused high number of victims. In order to avoid high number of victims, the disaster management should be improved. Disaster management consist of four phases i.e. mitigation, preparedness, response and reconstruction. In disaster mitigation phase, prediction of the Merapi unrest probability is needed. This paper focus on how to predict the probability of Merapi unrest based on volcano-logical information by using Bayesian Event Tree. Bayesian Event Tree (BET) is a probabilistic model that merges all kinds of volcano-logical information to obtain probability of any relevant volcanic event. The result showed that the probability of Merapi unrest is 0,822. In the next eruption, it has predicted that the volcanic explosivity index (VEI) 2 was biggest chance with the probability of 0,549. It showed that the eruption will take place in the main crater of Merapi with the probability of 0,938.

A new Bayesian Event Tree tool to track and quantify volcanic unrest and its application to Kawah Ijen volcano

2016 ◽  
Vol 17 (7) ◽  
pp. 2539-2555 ◽  
Author(s):  
Roberto Tonini ◽  
Laura Sandri ◽  
Dmitri Rouwet ◽  
Corentin Caudron ◽  
Warner Marzocchi ◽  
...  
Keyword(s):  
Event Tree ◽  
Volcanic Unrest ◽  
Bayesian Event Tree ◽  
Kawah Ijen

FAULT AND EVENT-TREE TECHNIQUES IN OCCUPATIONAL HEALTH-SAFETY SYSTEMS - PART II: STATISTICAL ANALYSIS

2014 ◽  
Vol 13 (9) ◽  
pp. 2371-2386 ◽  
Author(s):  
Panagiotis Marhavilas ◽  
Dimitrios Koulouriotis ◽  
Christos Mitrakas
Keyword(s):  
Statistical Analysis ◽  
Occupational Health ◽  
Event Tree ◽  
Health Safety ◽  
Safety Systems

Volcanic eruption forecasting

Impact ◽  
2018 ◽  
Vol 2018 (6) ◽  
pp. 66-68
Author(s):  
Kostas Konstantinou
Keyword(s):  
Volcanic Eruption ◽  
Eruption Forecasting
Sign in / Sign up

Export Citation Format

Share Document