scholarly journals Agent-Based Land Change Modeling of a Large Watershed: Space-Time Locations of Critical Threshold

2020 ◽  
Vol 23 (1) ◽  
Author(s):  
Wenwu Tang ◽  
Jianxin Yang
Keyword(s):  
Space Time ◽  
Critical Threshold ◽  
Land Change ◽  
Agent Based ◽  
Land Change Modeling

Progress of agent-based agricultural land change modeling: a review

2013 ◽  
Vol 33 (6) ◽  
pp. 1690-1700 ◽  
Author(s):  
余强毅 YU Qiangyi ◽  
吴文斌 WU Wenbin ◽  
杨鹏 YANG Peng ◽  
唐华俊 TANG Huajun ◽  
周清波 ZHOU Qingbo ◽  
...  
Keyword(s):  
Agricultural Land ◽  
Land Change ◽  
Agent Based ◽  
Land Change Modeling

An adding/deleting approach to improve land change modeling: a case study in Qeshm Island, Iran

2019 ◽  
Vol 12 (11) ◽  
Author(s):  
Ali Kourosh Niya ◽  
Jinliang Huang ◽  
Ali Kazemzadeh-Zow ◽  
Babak Naimi
Keyword(s):  
Land Change ◽  
Qeshm Island ◽  
Land Change Modeling

scholarly journals Modelling aerosol-based exposure to SARS-CoV-2 by an agent based Monte Carlo method: Risk estimates in a shop and bar

PLoS ONE ◽  
2021 ◽  
Vol 16 (11) ◽  
pp. e0260237
Author(s):  
Henri Salmenjoki ◽  
Marko Korhonen ◽  
Antti Puisto ◽  
Ville Vuorinen ◽  
Mikko J. Alava
Keyword(s):  
High Risk ◽  
Quantitative Difference ◽  
Equilibrium Concentration ◽  
Infection Risk ◽  
Space Time ◽  
Aerosol Concentration ◽  
Model Parameters ◽  
Single Individual ◽  
Agent Based ◽  
Aerosol Inhalation

Present day risk assessment on the spreading of airborne viruses is often based on the classical Wells-Riley model assuming immediate mixing of the aerosol into the studied environment. Here, we improve on this approach and the underlying assumptions by modeling the space-time dependency of the aerosol concentration via a transport equation with a dynamic source term introduced by the infected individual(s). In the present agent-based methodology, we study the viral aerosol inhalation exposure risk in two scenarios including a low/high risk scenario of a “supermarket”/“bar”. The model takes into account typical behavioral patterns for determining the rules of motion for the agents. We solve a diffusion model for aerosol concentration in the prescribed environments in order to account for local exposure to aerosol inhalation. We assess the infection risk using the Wells-Riley model formula using a space-time dependent aerosol concentration. The results are compared against the classical Wells-Riley model. The results indicate features that explain individual cases of high risk with repeated sampling of a heterogeneous environment occupied by non-equilibrium concentration clouds. An example is the relative frequency of cases that might be called superspreading events depending on the model parameters. A simple interpretation is that averages of infection risk are often misleading. They also point out and explain the qualitative and quantitative difference between the two cases—shopping is typically safer for a single individual person.

Mase

2017 ◽  
pp. 106-127 ◽  
Author(s):  
Celia G. Ralha ◽  
Carolina G. Abreu
Keyword(s):  
Land Use ◽  
Conceptual Model ◽  
Model Complexity ◽  
Land Change ◽  
Map Comparison ◽  
Agent Based ◽  
Change Models ◽  
Multi Agent ◽  
Definition Of ◽  
Simulation Parameters

This chapter presents research carried out under the MASE project, including the definition of a conceptual model to characterize the behavior of individuals that interact in the dynamics of land-use and cover change. A computational tool for analyzing environmental scenarios of land change was developed, called MASE - Multi-Agent System for Environmental Simulation. MASE enables agent-based simulation scenarios and integrates the influence of socio-economic and political dynamics through the interaction of agents with rules of land-use and planning policies and the environmental physical and spatial variables. MASE simulator was extended to implement the Belief-Desire-Intention (BDI) model, called MASE-BDI. MASE and MASE-BDI are discussed including the conceptual model complexity and statistical techniques of map comparison to land change models. Two real cases of the Brazilian Cerrado validate quantitative and qualitative aspects of MASE and MASE-BDI simulators. Finally, the authors present some auto-tuning aspects of adjusting simulation parameters of MASE-BDI.

Revealing Uncertainties in Land Change Modeling Using Probabilities

2015 ◽  
Vol 20 (4) ◽  
pp. 526-546 ◽  
Author(s):  
Carsten Krüger ◽  
Tobia Lakes
Keyword(s):  
Land Change ◽  
Land Change Modeling

A review of current calibration and validation practices in land-change modeling

2016 ◽  
Vol 82 ◽  
pp. 174-182 ◽  
Author(s):  
Jasper van Vliet ◽  
Arnold K. Bregt ◽  
Daniel G. Brown ◽  
Hedwig van Delden ◽  
Scott Heckbert ◽  
...  
Keyword(s):  
Land Change ◽  
Calibration And Validation ◽  
Land Change Modeling

MASE-BDI: agent-based simulator for environmental land change with efficient and parallel auto-tuning

2016 ◽  
Vol 45 (3) ◽  
pp. 904-922 ◽  
Author(s):  
Cássio G. C. Coelho ◽  
Carolina G. Abreu ◽  
Rafael M. Ramos ◽  
Aldo H. D. Mendes ◽  
George Teodoro ◽  
...  
Keyword(s):  
Land Change ◽  
Agent Based ◽  
Bdi Agent ◽  
Auto Tuning
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