An Agent-Based Model of Lost Person Dynamics for Enabling Wilderness Search and Rescue

2019 ◽  
Author(s):  
Amanda Hashimoto ◽  
Nicole Abaid
Keyword(s):  
Real World ◽  
Random Variable ◽  
Fixed Time ◽  
Search And Rescue ◽  
Agent Based Model ◽  
Real World Data ◽  
Agent Based ◽  
World Data ◽  
Analogous Data ◽  
Behavior Strategies

Abstract In this paper, we introduce an agent-based model of lost person behavior that may be used to improve current methods for wilderness search and rescue (SAR). The model defines agents moving on a landscape with behavior considered as a random variable. The behavior uses a distribution of four known lost person behavior strategies in order to simulate possible trajectories for the agent. We simulate all possible distributions of behaviors in the model and compute distributions of horizontal distances traveled in a fixed time. By comparing these results to analogous data from a database of lost person cases, we explore the model’s validity with respect to real-world data.

scholarly journals An agent-based model of sign language persistence informed by real-world data

2020 ◽  
Vol 10 (2) ◽  
pp. 158-187
Author(s):  
Katie Mudd ◽  
Connie de Vos ◽  
Bart de Boer
Keyword(s):  
Sign Language ◽  
Real World ◽  
Cultural Transmission ◽  
Model Development ◽  
Agent Based Modeling ◽  
Real World Data ◽  
Sign Languages ◽  
Genetic Transmission ◽  
Agent Based ◽  
World Data

Abstract As evidence from sign languages is increasingly used to investigate the process of language emergence and evolution, it is important to understand the conditions that allow for sign languages to persist. We build on a mathematical model of sign language persistence (i.e. protection from loss) which takes into account the genetic transmission of deafness, the cultural transmission of sign language and marital patterns (Aoki & Feldman, 1991). We use agent-based modeling techniques and draw inspiration from the wealth of genetic and cultural data on the sign language Kata Kolok to move towards a less abstract model of sign language persistence. In a set of experiments we explore how sign language persistence is affected by language transmission types, the distribution of deaf alleles, population size and marital patterns. We highlight the value of using agent-based modeling for this type of research, which allows for the incorporation of real-world data into model development.

scholarly journals A New Birnbaum–Saunders Distribution and Its Mathematical Features Applied to Bimodal Real-World Data from Environment and Medicine

Mathematics ◽  
2021 ◽  
Vol 9 (16) ◽  
pp. 1891
Author(s):  
Jimmy Reyes ◽  
Jaime Arrué ◽  
Víctor Leiva ◽  
Carlos Martin-Barreiro
Keyword(s):  
Real World ◽  
Random Variable ◽  
Estimation Methods ◽  
Data Sets ◽  
Real World Data ◽  
Fourth Degree ◽  
World Data ◽  
The Monte Carlo Method ◽  
Rejection Criterion ◽  
Methods Of Moments

In this paper, we propose and derive a Birnbaum–Saunders distribution to model bimodal data. This new distribution is obtained using the product of the standard Birnbaum–Saunders distribution and a polynomial function of the fourth degree. We study the mathematical and statistical properties of the bimodal Birnbaum–Saunders distribution, including probabilistic features and moments. Inference on its parameters is conducted using the estimation methods of moments and maximum likelihood. Based on the acceptance–rejection criterion, an algorithm is proposed to generate values of a random variable that follows the new bimodal Birnbaum–Saunders distribution. We carry out a simulation study using the Monte Carlo method to assess the statistical performance of the parameter estimators. Illustrations with real-world data sets from environmental and medical sciences are provided to show applications that can be of potential use in real problems.

Building Distribution Networks Using Cooperating Agents

2007 ◽  
pp. 557-571
Author(s):  
N. Urquhart
Keyword(s):  
Evolutionary Algorithms ◽  
Social Interactions ◽  
Real World ◽  
Social Systems ◽  
Dynamic Environment ◽  
Distribution Networks ◽  
Real World Data ◽  
Agent Based ◽  
World Data ◽  
Cooperating Agents

This chapter examines the use of emergent computing to optimize solutions to logistics problems. The chapter initially explores the use of agents and evolutionary algorithms to optimise postal distribution networks. The structure of the agent community and the means of interaction between agents is based on social interactions previously used to solve these problems. The techniques developed are then adapted for use in a dynamic environment planning the despatch of goods from a supermarket. These problems are based on real-world data in terms of geography and constraints. The author hopes that this chapter will inform researchers as to the suitability of emergent computing in real-world scenarios and the abilities of agent-based systems to mimic social systems.

Abstract #946: Assessment of Acromegaly Patients with and Without Diabetes Treated with Lanreotide Depot: 2-Year Real World Data

2016 ◽  
Vol 22 ◽  
pp. 219
Author(s):  
Roberto Salvatori ◽  
Olga Gambetti ◽  
Whitney Woodmansee ◽  
David Cox ◽  
Beloo Mirakhur ◽  
...  
Keyword(s):  
Real World ◽  
Real World Data ◽  
World Data

Real world data of Type 2 Diabetes Mellitus (T2DM) obese patients using another GLP1 receptor agonist (GLP1–RA) and switching to Semaglutide in Spain

2020 ◽  
Author(s):  
Jersy Cardenas ◽  
Gomez Nancy Sanchez ◽  
Sierra Poyatos Roberto Miguel ◽  
Luca Bogdana Luiza ◽  
Mostoles Naiara Modroño ◽  
...  
Keyword(s):  
Diabetes Mellitus ◽  
Type 2 Diabetes ◽  
Type 2 Diabetes Mellitus ◽  
Real World ◽  
Receptor Agonist ◽  
Obese Patients ◽  
Real World Data ◽  
World Data
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