Modeling the Effects of Disasters on a Human Population and Resources Population and Resources TJHSST Computer Systems Tech Lab 2008-2009 Joshua Yoon.

Slides:



Advertisements
Similar presentations
JustinMind: Dynamic Panels
Advertisements

System Dynamics Modeling with STELLA software. Learning objective  After this class the students should be able to: Understand basic concepts of system.
Unified Modeling Language
A metapopulation simulation including spatial heterogeneity, among and between patch heterogeneity Travis J. Lawrence Department of Biological Science,
Agent-based model of a simple stable economy Alexandre Lomovtsev Advisor: Dr. Russell Abbott, Ph.D. California State University, Los Angeles Department.
Introduction to Neural Network Justin Jansen December 9 th 2002.
©TheMcGraw-Hill Companies, Inc. Permission required for reproduction or display. Chapter 1 Introduction to Object-Oriented Programming and Software Development.
©TheMcGraw-Hill Companies, Inc. Permission required for reproduction or display. Chapter 1 Introduction to Object-Oriented Programming and Software Development.
Dynamic Models Lecture 13. Dynamic Models: Introduction Dynamic models can describe how variables change over time or explain variation by appealing to.
Modeling Fishery Regulation & Compliance: A Case Study of the Yellowtail Rockfish Wayne Wakeland Portland State University Systems Science Ph.D. Program.
©TheMcGraw-Hill Companies, Inc. Permission required for reproduction or display. Chapter 1 Introduction to Object-Oriented Programming and Software Development.
Agent-based model of a simple stable economy Alexandre Lomovtsev Advisor: Dr. Russell Abbott, Ph.D. California State University, Los Angeles Department.
Monté Carlo Simulation MGS 3100 – Chapter 9. Simulation Defined A computer-based model used to run experiments on a real system.  Typically done on a.
Introduction To C++ Programming 1.0 Basic C++ Program Structure 2.0 Program Control 3.0 Array And Structures 4.0 Function 5.0 Pointer 6.0 Secure Programming.
Process Modeling SYSTEMS ANALYSIS AND DESIGN, 6 TH EDITION DENNIS, WIXOM, AND ROTH © 2015 JOHN WILEY & SONS. ALL RIGHTS RESERVED. 1 Roberta M. Roth.
New Mexico Computer Science For All More Looping in NetLogo Maureen Psaila-Dombrowski.
Emergy & Complex Systems Day 1, Lecture 1…. Energy Systems Diagramming Energy Systems Diagramming A Systems language...symbols, conventions and simulation…
FW364 Ecological Problem Solving Lab 4: Blue Whale Population Variation [Ramas Lab]
Chapter 4 Populations. Properties of Populations Population: a group of organisms of 1 species in the same area 1) Population Size (usually estimated)
Simulation of Global Warming in the Continental United States Using Agent-Based Modeling By Marika Lohmus.
© CCI Learning Solutions Inc. 1 Lesson 5: Basic Troubleshooting Techniques Computer performance Care of the computer Working with hardware Basic maintenance.
© Copyright 1992–2005 by Deitel & Associates, Inc. and Pearson Education Inc. All Rights Reserved. Tutorial 4 – Wage Calculator Application: Introducing.
Software Life Cycle Requirements and problem analysis. –What exactly is this system supposed to do? Design –How will the system solve the problem? Coding.
Prerequisites: Fundamental Concepts of Algebra
Chapter 5 Populations 5-1 How Populations Grow.
Discrete Distributions The values generated for a random variable must be from a finite distinct set of individual values. For example, based on past observations,
Copyright © 2007 Pearson Education, Inc. Publishing as Pearson Addison-Wesley Chapter 11 Understanding Randomness.
Population Dynamics Ms. Becky Blackwell Dr. Deano Smith Mr. Dean Sheridan Ms. Mary Ellen McNamara Glenelg High School Glenelg, Maryland.
Network Optimization Problems
Operations Management using System Dynamics Part I.
Epidemic Modeling in NetLogo Brendan Greenley Pd. 3.
Basic building blocks of SD Levels (Stocks), Rates (Flows), Auxiliary variables and Arrows Essential building blocks Represent the way dynamic systems.
SD modeling process One drawback of using a computer to simulate systems is that the computer will always do exactly what you tell it to do. (Garbage in.
The Evolution of Specialisation in Groups – Tags (again!) David Hales Centre for Policy Modelling, Manchester Metropolitan University, UK.
Lesson 6 – Libraries & APIs Libraries & APIs. Objective: We will explore how to take advantage of the huge number of pre-made classes provided with Java.
How Populations Grow. What is a Population? A population consists of all individuals of a species that live together in one place at one time. A population.
1 1 Slide Simulation Professor Ahmadi. 2 2 Slide Simulation Chapter Outline n Computer Simulation n Simulation Modeling n Random Variables and Pseudo-Random.
CSCI1600: Embedded and Real Time Software Lecture 28: Verification I Steven Reiss, Fall 2015.
EVAN’S FAST FOOD VISUAL BASIC 2012 FINAL PROJECT BY: EVAN CHOATE.
STL CSSE 250 Susan Reeder. What is the STL? Standard Template Library Standard C++ Library is an extensible framework which contains components for Language.
System Dynamics Modeling of Community Sustainability in NetLogo Thomas Bettge TJHSST Computer Systems Lab Senior Research Project
Simulation of the Spread of a Virus Throughout Interacting Populations with Varying Degrees and Methods of Vaccination Jack DeWeese Computer Systems Lab.
Modeling the effect of virus transmission on population using Systems Dynamics Modeling Dheeraj Manjunath Computer Systems Lab TJHSST.
Populations. Remember a population is… A group of the same species in the same area at the same time. A group of the same species in the same area at.
Lessons from the Tragedy of the Sahel Doug Cullen, July 2010.
Evolving Specialisation, Altruism & Group-Level Optimisation Using Tags David Hales Centre for Policy Modelling, Manchester Metropolitan University, UK.
Computer Systems Lab TJHSST Current Projects In-House, pt 2.
System Dynamics Modeling of Community Sustainability in NetLogo Thomas Bettge TJHSST Computer Systems Lab Senior Research Project
“Unboxing” means taking an Integer object and assigning its value to a primitive int. This is done using the.intValue( ) method. Example; Integer z = new.
YEAR 11 MATHS REVISION Box Plots Cumulative Frequency with Box Plots.
CSE 219 Final exam review.
Inventory Levels.
Unit 2 Lesson 3 Models and Simulations
The Nature of Science Do Now: In your notes answer the following question What does science mean to you?
Population Dynamics (Predator-Prey relationship).
Modeling Human Population Growth
Chapter 5 Populations 5-1 How Populations Grow.
Completing the tasks for A452 with….
Simulation Modeling.
Population Growth How Populations Grow.
Section 1: How Populations Grow
Modeling the Effects of Disasters on a Human Population and Resources
Population Ecology How are populations dispersed in areas?
Students will be able to: Convert data sets into graphs.
Unit 4- Interaction of Living Things
Hiroki Sayama NECSI Summer School 2008 Week 2: Complex Systems Modeling and Networks Agent-Based Models Hiroki Sayama
Maintenance Sheet Due Wednesday
Maintenance Sheet Due Wednesday
Maintenance Sheet Due Wednesday
Modeling the Effects of Disasters on a Human Population and Resources
Presentation transcript:

Modeling the Effects of Disasters on a Human Population and Resources Population and Resources TJHSST Computer Systems Tech Lab Joshua Yoon

Recently over the past decades, numerous disasters such as the earthquakes and tsunamis have struck all over the world This project is an attempt to not only model the effects of these disasters on a human population accurately, but also be able to extrapolate the effects of future disasters on a nearby human population using a System Dynamics approach.Abstract

System Dynamics portion of the NetLogo language, and the System Dynamics approach looks into the relationships between different local variables Difference between System Dynamics and agent-based modeling: System Dynamics looks into the relationship between variables and how these variables affect each other over time, whereas in agent- based, interactions between individuals of a population are generated randomly Background

Current System Dynamics modeler used is "Stella" Currently using NetLogo, must draw up the separate variables and the relationships between them System Dynamics can be used in many different ways, but mainly to simulate efficiency Train System Efficiency Policy on flood prevention Background cont.

Create a human population that behaves like a human population Implement a resource class, which inhibits unlimited growth of the population Implement disasters so that human population drops and recovers over time Compare simulation test results with results from actual disasters Methodology/Procedure

Disaster Class: This portion of the code handles everything there is to handle about disasters. The death rates are made by the different converters (blue diamonds), and each death rate is set to a constant. The DisasterProbability converter handles the frequency of a disaster. The converter creates a random integer from 0 to 400 and if that random integer is equal to 1, then the disaster(s) is turned on. The ActiveDisaster converter calculates new death rates if more than one disaster is turned on at once. All of these converters connect to DeathDRate, which is the final death rate due to disaster after all the disaster related death rates have been accounted for. 3 Main Components: Part 1

Resource Class: This is another stock called resources. This stock represents the resources, which are available to the population and this in turn keeps the population in check. I made this class originally to create a carrying capacity, but now I'm implementing it so that resources can also be affects by disasters. The DeathNDRate stock stands for the non-disaster death rate, and basically it is controlled by the resources and how abundant the resources are compared to the size of the population. 3 Main Components: Part 2

Human Class: This diagram controls the actual human population signified by the stock (tan box). There is an inflow (gray arrows going into stock) of people, which are new people added to the already existing population, and then there is the outflow (gray arrow going out of stock) which signifies the death of individuals in the population. The inflows are controlled by converters such as BirthRate and NewPeopleInfluxRate, whereas the outflow is controlled by the DeathDRate and DeathNDRate. 3 Main Components: Part 3

The Complete Web: 3 Main Components: Pieced Together

Simulations are now running, even though the behavior of human population hasn't been perfected. There is obviously a relationship between the variables, but that too must be perfected. Results & Conclusions

Curve looks similar to a regular human population curve, and the recovery curve is sporadic, but it exists. Must work more to fix the glitches, and then comparisons to real disaster data will begin Results & Conclusions cont.