PPT-Simulation Models 16 Introduction

Simulation can be used to analyze a wide variety of problems The applications can be grouped into four general areas Operations models Financial models Marketing models Games of chance. Sherman Robinson. International Food Policy Research Institute (IFPRI. ). Outline. Simulation models: . Types. issues. design. Implementation. Impact model. CGE models . Estimation and validation. 2. Using Modeling and Simulation for. System . Level Analysis and Design. Prof. Dr. Fran. çois E. Cellier. Computer Science Department. ETH Zurich. Switzerland. Acknowledgments. Dr. Ernesto . Kofman. (National University of Rosario, Argentina) is the originator of the . th. . Victory in the . Kargil. War – homage to those that struggled that we may live happily!. Introduction to Stochastic Modeling and Simulation (MEL770). Introduction and Motivation. Intro. . Nomesh. Dr. . Feng Gu. Weather Prediction Example. Possible models to predict the weather tomorrow. . 1. Mystery-based models . (e.g., whenever my right eyelid twitches, it is going to rain tomorrow) . Konstantinos Theodorakos. January 2015. Modern Processor Design. “Free lunch is over”. Lower Power consumption is favored on multi-core/processor architectures. CBD Parallelization . intention. Why Parallelize CBD models?. Charge . Your Friends . for . Borrowing Your Stuff. Kijung Shin. , . Euiwoong. Lee. , . Dhivya. . Eswaran. , . Ariel . Procaccia. Carnegie Mellon University . Motivation: Sharable . Goods. Used rarely. Tom Creasey, PE, PhD. September 9, 2015. Models: Keeping the Horse before the Cart. “If all you have is a hammer, everything looks like a nail.”. Paraphrased from. The Psychology of Science. Abraham Maslow, 1966. Introduction. In the previous . chapter, . we introduced most of the important concepts for developing . and analyzing . spreadsheet simulation models. . We . also discussed many of the features . available in . Dr. . Feng Gu. Weather Prediction Example. Possible models to predict the weather tomorrow. . 1. Mystery-based models . (e.g., whenever my right eyelid twitches, it is going to rain tomorrow) . Reproducibility. MIASE Definition. 1. Repeatability. The closeness between independent simulations performed with the same methods on identical models with the . same experimental setup.. Reproducibility.  . With Bayesian conditional density estimation. Problem. Analytic expressions for likelihood of parameters is not available with simulation based models. Approximate Bayesian Computation (ABC). Provides likelihood free inference. Simulation Models 16 Introduction Simulation can be used to analyze a wide variety of problems. The applications can be grouped into four general areas: Operations models Financial models Marketing models Geant4 toolkit & collaboration. J. Apostolakis, CERN. for the Geant4 collaboration. 2. Overview. Simulation packages/toolkits . Key capabilities and concepts. What it can do - highlights. Application . Sherman Robinson. International Food Policy Research Institute (IFPRI. ). Outline. Simulation models: . Types. issues. design. Implementation. Impact model. CGE models . Estimation and validation. 2.