PPT-Modelling Behaviour in Simulation Models

Stewart Robinson Dean School of Business and Economics Professor of Management Science Four examples A Lorry Loading Bay Problem Knowledge Based Improvement KBI Ford Engine Plant. Pipeline . Qra. Seminar. Pipeline risk assessment . Software for consequence modelling. 2. What is consequence modelling?. Effects from accident (e.g. release or explosion). Strict physical effect (e.g. overpressure from explosion, flow from release and concentration at distance). -Preserving Model Transformation. Arend. . Rensink. , University of . Twente. IPA Spring Days, 18 April 2012. Models in Science. 2. 18 April 2012. Behaviour Preserving Model Transformation. Physical world. Dr Andy . Evans. I. ndividual level.. A. gents interact with environment and each other.. M. odel behaviour and decision making.. Agent-Based Models. Typical social science model:. Agents are burglars.. Lecture 5 & 6. Basics of Device Modelling Approaches. Device Modeling. It is extremely important to have a valid device modeling & simulation design prior to the device fabrication b/c technology & design iteration are expensive and post fabrication tuning is not a fun. . Your exam. Lesson objectives. To be able to define and understand:. Definition . of a simulation model.. Advantages and disadvantages of using simulation models. .. Benefits of Spreadsheet software. Uses of simulation modelling for weather forecasting, car crash analysis and financial forecasting.. Environmental Modelling: II. Dr. Mathias (Mat) Disney. UCL Geography. Office: 113 Pearson Building. Tel: 7670 0592. Email: mdisney@ucl.geog.ac.uk. www.geog.ucl.ac.uk/~mdisney. Last week. Why model?. Improve process / system understanding. Chapter 8. Asfia Rahman . 1. Model. A model is a computer representation of a real-world process. . A . model is created through mathematical analysis oi the real-world process. .. Modelling . software is used to create a model. . Predictions in ecology rely on models. . What is a model?. Matrix algebra. Linear regression models. More on regression. Variance analysis. Model selection techniques. Classification techniques. Eigenvector techniques. Observational learning. Theorist . Albert Bandura. Social learning theory – learning which occurs within a social context.. Provides information about our environment, thoughts, feelings and . behaviours. Joanne Evans and . Mirna. . Willer. Agenda. Introductions. Mirna’s. . story. Entity-Relationship Modeling Method: “Bibliographic Universe”. Joanne’s story. Recordkeeping Metadata Models. Metadata Modeling Exercise. Social Learning Theory (1960s). Combines concepts of . ‘. identification. ’ (. Psychodynamic Approach) and . reinforcement. (Learning Approach. ). tendency . to . observe. and . imitate. . people we . Joanne Evans and . Mirna. . Willer. Agenda. Introductions. Mirna’s. . story. Entity-Relationship Modeling Method: “Bibliographic Universe”. Joanne’s story. Recordkeeping Metadata Models. Metadata Modeling Exercise. Lecture 7 & 8. Hierarchy of Semiconductor Models. Introduction. Nowadays, semiconductor materials are contained in almost all electronic . de-vices. . . Some . examples of semiconductor devices and their use are described in .  . 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.