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Sensitivity Analysis and Monte Carlo Simulation
 
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When you are working with large and complex Simulink models, it is sometimes difficult to determine which model parameters impact behavior the most. Using Monte Carlo simulations, correlation techniques and design of experiments (DoE), Sensitivity Analysis allows you to determine which parameters have the greatest impact on your model.
Views: 1692 Opti-Num Solutions
Sensitivity Analysis and Monte Carlo Simulations using Simulink Design Optimization
 
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Free MATLAB Trial: https://goo.gl/yXuXnS Request a Quote: https://goo.gl/wNKDSg Contact Us: https://goo.gl/RjJAkE Learn more about MATLAB: https://goo.gl/8QV7ZZ Learn more about Simulink: https://goo.gl/nqnbLe ------------------------------------------------------------------------- When you are working with large and complex Simulink models, it is sometimes difficult to determine which model parameters impact behavior the most. Using Monte Carlo simulations, correlation techniques and design of experiments (DoE), Sensitivity Analysis allows you to determine which parameters have the greatest impact on your model. In this webinar, we will use an example to demonstrate how to analyze and visualize your model's behavior across its design space using Monte Carlo simulations. This will help you identify which parameters impact characteristics such as step response times, energy consumption and component failure rates. You can also use sensitivity analysis to improve design optimization performance. Using an example, we will see how you can identify a good initial point and a smaller set of parameters in a large model, allowing you to reduce the time taken for the optimization process.
Views: 2417 MATLAB
11 GAMS and Matlab - Sensitivity Analysis (Example)
 
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Download scripts/files/codes and further information: www.gamsoptimization.com. This video shows a small sensitivity analysis to point out how a big one can work.
Views: 844 man goon
00 Sensitivity Analysis with GAMS and Matlab - Introduction
 
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Download scripts/files/codes and further information: www.gamsoptimization.com. This video introduces to my youtube channel and website. I explain how to link GAMS, Matlab and Excel so that sensitivity analyses can be conducted conveniently.
Views: 1315 man goon
Sensitivity Analysis
 
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The concept of sensitivity of a function to small changes in one of its parameters is introduced. After showing how to compute it, a few examples are considered. The final example shows how sensitivity can be applied to closed loop control design.
Views: 25674 Gordon Parker
Sensitivity Analysis
 
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Views: 1395 Wehrspohn
Dynamic Optimization Sensitivity in MATLAB and Python
 
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Dynamic optimization solutions may be sensitive to certain parameters or variables that are decisions. A sensitivity analysis determines how the objective or other variables change with those parameters or decision variables.
Views: 1124 APMonitor.com
Probabilistic Sensitivity Analysis: Analyze a Health Care model
 
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We analyze a simple Health Care model using Probabilistic Sensitivity Analysis techniques. We consider what we can learn about the confidence in our base case analysis and strategy selection.
Views: 7348 TreeAgePro
Sensitivity Analysis and Tornado Plots
 
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Analyzes net present value using sensitivity analysis and generates a tornado plot. Made by faculty at the University of Colorado Boulder Department of Chemical & Biological Engineering. Check out our process design playlist: http://www.youtube.com/playlist?list=PL4xAk5aclnUjEuE_fvbyEts_oBpHYcwLY
Views: 60029 LearnChemE
7.3 Sensitivity Analysis
 
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Sensitivity Analysis
Views: 43473 Dee Amaradasa
Probabilistic Sensitivity Analysis: examine and build a simple Health Care model
 
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Consider how to adapt a simple Health Care model to run Probabilistic Sensitivity Analysis, including incorporating distributions into the model.
Views: 5646 TreeAgePro
Basics of Sensitivity Analysis (Linear Programming_
 
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Sensitivity Analysis - Part 1 The video forms the basis of sensitivity analysis. It covers - Movement of a line on the x-y axis. - Equating the slopes of two lines and representing it on the x-y axis.
Views: 312 Nitesh Sharma
Design Exploration Using the Sensitivity Analysis Tool
 
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Learn more about Simulink Design Optimization: http://goo.gl/X8fhSi Download a free trial of Simulink: https://goo.gl/mEl9ym Analyze the behavior of an electrical circuit used to rectify an AC voltage supply and then amplify it using an op-amp. Use the Sensitivity Analysis tool in Simulink Design Optimization™ to identify which circuit parameters have the greatest impact on characteristics such as the maximum voltage value and waveform smoothness. Sensitivity Analysis Tool Explore design space and determine the most influential model parameters The Sensitivity Analysis tool lets you explore the design space and determine the most influential Simulink® model parameters using design of experiments, Monte Carlo simulations, and correlation analysis. Using this tool, you can: -Select and sample parameters using design of experiments. -Specify design requirements. -Perform Monte Carlo simulations to evaluate the design requirement at selected parameter values. -Analyze and visualize model sensitivity to parameters. -You can accelerate evaluation of design requirements using parallel computing and Simulink fast restart.
Views: 2091 MATLAB
NeuralTools - Testing Sensitivity Analysis
 
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NeuralTools has a new sensitivity feature which trains a number of neural nets to ensure good results and avoiding 'lucky' and 'unlucky' test cases.
Views: 1097 PalisadeCorp
Global Sensitivity Analysis - Saman Razavi
 
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The JRC's Sensitivity Analysis group (SAMO) presents "A New Framework for Comprehensive, Efficient, and Robust Global Sensitivity Analysis", by Saman Razavi, University of Saskatchewan. Seminar at the European Commision Joint Research Centre (JRC) – Ispra – 2 May 2017. This presentation provides an overview of the theory and application of a new framework for Global Sensitivity Analysis (GSA), called Variogram Analysis of Response Surfaces (VARS). VARS utilizes the concepts of variograms and covariograms to characterize a spectrum of sensitivity-related information across the model factor space. VARS is a general framework with explicit theoretical relationships with variance-based (e.g., Sobol) and derivative-based (e.g, Morris) approaches to GSA, while being highly efficient and statistically robust. This presentation also discusses strategies for improved convergence and robustness of GSA, and to this end, introduces a sequential sampling algorithm, called Progressive Latin Hypercube Sampling (PLHS), which allows progressively increasing the sample size, while maintaining the required distributional properties. Saman Razavi received his PhD degree (2013) in civil engineering from the University of Waterloo, Ontario, and his MSc (2004) and BSc (2002) degrees in civil engineering from Amirkabir University and Iran University of Science and Technology in Iran. His research interests include environmental and water resources systems analysis, hydrologic modelling, single and multiple-objective optimization, sensitivity and uncertainty analysis, and climate change and impacts on hydrology and water resources. Seminar organiser: William BECKER Video recording, audio and video editing: Mayeul KAUFFMANN
Views: 1256 mayeulk
Sensitivity Analysis for Financial Modeling | Investopedia Academy
 
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Sensitivity analysis is a way to predict the outcome of a decision given a certain range of variables. Take the Investopedia Academy 'Financial Modeling' course: https://bit.ly/2Gb0k8N INVESTOPEDIA ACADEMY is expert instruction from Investopedia. Self-paced, online courses that provide on-the-job skills—all from the world’s leader in finance and investing education. Website: https://academy.investopedia.com/ Facebook: https://www.facebook.com/investopedia Twitter: https://twitter.com/investopedia
Views: 3830 Investopedia Academy
SimLab v2.2 Sensitivity Analysis
 
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Sensitivity Analysis of Building energy simulation results using SimLab. You can use JEPlus (http://www.jeplus.org/) to get Energy Simulation results for ranges generated by SimLab. SimLab v2.2 can be downloaded from https://ec.europa.eu/jrc/en/samo/simlab
Views: 1028 Aviruch Bhatia
04-2 Sensitivity Analysis Global
 
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Sobol' and regionalized sensitivity analysis
Views: 193 Jef Caers
Sensitivity Analyses and Monte Carlo Simulations with Apogee
 
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This tutorial shows you how to perform Sensitivity Analyses and Monte Carlo simulations using Apogee which is an Excel Add-in that is part of SDI Tools.
Views: 2707 statdesign
ECE320 Lecture3-1a: Sensitivity Analysis
 
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This video will define sensitivity for a feedback control system. It will derive the sensitivity function based upon parameter and block variations. It will also determine the sensitivity of the steady-state error due to a disturbance or sensor noise.
Views: 2434 Rose-Hulman Online
Model Fitting and Regression in MATLAB
 
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Demonstrates how to model a curve and perform regression in Matlab. Made by faculty at the University of Colorado Boulder Department of Chemical and Biological Engineering. Check out our Engineering Computing playlists: https://www.youtube.com/user/LearnChemE/playlists?sort=dd&view=50&shelf_id=4 Are you using a textbook? Check out our website for videos organized by textbook chapters: http://www.learncheme.com/screencasts
Views: 134215 LearnChemE
Global Sensitivity Analysis: Variogram Analysis of Response Surfaces (VARS)
 
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Dr. Saman Razavi speaks about the fundamentals of global sensitivity analysis (GSA) and VARS, which is a new mathematical framework for GSA of computer simulation models, including Earth and Environmental Systems Models (EESMs). VARS, which stands for Variogram Analysis of Response Surfaces, utilizes directional variogram and covariogram functions to characterize the full spectrum of sensitivity-related information, thereby providing a comprehensive set of "global" sensitivity metrics with minimal computational cost. See more on VARS in http://homepage.usask.ca/~ser134/nex_gen_sen_an.php Dr. Saman Razavi leads Watershed Systems Analysis and Modelling Lab at the Global Institute for Water Security. He is an assistant professor with School of Environment and Sustainability and Department of Civil and Geological Engineering at the University of Saskatchewan. He received the PhD degree (2013) in civil engineering from the University of Waterloo, Ontario, and the MSc (2004) and BSc (2002) degrees in civil engineering from Amirkabir University and Iran University of Science and Technology in Iran. Dr. Razavi is an Associate Editor of Journal of Hydrology and an Editorial Board Member of Environmental Modelling & Software. He also serves on several international committees. His research interests include environmental and water resources systems analysis, hydrologic modelling, single- and multiple-objective optimization, sensitivity and uncertainty analysis, and climate change and impacts on hydrology and water resources. http://homepage.usask.ca/~ser134/ ________________________________________________________ What is Global Sensitivity Analysis (GSA)? Global sensitivity analysis is a systems theoretic approach to characterizing the overall (average) sensitivity of one or more model responses across the factor space, by attributing the variability of those responses to different controlling (but uncertain) factors (e.g., model parameters, forcings, and boundary and initial conditions). ________________________________________________________ What was the Motivation for the Development of VARS? VARS was developed to address two major issues with GSA: · Ambiguous Definition of "Global" Sensitivity: different GSA methods are based in different philosophies and theoretical definitions of sensitivity, leading to different, even conflicting, assessments of the underlying sensitivities for a given problem. · Computational Cost: the cost of carrying out GSA can be large, even excessive, for high-dimensional problems and/or computationally intensive models, where cost (or "efficiency") is commonly assessed by of the number of required model runs. ________________________________________________________ What are the Special Features of VARS? · VARS re-defines GSA by characterizing a comprehensive spectrum of information about the underlying sensitivities of a response surface to its factors, while reducing to well-known and commonly used approaches to GSA as special/limiting cases. · VARS generates a new set of sensitivity metrics called IVARS (Integrated Variogram Across a Range of Scales) that summarize the variance of change (rate of variability) in model response at a range of perturbation scales in the factor space. · VARS also generates the Sobol (variance-based) total-order effect, the most popular metric for GSA, and the Morris (derivative-based) elementary effects across the full range of step sizes in numerical differencing (theoretical relationship exists). · VARS is highly efficient and statistically robust, providing stable results within 1-2 orders of magnitude smaller numbers of sampled points (model runs), compared with alternative GSA approaches, such as the Sobol and Morris approaches. · VARS effectively and efficiently handles high-dimensional problems, because of its computational efficiency, which is, in part, due to VARS being based on the information contained in pairs of points, rather than in individual points. · VARS is unique in that it characterizes different sensitivity-related properties of response surfaces including local sensitivities and their global distribution, the global distribution of model responses, and the structure of the response surface. · VARS tackles the scale issue of sensitivity analysis by providing sensitivity information spanning a range of scales across the factor space, from small-scale features such as roughness/noise to large-scale features such as multimodality.
Views: 1392 usaskgiws
Monte Carlo Simulation using Matlab - Uniformedia Matlab Tutorial
 
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Monte Carlo Simulation using Matlab. Monte Carlo simulation is a method for exploring the sensitivity of a complex system by varying parameters within statistical constraints. These systems can include financial, physical, and mathematical models that are simulated in a loop, with statistical uncertainty between simulations. The results from the simulation are analyzed to determine the characteristics of the system. Common tasks for performing Monte Carlo analysis include: Varying uncertain parameters for your model Creating dynamic simulations and alter parameters with statistical uncertainty Creating a Monte Carlo simulation to model a complex dynamic system Distributing simulations between processor cores and individual PCs to speed analysis Analyzing data through robust plotting and advanced statistical methods Monte Carlo simulation, or probability simulation, is a technique used to understand the impact of risk and uncertainty in financial, project management, cost, and other forecasting models.
Views: 5655 Uniformedia
How to run Sobol sensitivity analysis using MOEAFramework
 
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This video shows how you can use MOEAFramework to run Sobol sensitivity analysis, which is a valuable diagnostic tool for scientific models. For more information, visit http://waterprogramming.wordpress.com.
Views: 942 PatReedResearch
PRMS Parameter Sensitivity
 
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Parameter sensitivity analysis of USGS Precipitation Runoff Modeling System (PRMS) using the Fourier Amplitude Sensitivity Test algorithm.
Views: 822 USGS
Monte Carlo Simulation in Matlab
 
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This is a slide-based introduction to techniques for doing Monte Carlo simulation in Matlab. It comes from a course I teach as part of an online Masters degree program in engineering (http://mepp.engr.wisc.edu/). Higher res versions of this video can be found at http://blanchard.ep.wisc.edu
Views: 195895 Jake Blanchard
HOMER Renewable Energy Software Training - Sensitivity Analysis
 
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HOMER is the global standard in microgrid software, based on decades of listening to the needs of users around the world with experience in designing and deploying microgrids and distributed power systems that can include a combination of renewable power sources, storage, and fossil-based generation (either through a local generator or a power grid). This video covers the sensitivity analysis feature of a simulation, which is critical in understanding the robustness of a design.
Views: 4028 HOMER Energy
Analysis Option 3: Sensitivity Analysis
 
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Screen capture of DSS using sensitivity analysis to calculate most sensitive variable.
Views: 59 Sophie Kay
Prediction Artificial Neural Network (ANN) using Matlab - nntool
 
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Prediction Artificial Neural Network (ANN) using Matlab - nntool
Views: 10359 samet uslu
Sensitivity analysis using SimLab and jEPlus
 
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This demo shows how to performance sensitivity analysis using SimLab 2.2 and jEPlus. An example project included in jEPlus v1.6's distribution package is used in this walk-through. (This video has no sound)
Views: 3678 jEPlusMedia
Part 1: Monte Carlo Simulations in MATLAB (Tutorial)
 
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In this video I explain what a Monte Carlo Simulation is and the uses of them and I go through how to write a simple simulation using MATLAB. Code on my GitHub: https://github.com/jamesldalton/Monte-Carlo (Example) What is the probability of a hand of 5 cards drawn from a fair deck of 52 cards being all hearts?
Views: 23673 James Dalton
OptiY-Interface to Matlab/Simulink
 
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OptiY® is an open and multidisciplinary design environment providing most modern optimization strategies and state of the art probabilistic algorithms for uncertainty, reliability, robustness, sensitivity analysis, fatigue life prediction, data-mining and meta-modeling. The simulation model can be considered as black box with inputs and outputs. Within, it is an open platform for different kind of model classes. The adaptation to a special simulation environment takes place by a suitable interface. Collaborating different simulation systems is possible as networks, finite-element-method, rigid body dynamics, also material test bench as control optimization for drives.
Views: 540 OptiY
Gain a better understanding of Root Locus Plots using Matlab
 
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I'm writing a book on the fundamentals of control theory! Get the book-in-progress with any contribution for my work on Patreon - https://www.patreon.com/briandouglas In this video I go through various ways to use Matlab to plot and visualize the root locus? Errata: None yet that I know of! Links to other Matlab demos and tutorials: Getting started with the SISO design Tool: http://www.mathworks.com/help/control/examples/getting-started-with-the-siso-design-tool.html?prodcode=CT&language=en Control System Design with Control System Tuning App: http://www.mathworks.com/videos/control-system-design-with-control-system-tuning-app-68749.html Using Bode Plots with DC motor control example: http://www.mathworks.com/videos/using-bode-plots-dc-motor-control-example-5-of-5-77062.html Nonlinear Plant Control at Different Operating Points: http://www.mathworks.com/videos/nonlinear-plant-control-at-different-operating-points-68747.html Don't forget to subscribe! I'm on Twitter @BrianBDouglas! If you have any questions on it leave them in the comment section below or on Twitter and I'll try my best to answer them. I will be loading a new video whenever I can and welcome suggestions for new topics. Please leave a comment or question below and I will do my best to address it. Thanks for watching!
Views: 80036 Brian Douglas
Parameter Sensitivity Analysis in GastroPlus™
 
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This video describes how to set up a parameter sensitivity analysis (PSA) in GastroPlus. This allows researchers to determine the effect of an input parameter, e.g., solubility, on a pharmacokinetic property like fraction absorbed. The tasks in Tutorial 5.3.7 will be illustrated.
Samo 2016 : Sobol' sensitivity analysis, Iooss BERTRAND
 
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Sobol' sensitivity analysis for stochastic numerical codes, Iooss Bertrand
Sensitivity Analysis
 
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Views: 785 Build Sci
Aspen Plus V8.0 Tutorial - Sensitivity Analysis
 
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Flow sheeting + Sensitivity Analysis
Views: 42359 Merten Morales
Will Usher: Using the SALib library for conducting sensitivity analyses of models
 
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Sensitivity analysis should be a central part of the model development process, yet software to actually perform the best-practice approaches are seldom available. In this talk, there is justification for the importance of sensitivity analysis, step-by-step examples of how to use SALib and an outline of the advantages. Full details — http://london.pydata.org/schedule/presentation/45/
Views: 1251 PyData
4.8  TNA Step 1: Sensitivity Analysis
 
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Identification and Prioritization of Technologies: Results
Random Sampling - Tutorial 4 - Latin Hypercube Sampling
 
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Please check out www.sphackswithiman.com for more tutorials.
Views: 9568 iman

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