This document provides a running log of changes made in the various public and beta releases of JSim 2.0 as well as pending changes to upcoming releases. Most recent changes are listed first.

Introduction

There is no perfect optimization algorithm that is best for all problems. Optimization algorithms vary in their approach, efficiency, robustness and applicability to particular problem domains. This document describes the optimization algorithms currently supported by JSim in some detail so users can make intelligent use of them. JSim's currently available optimizers are listed below. Other algorithms are in development.

Prerequisites:

• Introduction to the JSim Optimizer

Contents:

Introduction

JSim allows users to create arbitrarily large models, which can tax a computer's memory and cause various problems. There are two methods for dealing with these problems - either by increasing the total memory available to JSim or by reducing the memory needed during a model run via every Nth point storage. This document provides information about these two approaches.

Prerequisites:

• Introduction to the JSim GUI (required)

Contents:

Introduction

This document describes how to generate functional images using the jsfim command line tool.

Prerequisites:

Preface

JSim's model parameter optimizers are automated tools for finding model parameter values which cause model output to best match fixed reference data. This document provides step-by-step instruction for operating the optimizers.

Prerequisites:

• Introduction to the JSim GUI (required)
• Data Files and Project Data Sets (required)
• JSim Projects (recommended)

Contents:

What does the condition number on the optimization report mean?

Notation: Let the observed data be given as:                                        

hence (nh-nx) represents the degrees of freedom.

The n x n correlation matrix is given by

The JSim "Loops" feature allows users to observe the effects of changing model parameter values.

Prerequisites:

• Introduction to the JSim GUI

Contents:

Introduction

JSim parameter sets are collections of values given to parameters at run-time. Parameters, in JSim parlance, include model input variables and control settings for numeric solvers, function generators, loops, sensitivity analysis and optimization. Each model in a project has a "current parameter set" which is used when the model is run. In addition, the user may create one or more alternative parameter sets that are stored in separate tabs on the left hand side of the JSim GUI.

Preface

Prerequisites:

• Introduction to the JSim GUI (required)
• Using Loops in JSim (required)
• Data Files & Project Data Sets (recommended)

Contents:

Preface

JSim Monte Carlo analysis provides a mechanism for analyzing parameter confidence limits through statistical analysis of multiple optimizations on noisy data sets.

Monte Carlo analysis is available in JSim releases 2.06 and above. This functionality is supported in applets and other remote server applications in JSim releases 2.07 and above.

Prerequisites: