Glossary of Key Terms
Glossary of Key Terms
| Term | Definition |
| ADALINE / MADALINE | Models developed in 1959 by Bernard Widrow and Marcian Hoff. They are based on Multiple ADAptive LINear Elements, and MADALINE was the first neural network applied to a real-world problem. |
| Attributes | The local values used by an entity. |
| Base Model | A hypothetical explanation of an object’s properties and its behavior, which is valid across the model. |
| Continuous System | A system in which the state variables change continuously as a function of time. Important activities complete smoothly without any delay or queuing. |
| Decision Variables | Input variables that are controlled by the programmer during a simulation process. |
| Delay | An indefinite duration that is caused by some combination of system conditions. |
| Deterministic Systems | Systems that are not affected by randomness, and their output is not a random variable. |
| Discrete System | A system where the state variable changes only at discrete points in time. |
| Discrete-Event Simulation | A type of simulation where the model’s state variable values change only at some discrete points in time where events occur. |
| Dynamic Simulation | Includes models that are affected by time. |
| Entities | A representation of an object whose value can be static or dynamic. In discrete event simulation, they represent real elements like parts of machines. |
| Event | Each discontinuous change in the state of a discrete system. |
| Experimental Frame | A framework used to study a system in the real world, including experimental conditions, aspects, and objectives. It consists of Frame Input and Frame Output Variables. |
| Face Validity | A validation principle stating that if a model performs on opposite logics, it should be rejected even if it behaves like the real system. |
| Fuzzy Set | A set where elements have a degree of membership, defined by a function μA(x). It is used to handle uncertainty in estimates for unknown parameters. |
| Internal Validity | A validation concept where a model with a high degree of internal variance will be rejected because its internal randomness may hide changes in output caused by input changes. |
| Lists | Used to represent the queues used by entities and resources in a simulation. |
| Lumped Model | An exact explanation of a system which follows the specified conditions of a given Experimental Frame. |
| Modelling | The process of representing a model, including its construction and working. It is an act of building a model that represents a system and its properties. |
| Monte Carlo Simulation | A computerized mathematical technique to generate random sample data based on a known distribution for numerical experiments, often used for risk analysis and decision-making. |
| Neural Network | A branch of artificial intelligence consisting of a network of many processors (units) connected by unidirectional communication channels. |
| Object | An entity which exists in the real world to study the behavior of a model. |
| Queue | The combination of all entities in a system being served and those waiting for their turn. |
| Resources | An entity that provides service to one or more dynamic entities at a time. |
| Sensitivity Analysis | A validation technique that provides information about the sensitive parameters in a system, observing the effect of changes in input data on the results. |
| Simulation | The operation of a model in terms of time or space, which helps analyze the performance of an existing or a proposed system. It is the act of using a model. |
| Simulation Executive | A key feature of discrete event simulation responsible for controlling the advance of time and executing discrete events. |
| State Descriptor | A set of numbers used in a discrete system simulation model to represent the state of the system. |
| Static Simulation | Includes models which are not affected by time, such as a Monte Carlo Model. |
| Stochastic Systems | Systems that are affected by randomness, and their output is a random variable. |
| Subsystem Validity | A validation technique where a model, which may not have an existing system to compare with, is validated by testing its known subsystems separately. |
| System | The articulate object under definite conditions, which exists in the real world. |
| System State Variables | A set of data required to define the internal process within the system at a given point of time. |
| Time-Sharing System | A system designed so that each user uses a small portion of shared time, allowing multiple users to share the system simultaneously. |
| Turing Test | A method of comparison used in validation where data is presented in the system format, which can be explained and compared by experts. |
| Uncontrollable Variables | Random variables that are an input to a simulation but cannot be controlled by the programmer. |
| Validation | The process of comparing two results, specifically a conceptual model’s representation to the real system, to ensure the model is an accurate representation. |
| Verification | The process of comparing two or more items to ensure accuracy, specifically comparing a model’s implementation and data with the developer’s conceptual description and specifications. |