Search results
Results from the WOW.Com Content Network
Continuous dynamic systems can only be captured by a continuous simulation model, while discrete dynamic systems can be captured either in a more abstract manner by a continuous simulation model (like the Lotka-Volterra equations for modeling a predator-prey eco-system) or in a more realistic manner by a discrete event simulation model (in a ...
Continuous modelling is the mathematical practice of applying a model to continuous data (data which has a potentially infinite number, and divisibility, of attributes). They often use differential equations [1] and are converse to discrete modelling. Modelling is generally broken down into several steps:
A comparison between discrete rate, continuous, and discrete event simulation. Discrete rate simulation is similar to discrete event simulation in that both methodologies model the operation of the system as a discrete sequence of events in time. However, while discrete event simulation assumes there is no change in the system between ...
Discrete vs. continuous. A discrete model treats objects as discrete, such as the particles in a molecular model or the states in a statistical model; while a continuous model represents the objects in a continuous manner, such as the velocity field of fluid in pipe flows, temperatures and stresses in a solid, and electric field that applies ...
Dichotomization is the special case of discretization in which the number of discrete classes is 2, which can approximate a continuous variable as a binary variable (creating a dichotomy for modeling purposes, as in binary classification). Discretization is also related to discrete mathematics, and is an important component of granular computing.
Mechanisms for discretizing continuous data include Fayyad & Irani's MDL method, [2] which uses mutual information to recursively define the best bins, CAIM, CACC, Ameva, and many others [3] Many machine learning algorithms are known to produce better models by discretizing continuous attributes.
[9] [10] [11] These models help in the development of reliable disaster managing plans and safer design for the built environment. Energy forecasters and policymakers use discrete choice models for households' and firms' choice of heating system, appliance efficiency levels, and fuel efficiency level of vehicles. [12] [13]
A discrete-event simulation (DES) models the operation of a system as a sequence of events in time. Each event occurs at a particular instant in time and marks a change of state in the system. [ 1 ] Between consecutive events, no change in the system is assumed to occur; thus the simulation time can directly jump to the occurrence time of the ...