3-Computer Science-System Analysis-Model

model

Ordered sets {model, system} {software model}, of various elements, can represent object or process properties. Models simulate positions, motions, times, momenta, energies, and interactions. Models can be physical or mathematical but have actual physical actions. Model elements have or represent points, lines, angles, surfaces, and/or solids, so models have geometric relations. Typically, model shapes are similar to physical shapes. Model and physical metrics are proportional. Model motions represent physical motions. Typically, model motions are similar to physical motions. Function models have moving parts that change positions and motions to represent events and transfers among states.

purposes

Constructing models can find what is important and not important, sharpen definitions and categories, identify procedure steps, identify structure parts, test interactions, sharpen boundaries, make categories, and uncover new relations, meanings, and properties. Constructing models adds information that causes understanding.

Models can represent system views. Models try to include constancies in real system and relations among elements. Models can simulate one description level or one input/output signal class. Models can measure information flows and constraints. Models can test knowledge or predictions and can reveal new object or process knowledge.

symbol grounding

Models can have parts and functions that relate to physical parts and functions {symbol grounding, model}.

black box

Systems {black box}| can have only inputs and outputs, with no process explanation.

computation theory

Models {computation theory} must specify what to compute.

formal model

Models {formal model} can put relations and components into symbols. Solutions come from mathematical analysis.

scale model

Models {scale model}| {replica} can copy larger-object shapes.

simulation on computer

Models {simulation, computer} can put relations and components into symbols. Computers find iterated or statistical solutions [Pellionisz and Llinas, 1982].

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Date Modified: 2022.0225