DISCRETE MODELS
GROUP 3
Submitted by:
Leader: Ian Sagaral
Members:
Meriza C. Malinao
Holemaie Nepalar
Keneth Pormento
Rico Jay Queňonez
INTRODUCTION
Discrete models are mathematical models used to study a system with discrete
components. They are used to analyze the behavior of a system over time, and
can be used to predict future behavior. Discrete models are used in a variety of
fields, such as computer science, engineering, economics, and finance. Discrete
models are often used to simulate processes, and can provide valuable insights
into the behavior of a system. They can also be used to optimize processes, and
to identify potential problems.
What is Discrete Models?
Discrete models are mathematical models that can be used to describe a system
that changes over time. These models are composed of a set of equations that
describe the relationship between different variables within the system. Discrete
models are often used to analyze the behavior of systems with a finite number of
states, such as a computer program or a machine. They are also used to analyze
the behavior of systems with a finite number of events, such as a stock market.
Advantages of Discrete Models
Discrete models are incredibly useful and advantageous in many areas of
research and development. They allow us to accurately model complex
systems and processes in a simplified way, making them easier to understand
and analyze. Discrete models also enable us to make predictions about future
outcomes based on current conditions, allowing us to plan accordingly.
Furthermore, discrete models are cost effective and require less computing
power than many other modeling methods. As a result, they are becoming
increasingly popular in many fields.
Importance of Discrete Models
Discrete models are an important tool in mathematics and computer science.
They provide a way to represent and analyze complex problems in a simplified
form. Discrete models can be used to model a variety of systems, from physical
and biological systems to financial and economic systems. They can also be used
to develop algorithms for solving problems, which can be applied to a wide range
of applications.
Examples of Discrete Models
Cellular Automaton: Cellular automaton is a discrete model that consists of a
grid of cells, each of which can be in different states. The cells evolve over time
based on a set of rules. One well-known cellular automaton is Conway's Game
of Life, which follows simple rules to determine the state of each cell in the next
generation.
Finite State Machine: is a computation model that can be used to simulate
sequential logic, or, in other words, to represent and control execution flow.
Finite State Machines can be used to model problems in many fields,
including mathematics, artificial intelligence, games or linguistics.
Decision Tree: are a powerful tool for making decisions and predictions.
They are particularly useful when dealing with complex data sets, as they
allow for the efficient evaluation of multiple scenarios. One way of making
decision trees even more effective is through the use of discrete models.
Discrete models allow for the use of discrete variables, such as binary
values, in the decision tree.
CONCLUSION
Discrete Models are incredibly useful for understanding and predicting the
behavior of complex systems. They allow us to break down a system into its
individual components and analyze each of them separately. This allows us to
gain insight on how the different parts interact and how they can be
manipulated to achieve the desired outcome. Discrete models are a powerful
tool that can be used to identify patterns and trends in data, and they can be
used to develop effective solutions to difficult problems.
