What is the difference between a neural network, fuzzy logic, and ...

[james]

What is the difference between a neural network, fuzzy logic, and genetic algorithms? Which would be of most use to an organization of astronomers analyzing gamma ray emissions reaching Earth?
 
  What will be an ideal response?

Question 2

DBMS simplify how end users work with databases by separating the logical and physical views of the data.
 
  Indicate whether the statement is true or false

[Kjones0604]

Answer to Question 1

A neural network attempts to emulate the processing patterns of the biological brain. It results in a program that can learn by comparing solutions to known problems to sets of data presented to it. Neural networks are used for solving complex, poorly understood problems for which large amounts of data have been collected. Fuzzy logic creates rules that use approximate or subjective values. It describes a particular phenomenon or process linguistically and then represents that logic in a small number of flexible rules. Genetic algorithms are problem-solving methods that use the model of living organisms adapting to their environment. Possible solutions are evaluated, the best choices are made, then more possible solutions are created by combining the factors involved in those first best choices, and choosing again. The process continues until an optimum solution is reached. These genetic algorithms are useful for finding the optimal solution for a specific problem by examining a very large number of alternative solutions for that problem.
Student evaluations will vary. A sample answer is: I think a neural network would be of most use because of information technology's ability to analyze large amounts of data and find hidden relationships.

Answer to Question 2

TRUE