2.2.2 Computational methods Flashcards

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1
Q

What is meant by a computable problem?

A

A problem that can be solved using an algorithm

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2
Q

Give three limiting factors to computable problems

A
  • Processing power
  • Computer memory
  • Time
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3
Q

What are tractable problems?

A

Problems that are considered to be computable // can be solved using computational methods

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4
Q

Decomposition

A
  • Breaking a complex problem into manageable sub-problems
  • The lowest sub problems can be coded as a procedure, module, function or method
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5
Q

Abstraction

A

Removing unnecessary features and keeping the necessary features that are important in context

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6
Q

Enumeration

A

Method that involves designing an algorithm that performs an exhaustive search and attempts possible solutions until the correct one is found

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7
Q

Simulation

A
  • Process of designing a model of a real system to understand its behaviour
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8
Q

Automation

A

Building problem solving models and putting them into action

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9
Q

Theoretical approach

A
  • Problem is represented using mathematical equations
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10
Q

What is problem recognition?

A
  • The ability to recognise and acknowledge that an issue exists or that a situation needs attention in an existing process or program
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11
Q

Divide and conquer

A

A technique that reduces the size of a problem with each successive iteration

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12
Q

Divide and conquer steps (4)

A
  • Take a problem/data set
  • Apply some rules
  • Based on the outcome of those rules, discard any data that doesn’t match
  • Repeat the process with the data that is left
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13
Q

Backtracking

A

The process of incrementally building towards a solution, abandoning partial success when the solution cannot be completed and going back to a previously successful match

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14
Q

Data mining

A

The concept of analysing vast amounts of data gathered from a variety of sources to discover new information and trends

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15
Q

Practical applications of data mining

A
  • Business and economics
  • Science and engineering
  • Law enforcement
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16
Q

Heuristics

A

An approach to solving problems that allows/encourages us to make use of our experience and find a solution that can be considered good enough

17
Q

Performance modelling

A

The process of approximating how well models perform using mathematics

18
Q

Pipelining

A

Splitting up a large task into manageable chunks and overlapping these smaller processes to speed up the overall process

19
Q

Visualisation

A

Creating a mental image of what a program will do or how it will work

20
Q

What are the advantages of using a visualisation?

A
  • Presents info in a simpler form to understand
  • Can best explain complex situations
21
Q

Characteristics of a problem that are needed to be solved using computational methods

A
  • Problems to be clearly defined
  • Needs to be computable
  • Data requirements