The document discusses algorithms as step-by-step problem-solving procedures, emphasizing their usefulness in simplifying complex problems. It also highlights various applications of algorithms in daily life, programming, and natural processes such as genetic algorithms, and touches on the future of algorithms in fields like artificial intelligence and machine learning. The authors, students from Daffodil International University, submitted this document on February 19, 2018.

1. Application of algorithm in
1

2. Daffodil International University
 Submitted By
 N H M Ahsanul gani Faysal (171-35-220)
 Niloy Biswas (171-35-225)
 Tanvir islam (171-35-239)
 Mahmudul Islam (171-35-218)
 Submitted to
 Mr. Sayed Asaduzzaman
Lecturer,
Department of SWE
Daffodil International University
Date of submission
February 19, 2018
2

3. What is an algorithm
 An algorithm is a step by step problem solving procedure.
 Informally, an algorithm is any well-defined countable procedure that
takes some value, or set of values, as input and produces some value,
or set of values, as output.
 An algorithm is thus a sequence of countable steps that transform
the input into the output.
3

4. Why we use algorithm
4
Basically, algorithm is a process to solve a problem in step by step. When we face a
problem in our real life , we are try to solve this problem in our own ideas. When we see
a problem then we feel anxious / depressed . We don’t know how to solve this problem.
Then we try to solve this problem randomly and that time it’s turn into more difficult then
the previous one . But when we will try to solve this problem step by step , it will be
easier to solve those problem.
In that reason , we use algorithm to solve a problem by easier way and free from any
difficulty. It will saves our valuable time , money , etc.

5. Usefulness of algorithm
 An algorithm can be roughly described as a sequence of steps that have to be executed
(mechanically, manually, whatever). So it's about repeating more or less the same thing
several times, applying it do different but similar problems.
 So why are algorithms working in this setting, for different problems? The deeper reason
why we use algorithms is because our environment is stable and to some degree
predictable
5

6. Algorithm in our life
 Your Life is an Algorithm, Your Brain is an Operating System.
-By DOMINIC BASULTO
 What algorithms do you use in every daily life?
6

7. Algorithm to add two number
7

8. Algorithm in games
8
Rubik's cube:
In Rubik's cube we have millions of
procedure to solve it. Each and every
procedure is an algorithm.

9. genetic algorithm
9
A genetic algorithm is a search heuristic that is inspired by
Charles Darwin’s theory of natural evolution. This algorithm
reflects the process of natural selection where the fittest
individuals are selected for reproduction in order to produce
offspring of the next generation.
 The three main rules of genetic algorithms are given below:
1. Natural selection
2. Crossover
3. Mutation

10. Algorithm in programming
10
 A programming algorithm is a computer
procedure that is a lot like a recipe (called
a procedure) and tells your computer
precisely what steps to take to solve a
problem or reach a goal. The ingredients
are called inputs, while the results are
called the outputs

11. Search Algorithm
11
 A search algorithm is the step-by-
step procedure used to locate
specific data among a collection of
data. In computer science, when
searching for data, the difference
between a fast application and a
slower one often lies in the use of
the proper search algorithm.

12. Sorting
12
 We all have
smartphone, right.
There has one or two
SIM slot. In this SIM
storage we save a lot
of numbers by name.
Customer contact list

13. Fibonacci Series
13
 The Fibonacci numbers are Nature's
numbering system.
They appear everywhere in Nature,
from the leaf arrangement in plants,
to the pattern of the bloom of a
flower, the bracts of a pinecone, or
the scales of a pineapple.

14. Future of algorithm
14
1. Artificial Intelligence
2. Big Data
3. Machine Learning
4. Robotics
5. Deep Learning

15. Thank you
15