SMU SOLVED ASSIGNMENTS, SMU BSCIT FALL 2014 ASSIGNMENTS, SMU MBA ASSIGNMENTS, SMU ASSIGNMENTS, SMU FALL DRIVE ASSIGNMENTS, SMU BSCIT SEM 2 FALL 2014 ASSIGNMENTS
Design & Analysis of Algorithms Lecture NotesFellowBuddy.com
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SMU SOLVED ASSIGNMENTS, SMU BSCIT FALL 2014 ASSIGNMENTS, SMU MBA ASSIGNMENTS, SMU ASSIGNMENTS, SMU FALL DRIVE ASSIGNMENTS, SMU BSCIT SEM 2 FALL 2014 ASSIGNMENTS
Design & Analysis of Algorithms Lecture NotesFellowBuddy.com
FellowBuddy.com is an innovative platform that brings students together to share notes, exam papers, study guides, project reports and presentation for upcoming exams.
We connect Students who have an understanding of course material with Students who need help.
Benefits:-
# Students can catch up on notes they missed because of an absence.
# Underachievers can find peer developed notes that break down lecture and study material in a way that they can understand
# Students can earn better grades, save time and study effectively
Our Vision & Mission – Simplifying Students Life
Our Belief – “The great breakthrough in your life comes when you realize it, that you can learn anything you need to learn; to accomplish any goal that you have set for yourself. This means there are no limits on what you can be, have or do.”
Like Us - https://www.facebook.com/FellowBuddycom
Introduction to Dynamic Programming, Principle of OptimalityBhavin Darji
Introduction
Dynamic Programming
How Dynamic Programming reduces computation
Steps in Dynamic Programming
Dynamic Programming Properties
Principle of Optimality
Problem solving using Dynamic Programming
What Is Dynamic Programming? | Dynamic Programming Explained | Programming Fo...Simplilearn
This presentation on 'What Is Dynamic Programming?' will acquaint you with a clear understanding of how this programming paradigm works with the help of a real-life example. In this Dynamic Programming Tutorial, you will understand why recursion is not compatible and how you can solve the problems involved in recursion using DP. Finally, we will cover the dynamic programming implementation of the Fibonacci series program. So, let's get started!
The topics covered in this presentation are:
1. Introduction
2. Real-Life Example of Dynamic Programming
3. Introduction to Dynamic Programming
4. Dynamic Programming Interpretation of Fibonacci Series Program
5. How Does Dynamic Programming Work?
What Is Dynamic Programming?
In computer science, something is said to be efficient if it is quick and uses minimal memory. By storing the solutions to subproblems, we can quickly look them up if the same problem arises again. Because there is no need to recompute the solution, this saves a significant amount of calculation time. But hold on! Efficiency comprises both time and space difficulty. But, why does it matter if we reduce the time required to solve the problem only to increase the space required? This is why it is critical to realize that the ultimate goal of Dynamic Programming is to obtain considerably quicker calculation time at the price of a minor increase in space utilized. Dynamic programming is defined as an algorithmic paradigm that solves a given complex problem by breaking it into several sub-problems and storing the results of those sub-problems to avoid the computation of the same sub-problem over and over again.
What is Programming?
Programming is an act of designing, developing, deploying an executlable software solution to the given user-defined problem.
Programming involves the following stages.
- Problem Statement
- Algorithms and Flowcharts
- Coding the program
- Debug the program.
- Documention
- Maintainence
Simplilearn’s Python Training Course is an all-inclusive program that will introduce you to the Python development language and expose you to the essentials of object-oriented programming, web development with Django and game development. Python has surpassed Java as the top language used to introduce U.S.
Learn more at: https://www.simplilearn.com/mobile-and-software-development/python-development-training
A NEW ALGORITHM FOR SOLVING FULLY FUZZY BI-LEVEL QUADRATIC PROGRAMMING PROBLEMSorajjournal
This paper is concerned with new method to find the fuzzy optimal solution of fully fuzzy bi-level non-linear (quadratic) programming (FFBLQP) problems where all the coefficients and decision variables of both objective functions and the constraints are triangular fuzzy numbers (TFNs). A new method is based on decomposed the given problem into bi-level problem with three crisp quadratic objective functions and bounded variables constraints. In order to often a fuzzy optimal solution of the FFBLQP problems, the concept of tolerance membership function is used to develop a fuzzy max-min decision model for generating satisfactory fuzzy solution for FFBLQP problems in which the upper-level decision maker (ULDM) specifies his/her objective functions and decisions with possible tolerances which are described by membership functions of fuzzy set theory. Then, the lower-level decision maker (LLDM) uses this preference information for ULDM and solves his/her problem subject to the ULDMs restrictions. Finally, the decomposed method is illustrated by numerical example.
What is Relational model
Characteristics
Relational constraints
Representation of schemas
characteristics and Constraints of Relational model with proper examples.
Updates and dealing with constraint violations in Relational model
This should give you an idea about how to operate the software. And use it to solve Ordinary Differential Equations. I will be using foggler's book for the examples that have code given with it.
Dynamic Programming is a method for solving a complex problem by breaking it down into a collection of simpler subproblems, solving each of those subproblems just once, and storing their solutions using a memory-based data structure (array, map,etc).
TYPE-2 FUZZY LINEAR PROGRAMMING PROBLEMS WITH PERFECTLY NORMAL INTERVAL TYPE-...ijceronline
In this paper, the Perfectly normal Interval Type-2 Fuzzy Linear Programming (PnIT2FLP) model is considered. This model is reduced to crisp linear programming model. This transformation is performed by a proposed ranking method. Based on the proposed fuzzy ranking method and arithmetic operation, the solution of Perfectly normal Interval Type-2 Fuzzy Linear Programming model is obtained by the solutions of linear programming model with help of MATLAB. Finally, the method is illustrated by numerical examples.
Introduction to Dynamic Programming, Principle of OptimalityBhavin Darji
Introduction
Dynamic Programming
How Dynamic Programming reduces computation
Steps in Dynamic Programming
Dynamic Programming Properties
Principle of Optimality
Problem solving using Dynamic Programming
What Is Dynamic Programming? | Dynamic Programming Explained | Programming Fo...Simplilearn
This presentation on 'What Is Dynamic Programming?' will acquaint you with a clear understanding of how this programming paradigm works with the help of a real-life example. In this Dynamic Programming Tutorial, you will understand why recursion is not compatible and how you can solve the problems involved in recursion using DP. Finally, we will cover the dynamic programming implementation of the Fibonacci series program. So, let's get started!
The topics covered in this presentation are:
1. Introduction
2. Real-Life Example of Dynamic Programming
3. Introduction to Dynamic Programming
4. Dynamic Programming Interpretation of Fibonacci Series Program
5. How Does Dynamic Programming Work?
What Is Dynamic Programming?
In computer science, something is said to be efficient if it is quick and uses minimal memory. By storing the solutions to subproblems, we can quickly look them up if the same problem arises again. Because there is no need to recompute the solution, this saves a significant amount of calculation time. But hold on! Efficiency comprises both time and space difficulty. But, why does it matter if we reduce the time required to solve the problem only to increase the space required? This is why it is critical to realize that the ultimate goal of Dynamic Programming is to obtain considerably quicker calculation time at the price of a minor increase in space utilized. Dynamic programming is defined as an algorithmic paradigm that solves a given complex problem by breaking it into several sub-problems and storing the results of those sub-problems to avoid the computation of the same sub-problem over and over again.
What is Programming?
Programming is an act of designing, developing, deploying an executlable software solution to the given user-defined problem.
Programming involves the following stages.
- Problem Statement
- Algorithms and Flowcharts
- Coding the program
- Debug the program.
- Documention
- Maintainence
Simplilearn’s Python Training Course is an all-inclusive program that will introduce you to the Python development language and expose you to the essentials of object-oriented programming, web development with Django and game development. Python has surpassed Java as the top language used to introduce U.S.
Learn more at: https://www.simplilearn.com/mobile-and-software-development/python-development-training
A NEW ALGORITHM FOR SOLVING FULLY FUZZY BI-LEVEL QUADRATIC PROGRAMMING PROBLEMSorajjournal
This paper is concerned with new method to find the fuzzy optimal solution of fully fuzzy bi-level non-linear (quadratic) programming (FFBLQP) problems where all the coefficients and decision variables of both objective functions and the constraints are triangular fuzzy numbers (TFNs). A new method is based on decomposed the given problem into bi-level problem with three crisp quadratic objective functions and bounded variables constraints. In order to often a fuzzy optimal solution of the FFBLQP problems, the concept of tolerance membership function is used to develop a fuzzy max-min decision model for generating satisfactory fuzzy solution for FFBLQP problems in which the upper-level decision maker (ULDM) specifies his/her objective functions and decisions with possible tolerances which are described by membership functions of fuzzy set theory. Then, the lower-level decision maker (LLDM) uses this preference information for ULDM and solves his/her problem subject to the ULDMs restrictions. Finally, the decomposed method is illustrated by numerical example.
What is Relational model
Characteristics
Relational constraints
Representation of schemas
characteristics and Constraints of Relational model with proper examples.
Updates and dealing with constraint violations in Relational model
This should give you an idea about how to operate the software. And use it to solve Ordinary Differential Equations. I will be using foggler's book for the examples that have code given with it.
Dynamic Programming is a method for solving a complex problem by breaking it down into a collection of simpler subproblems, solving each of those subproblems just once, and storing their solutions using a memory-based data structure (array, map,etc).
TYPE-2 FUZZY LINEAR PROGRAMMING PROBLEMS WITH PERFECTLY NORMAL INTERVAL TYPE-...ijceronline
In this paper, the Perfectly normal Interval Type-2 Fuzzy Linear Programming (PnIT2FLP) model is considered. This model is reduced to crisp linear programming model. This transformation is performed by a proposed ranking method. Based on the proposed fuzzy ranking method and arithmetic operation, the solution of Perfectly normal Interval Type-2 Fuzzy Linear Programming model is obtained by the solutions of linear programming model with help of MATLAB. Finally, the method is illustrated by numerical examples.
1. Civil Engineering
Skills
Computer
Programming
CIV1900
Dr Sam Clarke
Control of Program Flow
2. What is Program flow?
Learning outcomes & Aims
◦ What program flow is
◦ Why it may be useful to control the
flow
◦ How to control program flow using
sequential logic
“Making Decisions”
4. Program Flow – simple algorithm
Data in A=[1,2;3,4]
Data processing A=A*2
B=A
Data out B=[2,4;6,8]
Pure logic
5. Program Flow – another algorithm
Data in A=[1,2;3,4]
if A(1,1)==1
A=A*2
else
Statement
A=A*3
True False end
Process A Process B B=A
1st time B=[2,4;6,8]
Data out 2nd time B=[6,12;18,24]
Decisions give flexibility
6. Making Decisions– why?
• When two or more possible
outcomes are required
• Decisions are made based on a
conditional tests
• if-then
• if-then-else....
7. if-then
If this lecture is too boring then I will fall
asleep
if
expression (this lecture is too boring)
then
statement (I will fall asleep)
Let’s code this up
8. if-then
If this lecture is too boring then I will fall
asleep
relational operator
if boredom > tiredness
student = ‘asleep’
end
then is implied
by the next line
9. if-then-else
If I fall asleep in lectures then I will not
understand the lab class otherwise I will
be able to complete the class quickly.
if
expression (I fall asleep in lectures)
then
statement (I will not understand the lab)
else
statement (I will be able to complete the
class quickly)
10. if-then-else
If I fall asleep in lectures then I will not
understand the lab class otherwise I will
be able to complete the class quickly.
relational operator
if boredom > tiredness
student = ‘confused in lab’
else
student = ‘going home early’
end
11. Relational operators
Operator Description
< Less than
<= Less than or equal to
> Greater than
>= Greater than or equal to
== Equal to
~= Not equal to
12. Relational operators
Can be used independently of if-else
A = 12;
B = 18;
C = A > B
Remember = is an assignment
C = 0
False = 0, True = 1
13. Logical operators
Operator Description
& True if all relations are
(AND) true
| True if at least one
(OR) relation is true
~ True if all relations are
(NOT) false
14. More if-then-else
Conditionals with more than 2 cases can
be built as well:
if (expression1)
statement1
elseif (expression2)
statement2
else
statement3
end
15. More if-then-else (Practical 1)
m=randn(100,1); loops next week
for loop1=1:100
if m(loop1)>2
n(loop1,1)=2;
elseif m(loop1)<-2
n(loop1,1)=0;
else
n(loop1,1)=1;
end
end
o=find(n==0);
p=find(n==2);
q=length(o)+length(p);