Code for Computer Science

Elephant Herding Optimization Algorithm Learn Elephant Herding Optimization Algorithm Step-By-Step with Examples. Elephant Herding Optimization Algorithm - Introduced in 2015 - Inspired by Elephant Herding Behavior. - Main Operator used: + Elephant Clan Updating Operator + Elephant Separating Operator - Used to Solve Optimization Problems.

Python Turtle Graphics || Create a Happy Birthday Message to Someone Special || Feirnds || Family Members ||

Donkey and Smuggler Optimization Algorithm Learn Donkey and Smuggler Optimization Algorithm Step-By-Step with Examples Video Chapters: Introduction: 00:00 Donkey's Behavior: 02:02 Donkey Mode: 04:20 Donkey and Smuggler Optimization Algorithm: 06:49 Smuggler Mode: 08:02 Donkey and Smuggler Optimization Algorithm STEPS: 11:54 Donkey and Smuggler Optimization Algorithm FLOWCHART: 15:39 Conclusion: 16:24 About Donkey and Smuggler Optimization Algorithm: - Introduced in 2019 by Ahmed S Shamsaldin et. al. - Nature Inspired Population-Based Metaheuristic Optimization Algorithm. - Used to Solve Complex Optimization Problems. - Implemented to solve Real Life Optimization Problems such as Travelling Salesman Problem (TSP) Routing Problems     Ambulance Routing Donkey and Smuggler Optimization Algorithm MODES: Smuggler Mode [Non-Adaptive] Donkey Mode [Adapative] Donkey and Smuggler Optimization Algorithm STEPS: Initialize algorithm parameters i.e., Population Size, Dimensions, and

TURTLE GRAPHICS USING PYTHON || Turtle Star || 08 ||  STEPS Python Turtle Graphics Design First Import Turtle Here, variable r is considered a Turtle. Set Turtle Speed. Set Line Width. Set Background Color as while.  Select Colors for the Design. Create a List of Colors. For Loop Initialization. Access Colors from the List inside Loop. Set Direction for Turtle. SOURCE CODE import turtle r = turtle.Turtle() r = turtle.Pen() r.speed(1000) r.width(2) turtle.bgcolor('white') c = ['blue','lime','red','black','gold','aqua','purple','silver'] for x in range (600):     r.pencolor(c[x%8])     r.forward(x)     r.right(160) r.done() OUTPUT

SOURCE CODE import turtle r = turtle.Turtle() r = turtle.Pen() r.width(4) r.speed(50) turtle.bgcolor('black') c = ['white','red','blue','orange'] for i in range (700):     r.pencolor(c[i%4])     r.left(i)     r.right(100) r.done()

Python Turtle Graphics || Flower Design 0 6|| SOURCE CODE from turtle import Turtle r = Turtle() r.screen.bgcolor('black') color = ['red','lime','yellow'] r.screen.tracer(0,0) for x in range(150):     r.circle(x)     r.color(color[x%3])     r.left(60) r.screen.exitonclick() r.screen.mainloop() OUTPUT

Python Turtle Graphics || SPIRAL Design 05 ||  SOURCE CODE import turtle r = turtle.Turtle() s = turtle.Screen() s.bgcolor('white') r.width(2) r.speed(20) color = ('lime','aqua','red','indigo') for i in range (300):     r.pencolor(color[i%3])     r.forward(i*4)     r.right(121) OUTPUT

PYTHON TURTLE GRAPHICS || Turtle Star || SOURCE CODE from turtle import * color('blue','yellow') begin_fill() while True:     forward(300)     left(170)     if abs(pos())<1:         break end_fill() OUTPUT

TURTLE GRAPHICS USING PYTHON SOURCE CODE import turtle as r r.title('CIRCLE PATTERN') r.speed(20) r.bgcolor('white') r.shape('circle') r.color('red') for i in range (0,360,10):     r.seth(i)     r.circle(125) r.done() OUTPUT

PYTHON TURTLE GRAPHICS DESIGNS SOURCE CODE FOR SPIRAL HEXAGON import turtle colors = ['red','yellow','blue','green','white','orange','silver','pink'] s = turtle.Pen() turtle.bgcolor('black') for i in range (250):     s.pencolor(colors [i % 6])     s.width(i/100 +1)     s.forward(i)     s.left(50) OUTPUT

Python Turtles Graphics || Source Code || PYTHON TURTLE SOURCE CODE import turtle c = turtle.Turtle() c.color("blue") c.pensize(10) c.shape("turtle") c.backward(150) c.left(90) c.forward(150) c.right(90) c.forward(150) c.left(45) c.forward(40) c.right(67) c.backward(50) c.left(250) c.backward(60) c.left(180) c.forward(50) c.right(90) c.forward(100) c.down() c.forward(150) c.left(60) c.down() c.forward(40) c.down() c.right(60) c.forward(100) c.left(230) c.forward(200) c.up() c.right(52) c.forward(50) c.backward(200) c.left(20) c.forward(100) turtle.done()

PYTHON FOR BEGINNERS # Variables: Used to hold Values x = 200 y = 2 z = x+y print(z) OUTPUT: 202 # Careating Strings in Python r = 'Create stings' print(r) d = 'Don\'t Give Up' print(d) OUTPUT   Create stings Don't Give Up #Hold Values in Strings val = 50 disp = 'My Value is %s' print(disp % val) OUTPUT:  My Value is 50 #placeholder different variables - replace stings msg = '%s: Python is good' msg2 = '%s: Yes' c1 = 'Roy' c2 = 'Jhon' print(msg % c1) print(msg2 % c2) OUTPUT   Roy: Python is good Jhon: Yes #Hold Multiple Values  Hold= 'Add %s and %s' num1 = 23 num2 = 65 print(Hold % (num1,num2)) OUTPUT:   Add 23 and 65 #String Multiplication print(3 * 'R') OUTPUT:  RRR #How to use Space/Tab Space = ' ' * 10 print('%s Hello' % Space) print() print('%s Life = Peace' % Space) OUTPUT  :             Hello            Life = Peace #Create a String List and access Values from it. SimpleList

ARCHIMEDES OPTIMIZATION ALGORITHM VIDEO LINK: CLICK HERE... VIDEO CHAPTERS Introduction: 00:00 Archimedes Principle: 01:19 Archimedes Optimization Algorithm Idea: 07:07 Archimedes Optimization Algorithm Steps: 08:08 Archimedes Optimization Algorithm Mathematical Models: 11:32 Conclusion: 20 :12 Learn Archimedes Optimization Algorithm Step-by-Step with Example. Archimedes Optimization Algorithm Inspiration: Popular Physics Law (Archimedes Principle). - Used to Solve Complex Numerical Optimization Problems. - Used to solve Engineering Design Optimization Problems. Archimedes Principle : According to Archimedes Principle when a body is immersed wholly or partially in a fluid it loses its weight which is equal to the weight of the liquid displaced by the body. KEY TERMS Fluid: The Substance that flows under the action of applied forces. The fluid does not have its own shape. Pressure: It is a normal force acting on a unit surface area of the liquid. It is Force / Area. Density: Mas

Artificial Ecosystem Based Optimization Algorithm Video Link :  https://youtu.be/rbaxNqu7bdM Learn Artificial Ecosystem-based Optimization (AEO) Algorithm Step-by-Step with Example. - Algorithm Type: Nature Inspired Population-Based Metaheuristic Optimization - Used to solve Optimization Problems, Real life Engineering Design Optimization Problems - Provide best results when tested on different benchmark functions. - Outperforms other metaheuristics performance. Video Chapters: Introduction: 00:00 Algorithm Introduction: 01:06 The Ecosystem on Earth: 02:01 Food Chain: 06:28 Artificial Ecosystem-based Optimization Algorithm: 08:27 Artificial Ecosystem-based Optimization Algorithm Steps: 10:41 Mathematical Models: 12:12 Decomposition Process: 19:15 Conclusion: 22:29 An ecosystem is also known as Ecological System. Ecosystem components are Abiotic and Biotic. Abiotic components are non-living parts of the Ecosystem like Rock, water, air, etc. Biotic components are living parts of

Horse Herd Optimization Algorithm Learn the Horse herd optimization Algorithm (HOA) Step-by-Step. - Nature Inspired Metaheuristic Optimization Algorithm - Inspired by Horse Herd Behavior. - A large number of Controlling Parameters are Used. - Used to Solve Higher Dimensional Optimization Problems in real life. Video Chapters: Introduction: 00:00 Horse Herd Optimization Algorithm: 00:39 Horse Age Classification: 02:31 Horse Behavior: 04:28 Horse Position Update: 06:21 Horse Velocity Vectors: 08:26 Horse Grazing Vector: 09:28 Horse Hierarchy Vector: 10:38 Horse Sociability Vector: 11:45 Horse Imitation Vector: 12:30 Horse Defense Meachnism: 13:05 Horse Herd Optimization Algorithm Step: 15:06 Horse Velocity Vectors: 15:23 Horse Herd Optimization Algorithm Flowchart: 18:18 Conclusion: 19:00 A horse herd optimization algorithm is introduced in 2021. It is the nature-inspired population-based metaheuristic optimization algorithm that is basically inspired by the horse herdin