Learn different algorithms used in Space Missions. Video Link Video Chapters: Algorithms Behind Space Missions 00:00 Introduction 00:52 Space Missions 04:26 Space Missions Challenges 07:04 Algorithms Used in Space Missions 10:36 Optimization Techniques 11:44 Conclusion NASA conducts space missions to explore the universe for various scientific, technological, and practical reasons: Understanding Our Place in the Universe Search for Life Beyond Earth Studying Earth from Space Advancing Technology Supporting Human Exploration Resource Utilization Inspiring Humanity Examples of NASA Space Missions Apollo Program: Sent humans to the Moon (1969–1972). Mars Rovers (Spirit, Opportunity, Perseverance): Explored Mars' surface and geology. Voyager Missions: Studied the outer planets and interstellar space. Hubble Space Telescope: Captured breathtaking images of the universe. International Space Station (ISS): Supports research in microgravity and international collaboration. Different ...
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Shark Smell Optimization Algorithm Numerical Example
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SHARK SMELL OPTIMIXATION ALGORITHM [ Numerical Example ]
Shark Smell Optimization Algorithm is population based Metaheuristic optimization algorithm. Shark Smell Optimization Algorithm is inspired by the Shark food foraging behavior.
Shark Smell Optimization Algorithm Steps:
Initialize Algorithm Parameters
Initialize Population for N Sharks in the search space.
Evaluate Performance.
While (current Iteration < Maximum Iteration)
Calculate Shark Velocity
Calculate Shark Position based on forward movement.
Calculate Shark Position based on rotational movement.
Identify Shark next position based on forward and rotational movements.
Evaluate Performance.
End While
Display Best Solution.
STEP 01: Initial Important Parameters.
Current_Iteration =1;
Maximum_Iteration = 10;
and other.
STEP 02: Initial Population Randomly.
Suppose, Population Size = 2;
Position(1) = -0.9891
Position(2) = -8.3236
STEP 03: Using Fitness Function Calculate Fitness Values.
Fitness(1) = 0.97845
Fitness(2) = 69.2819
Global Best = 0.97845
STEP 04: Calculate Shark's Velocity.
NOTE: At 1st Iteration, you can either neglect initial velocity or assign very small value.
For this Check IF (Current_Iteration ==1){
Initialize Velocity.}
Else{
Modify Velocity.
End
Right Now as iteration is 1.
Velocity(1) = 0;
Velocity(2) = 0;
STEP 05: Calculate Shark Movement in the search space.
Update Position for 1st Agent
a.) Calculate Shark Forward Movement for 1st Agent.
New Position (1) = Previous Position + Previous Velocity * Current Iteration
New Position (1) = (-0.9891) + 0 * 1;
New Position (1) = -0.9291
New Fitness (1) = 0.8632
b.) Calculate Shark Rotational Movement for 1st Agent.
New Position (1) = Previous Position + (Random Value * Previous Position)
New Position (1) = 0.8632 + ( 0.9189*0.8632)
New Position (1) = 1.6563
New Fitness (1) = 2.7433
Update Position for 2nd Agent
a.) Calculate Shark Forward Movement for 2nd Agent.
New Position (2) = Previous Position + Previous Velocity * Current Iteration
New Position (2) = (-8.32361) + 0 * 1;
New Position (2) = -8.3261
New Fitness (2) = 69.2823
b.) Calculate Shark Rotational Movement for 2nd Agent.
New Position (2) = Previous Position + (Random Value * Previous Position)
New Position (2) = -8.3261 + ( 0.3259*(-8.3261))
New Position (2) = 5.6126
New Fitness (2) = 31.5015
STEP 06: Update Sharks Position based on Forward and Rotational Movement.
For 1st Agent:
New Position(1) = max { 0.8632, 2.7433} //Check max value (i.e., 0.8632)
New Position (1) = 1.6563
New Fitness (1) = 2.7433
For 2nd Agent:
New Position(2) = max {69.2823, 31.5015} //Check max value (i.e., 69.2823)
New Position (2) = -8.3261
New Fitness (2) = 69.2823
STEP 07: Increment Iteration Counter.
Current_Iteration = Current_Iteration + 1;
Current_Iteration = 1+1;
Current_Iteration = 2.
NOTE: Repeat The Loop until Stopping Criteria Met.
STEP 08: Display Best Solution Found.
First Iteration, Best Solution: 69.2823
The best position of shark is the Last Iteration that has the maximum Fitness value (for Maximization problems) is considered as the the BEST SOLUTION.
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