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                     DISSERTATION ALGORITHM 
DEVELOPMENT  TIPS FOR 
DEVELOPING SOCIAL SPIDER  
ALGORITHM AND GLOBAL 
OPTIMIZATION  WHERE AND HOW IT 
AInS A cademic presentation by
Dr. Nancy Agens, Head, Technical Operations, 
PUhdSassEistDanc?e  Group www.phdassistance.com
Email: [email protected]
Today's 
Discussion
OUTLINE
Short 
notes  
Backgroun
d
Social 
Spider 
Behavior
Social 
Spider 
Algorithm 
(SSA)
Flowchart for the Original Social Spider 
Algorithm  Conclusion
Future scope
In 
Brief
Swarm intelligence algorithm is the recent trend in Artificial Intelligence.
A Social Spider Algorithm (SSA) is one of Nature-Inspired Swarm Optimization 
Algorithm.  In a meta-heuristic design, SSA is a social animal foraging model
SSA is used to solve Global optimisation problems in engineering design 
particularly in  mechanical engineering design problems
Increasing complexity of real-world issues has inspired 
computer  scientists to look for effective methods of 
problem-solving.
A nature-inspired Swarm Optimization Algorithm called 
Backgroun Social  Spider Algorithm(SSA) is based primarily on the 
sf orcaigailn sgp iadpeprrso 'ach, using the vibrations on the spider 
d web to  assess the positions of the preys.
We perform preliminary parameter sensitivity 
analysis,  developing guidelines for selecting the 
parameter values.
Spiders have been a large research topic in bionic technology for 
several  years among the frequently seen animals.
Spiders have long been recognized to be very sensitive to 
Social vibratory  stimuli, as vibrations on their webs remind them of the capture of prey.
Spider  Social spiders indirectly receive the vibrations on the same web 
created  by other spiders to get a clear view of the web.
Behavior
This is one of the unique characteristics that separate social spiders 
from  other species as one typically regularly share information, 
which  decreases information loss to some extent but increases the 
energy  consumed by communication action.
Figure :
Social spider 
behaviour
Social Spider Algorithm, we formulate the search 
space as a
hopytpimeris-adtiimonensional spider web for the problem of
Social .
Spider  Every position on the web reflects a feasible solution to the  optimization problem, and there are 
Algorithm corresponding positions  on this web for all feasible 
solutions.
(SSA) Spider on the web has a position and the solution's 
efficiency  is dependent on the objective feature and 
reflects the potential  to find a food source at the position.
Contd..
A spider moves to a new location, a vibration is produced which propagates over the 
web.
Vibration contains information about one spider, and when the vibration is transmitted, 
other  spiders can get the information.
A predefined number of spiders are placed on the Web at the beginning of the 
algorithm.
Number of iterations has last changed its target vibration.
Dimension mask1 employed to guide movement in the previous iteration.
First two types of information describe the individual situation, while all others are 
involved in  directing new positions.
Flowchart
forthe
Original  
Social Spider  
Algorithm
Social Spider Algorithm is the inspiration of social 
spider  behaviours.
Algorithm is designed based on spider behaviour 
Conclusio and  preying nature.
n Social Spider Algorithm formulate the search space 
as a  hyper-dimensional spider web for an 
optimization  problem.
SSA is used to solve Global optimisation problems 
in  engineering design particularly in mechanical 
engineering  design problems.
For feature selection problem, social spider 
algorithm  can be used as an efficient binary 
FUTURE method.
SCOPE It provides a solution for optimal power 
flow  problems with single objective 
optimization.
Can be used as cloud tracking using multi-
objective  images on satellite
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