PhD Dissertation Writing Services-Dissertation Algorithm Development Tips For Developing Grey Wolf Optimization Algorithm Where And How It Is Solve Combined Economic Emission Dispatch Problems

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Research paper
DISSERTATION ALGORITHM DEVELOPMENT TIPS FOR
DEVELOPING GREY WOLF OPTIMIZATION
ALGORITHM Where and how it is Solve Combined
Economic Emission Dispatch Problems?
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SHORT NOTES
You will find the best dissertation research
areas / topics for future researchers enrolled in
Engineering. In order to identify the future
research topics, we have reviewed the Engineering
literature (recent peer-reviewed studies) on the
AI in optimization problems. Nature-Inspired
Optimization Algorithm is the recent trend in
Artificial Intelligence. Grey Wolf Optimizer
(GWO) is one of Nature-Inspired Optimization
Algorithm. Grey Wolf Optimizer (GWO) is inspired
by grey wolves called Canis lupus Grey Wolf
Optimizer is used to solve complicated aircraft
problems like weapon target assignment problem
(WTA) and also used to solve combined economic
emission dispatch problems.
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BACKGROUND
Over the couple of decades, meta-heuristic
optimization strategies have become very
prevalent, particularly in engineering
applications. The developing algorithm is easy
to implement, they are simple in concept, the
gradient data is not necessary, local optima can
circumvent them, they can be used in a wide
variety of disciplinary issues. Grey wolf
optimization is one of the popular meta-heuristic
optimization algorithms.
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GREY WOLF (CANIS LUPUS) BEHAVIOUR
Grey wolf (Canis lupus) is a member of the
Canida Grey wolves are regarded as predators of
the apex, indicating that they are at the top of
the pyramid (food chain). The grey lifestyle is
that the grey wolf has a very strict social
dominance hierarchy, as shown in figure.
Figure Hierarchy of Grey wolf
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FRIST LEVEL OF HIERARCHY OF GREY WOLVES
Alpha and they are group leaders. Alphas can be
male and female and they are the
decision-makers. The decisions made by the alpha
are communicated to the pack. The alpha wolf is
also known as the dominant wolf, as the pack must
obey his / her orders. Alpha wolves are only
permitted to mate in the pack. It reveals that a
pack's organization and discipline is more
important than its strength.
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SECOND LEVEL OF HIERARCHY OF GREY WOLVES
In the hierarchy of grey wolves, the second level
is Beta. The beta wolf could be female or male,
and if in case one of the alpha wolves becomes
very old or passes away, he/she is possibly the
best choice to be the alpha. The beta wolf is
supposed to honour the alpha, but can also order
the other lower-level wolves. The beta confirms
the alpha orders throughout the pack and provides
input to the alpha.
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THIRD LEVEL OF HIERARCHY OF GREY WOLVES
The lowest grey wolf ranking is Omega. The omega
takes a scapegoat's role. All other dominant
wolves can comment on the omega wolves. It might
seem that the omega is not an essential animal in
the pack, but it has been noted that in scenario
of losing the omega, the entire pack will face
the internal fight and few more issues. It helps
to please the whole pack and preserve the system
of dominance. The omega is also the nannies in
the family in certain situations.
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GREY WOLF ATTACK TOWARDS THE PREY
The delta wolves must report to alphas and
betas. Sentinels ensure the pack's security and
guarantee. Elders are the old skilled alpha or
beta wolves. Hunters assist the alphas and betas
during prey hunting and supplying the pack with
food. The interesting behaviour of grey wolves
is group hunting. The predominant stages of grey
wolf hunting are tracking, chasing, and reaching
the prey. The victim will be hunted, encircled
and threatened until it stops moving.
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GREY WOLF OPTIMIZER ALGORITHM
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CONCLUSION
The hunting strategy and the social hierarchy of
grey wolves have been mathematically modelled
and developed as an algorithm for Grey Wolf
Optimiser. It is efficient and powerful
algorithm to solve problems of continuous
optimization as well as real-life
optimization. GWO is able to solve complex
engineering problems with high efficiency and
superior performance. It is used in aircraft
engineering to overcome weapon target assignment
problems and also used to solve combined economic
emission dispatch problems.
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FUTURE SCOPES
Can be used in optimal positioning and sizing
multiple active power filters in the radial
distribution system Can be used as a bridging
tool Can be used as an adaptive neuro-fuzzy
inference system
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