نتایج جستجو برای: nature inspired algorithm

تعداد نتایج: 1083956  

Journal: :International Journal of Sustainable Engineering 2014

Journal: :CoRR 2012
Sudarshan Nandy Partha Pratim Sarkar Achintya Das

Back-propagation algorithm is one of the most widely used and popular techniques to optimize the feed forward neural network training. Nature inspired meta-heuristic algorithms also provide derivative-free solution to optimize complex problem. Artificial bee colony algorithm is a nature inspired meta-heuristic algorithm, mimicking the foraging or food source searching behaviour of bees in a bee...

Journal: :CoRR 2013
Sandeep Kumar Vivek Kumar Sharma Rajani Kumari

Artificial bee colony (ABC) algorithm has proved its importance in solving a number of problems including engineering optimization problems. ABC algorithm is one of the most popular and youngest member of the family of population based nature inspired meta-heuristic swarm intelligence method. ABC has been proved its superiority over some other Nature Inspired Algorithms (NIA) when applied for b...

Journal: :Artificial Intelligence Review 2015

Journal: :ACM Computing Surveys 2021

Nature-inspired computing is a type of human-designed motivated by nature, which based on the employ paradigms, mechanisms, and principles underlying natural systems. In this article, versatile vigorous bio-inspired branch computing, named membrane discussed. This paradigm aroused internal function structure biological cells. We first introduce some basic concepts formalisms then types or varia...

Journal: :international journal of smart electrical engineering 2013
setareh shafaghi fardad farokhi reza sabbaghi-nadooshan

many real world problems can be modelled as an optimization problem. evolutionary algorithms are used to solve these problems. ant colony algorithm is a class of evolutionary algorithms that have been inspired of some specific ants looking for food in the nature. these ants leave trail pheromone on the ground to mark good ways that can be followed by other members of the group. ant colony optim...

Journal: :Current Opinion in Structural Biology 2010

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