Augmented Intelligence: Deep Learning, Machine Learning, Cognitive Computing, Educational Data Mining

Crow Search Algorithm: A Systematic Review

Author(s): Ali Aloss, Barnali Sahu* and Om Prakash Jena

Pp: 149-180 (32)

DOI: 10.2174/9789815040401122030009

* (Excluding Mailing and Handling)

Abstract

Cognitive computing and Artificial Intelligence (AI) are Computer Science branches which aim to create machines and ingenious technologies that are capable of working and thinking like humans. Evolutionary computing is a subfield of AI that uses nature-inspired mechanisms (algorithms) and solves problems through processes that mimic the behavior of living organisms. Researchers have focused on several meta-heuristic algorithms, and the Crow Search Algorithm (CSA) is one of the recently developed algorithms dependent on the astute conduct of crows. CSA is a populacebased methodology. It works by storing excess food in hiding places and extracting the food when necessary. This algorithm has been used in different fields such as medical diagnoses, fractional optimization problems, and energy problems. Several modifications have been made to this algorithm, and the current research focuses on a systematic review of the applications of the crow search algorithm in the medical domain and the variants of CSA and its application in different engineering fields. 


Keywords: Application of CSA, Crow search algorithm, Evolutionary algorithm, Medical diagnosis, Meta-heuristic algorithm, Variants of CSA.

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