Nature Plus Plus Inspired Computing - The Superset of Nature Inspired Computing

Satish Gajawada; Hassan M. H. Mustafa

doi:10.34257/GJCSTCVOL20IS1PG53

Nature Plus Plus Inspired Computing – The Superset of Nature Inspired Computing

Satish Gajawada * § B.Tech/M.Tech, IDD, Computer Science with Specialization in IT, IIT Roorkee. CGPA - 7.23, 2012.

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Hassan M. H. Mustafa

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Indian Institute of Technology Roorkee

Nature Plus Plus Inspired Computing – The Superset of Nature Inspired Computing

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DOI
10.34257/GJCSTCVOL20IS1PG53

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Abstract

The term “Nature Plus Plus Inspired Computing” is coined by us in this article. The abbreviation for this new term is “N++IC.” Just like the C++ programming language is a superset of C programming language, Nature Plus Plus Inspired Computing (N++IC) field is a superset of the Nature Inspired Computing (NIC) field. We defined and introduced “Nature Plus Plus Inspired Computing Field” in this work. Several interesting opportunities in N++IC Field are shown for Artificial Intelligence Field Scientists and Students. We show a literature review of the N++IC Field after showing the definition of Nature Inspired Computing (NIC) Field. The primary purpose of publishing this innovative article is to show a new path to NIC Field Scientists so that they can come up with various innovative algorithms from scratch. As the focus of this article is to introduce N++IC to researchers across the globe, we added N++IC Field concepts to the Particle Swarm Optimization algorithm and created the “Children Cycle Riding Algorithm (CCR Algorithm).” Finally, results obtained by CCR Algorithm are shown, followed by Conclusions.

References

11 Cites in Article

Reference Format

Nazmul Siddique,Hojjat Adeli (2015). Nature Inspired Computing: An Overview and Some Future Directions.
Lei Wang,Qi Kang,Qi-Di Wu (2007). Nature-inspired Computation — Effective Realization of Artificial Intelligence.
Alexandros Tzanetos,Iztok Fister,Georgios Dounias (2020). A comprehensive database of Nature-Inspired Algorithms.
P Marrow (2000). Nature-Inspired Computing Technology and Applications.
Y Sergeyev,D Kvasov,M Mukhametzhanov (2018). On the efficiency of nature-inspired metaheuristics in expensive global optimization with limited budget.
Shruti Goel,Manas Gaur,Eshaan Jain (2015). Nature Inspired Algorithms in Remote Sensing Image Classification.
Xin-She Yang (2020). Nature-Inspired Optimization Algorithms: 2nd Edition.
Ashraf Darwish (2018). Bio-inspired computing: Algorithms review, deep analysis, and the scope of applications.
S Binitha,Siva Sathya (2012). A Survey of Bio inspired Optimization Algorithms.
Jon Crowcroft (2008). Bio-Inspired Computing and Communication.
Satish Gajawada,Hassan Mustafa (2019). Artificial Human Optimization – An Overview.

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Funding

No external funding was declared for this work.

Conflict of Interest

The authors declare no conflict of interest.

Ethical Approval

No ethics committee approval was required for this article type.

Data Availability

Not applicable for this article.

How to Cite This Article

Satish Gajawada, Hassan M. H. Mustafa. 2020. "Nature Plus Plus Inspired Computing – The Superset of Nature Inspired Computing". Global Journal of Computer Science and Technology - C: Software & Data Engineering GJCST-C Volume 20 (GJCST Volume 20 Issue C1).

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GJCST Volume 20 Issue C1

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Journal Specifications

Crossref Journal DOI 10.17406/gjcst

Print ISSN 0975-4350

e-ISSN 0975-4172

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Classification

GJCST-C Classification I.2.m

Submission ReceivedDecember 14, 2019
Peer Review Double Blind
Handling Editor
Accepted January 3, 2020
Published January 15, 2020

Version of record

v1.2

Issue date

July 16, 2020

Language

English

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