Optimization of Drug Design Composition by Hybrid Islamic and Evolutionary Medicine for Covid-19 and Its New Variants Using Geometric Time Variants Extreme Genetic Algorithm

DOI

10.2991/978-94-6463-148-7_36How to use a DOI?

Keywords

Hybrid Islamic and Evolutionary Medicine; Covid-19 and It’s New Variants; Geometric Time Variants; Extreme Genetic Algorithm; meta-Deep AI Medicine Engine

Abstract

There is a difficulty in building the implementation of a computational model to build a complex Covid-19 drug design involving a smart ecosystem. Covid-19 and the drug design of its new variants are formed by combining the appropriate compound and dose as an antiviral. Drug designs as the candidates for Covid-19 drugs can be in the form of herbal medicines and other materials. In computing the design of this drug, the encountered problem is the way to separate the features between the mixed compounds. The feature extraction received will be optimized into compounds that are useful as Covid-19 drug candidates. On the other hand, drug design using manual computational methods is very complicated and requires a fairly long-time estimation in forming the proper compound with many variants of each compound. From the problems that occur, it requires a system that can perform drug design computations quickly and precisely. Therefore, a new method of combining extreme learning machines and genetic algorithms is made called Geometric Time Variants (GTV) Extreme Genetic Algorithm (XtremeGA or eXGA or ExGA). As a result, drug design optimization using historical data by hybrid Islamic and evolutionary medicine for Covid-19 and its new variants can work quickly, optimally, and achieved convergence conditions.

Copyright

© 2023 The Author(s)

Open Access

Open Access This chapter is licensed under the terms of the Creative Commons Attribution-NonCommercial 4.0 International License (http://creativecommons.org/licenses/by-nc/4.0/), which permits any noncommercial use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license and indicate if changes were made.

Download article (PDF)

TY  - CONF
AU  - Imam Cholissodin
AU  - Lailil Muflikhah
AU  - Sutrisno
AU  - Arief Andy Soebroto
AU  - Aurick Yudha Nagara
AU  - Renny Nova
AU  - Tamara Gusti Ebtavanny
AU  - Zanna Annisa Nur Azizah Fareza
PY  - 2023
DA  - 2023/05/29
TI  - Optimization of Drug Design Composition by Hybrid Islamic and Evolutionary Medicine for Covid-19 and Its New Variants Using Geometric Time Variants Extreme Genetic Algorithm
BT  - Proceedings of the 12th International Conference on Green Technology (ICGT 2022)
PB  - Atlantis Press
SP  - 368
EP  - 377
SN  - 2352-5401
UR  - https://doi.org/10.2991/978-94-6463-148-7_36
DO  - 10.2991/978-94-6463-148-7_36
ID  - Cholissodin2023
ER  -