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Mycorrhiza optimization algorithm

Record Type:	Language materials, printed : Monograph/item
Title/Author:	Mycorrhiza optimization algorithm/ by Fevrier Valdez, Hector Carreon-Ortiz, Oscar Castillo.
Author:	Valdez, Fevrier.
other author:	Castillo, Oscar.
Published:	Cham :Springer Nature Switzerland : : 2023.,
Description:	viii, 78 p. :ill. (some col.), digital ; : 24 cm.;
Contained By:	Springer Nature eBook
Subject:	Engineering Mathematics. -
Online resource:	https://doi.org/10.1007/978-3-031-47369-2
ISBN:	9783031473692

Mycorrhiza optimization algorithm
Valdez, Fevrier.

Mycorrhiza optimization algorithm[electronic resource] /by Fevrier Valdez, Hector Carreon-Ortiz, Oscar Castillo. - Cham :Springer Nature Switzerland :2023. - viii, 78 p. :ill. (some col.), digital ;24 cm. - SpringerBriefs in computational intelligence,2625-3712. - SpringerBriefs in computational intelligence..

Introduction to the Mycorrhiza Optimization Algorithm -- Theory for the Mycorrhiza Optimization Algorithm -- Background for the Mycorrhiza Algorithm -- Problem Definition -- CMOA - Continuous Mycorrhiza Optimization Algorithm -- DMOA - Discrete Mycorrhiza Optimization Algorithm -- Conclusions of the Mycorrhiza Optimization Algorithm.

This book provides two new optimization algorithms to address real optimization problems. Optimization is a fundamental concept in engineering and science, and its applications are needed in many fields. From designing products and systems to developing algorithms and models, optimization plays a critical role in achieving efficient and effective solutions to complex problems. Optimization algorithms inspired by nature have proven effective in solving a wide range of problems, including those in engineering, finance, and machine learning. These algorithms are often used when traditional optimization techniques are impractical due to the size or complexity of the problem. In this book, we are presenting two new optimization algorithms inspired by plant roots and the Mycorrhiza Network. The first algorithm is called the Continuous Mycorrhiza Optimization Algorithm (CMOA), which was proposed based on the model of the Continuous Lotka-Volterra System Equations. The second algorithm is called the Discrete Mycorrhiza Optimization Algorithm (DMOA), which design based on the model of Discrete Lotka-Volterra System Equations. By mastering the proposed algorithms, the readers able to develop innovative solutions that improve efficiency, reduce costs, and improve performance in the corresponding field of work.

ISBN: 9783031473692

Standard No.: 10.1007/978-3-031-47369-2doiSubjects--Topical Terms:

1203947
Engineering Mathematics.

LC Class. No.: QA402.5 / .V353 2023

Dewey Class. No.: 519.6

Mycorrhiza optimization algorithm
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520 $a This book provides two new optimization algorithms to address real optimization problems. Optimization is a fundamental concept in engineering and science, and its applications are needed in many fields. From designing products and systems to developing algorithms and models, optimization plays a critical role in achieving efficient and effective solutions to complex problems. Optimization algorithms inspired by nature have proven effective in solving a wide range of problems, including those in engineering, finance, and machine learning. These algorithms are often used when traditional optimization techniques are impractical due to the size or complexity of the problem. In this book, we are presenting two new optimization algorithms inspired by plant roots and the Mycorrhiza Network. The first algorithm is called the Continuous Mycorrhiza Optimization Algorithm (CMOA), which was proposed based on the model of the Continuous Lotka-Volterra System Equations. The second algorithm is called the Discrete Mycorrhiza Optimization Algorithm (DMOA), which design based on the model of Discrete Lotka-Volterra System Equations. By mastering the proposed algorithms, the readers able to develop innovative solutions that improve efficiency, reduce costs, and improve performance in the corresponding field of work.
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