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Solving with bees = transformative applications of artificial bee colony algorithm /

Record Type:	Electronic resources : Monograph/item
Title/Author:	Solving with bees/ edited by Khalid Raza.
Reminder of title:	transformative applications of artificial bee colony algorithm /
other author:	Raza, Khalid.
Published:	Singapore :Springer Nature Singapore : : 2024.,
Description:	xviii, 199 p. :ill. (chiefly color), digital ;24 cm.
[NT 15003449]:	Fundamentals of Artificial Bee Colony Algorithms and Its Variants -- The Rise of Artificial Bee Colony Algorithms in Data Science and Machine Learning is Notable -- Swarm Intelligence for Optimization: A Bee's-Eye View on Multi-objective and Dynamic Challenges -- Artificial Bee Colony Algorithms in Control Systems, Robotics and Automation -- Integrating Artificial Bee Colony Algorithms for Deep Learning Model Optimization: A Comprehensive Review -- An IoMT Enabled Iterative Artificial Bee Colony Approach Using Federated Learning for Detection of Heart Disease -- Optimal Design of a Biomedical Amplifier for Minimum Offset Using a Modified ABC Algorithm -- Using Honeybees for Gene Expression Profiling: The Artificial Bee Colony Algorithm to Identify Robust Gene Biomarkers for Clinical Diagnosis -- Smart Diagnostics for Diabetic Retinopathy: Integrating Artificial Bee Colony Algorithms into Medical Image Analysis -- Artificial Bee Colony Algorithms in Gene Expression Studies: A Case Study -- Artificial Bee Colony Algorithm in Multi-Omics Analysis: A Case Study.
Contained By:	Springer Nature eBook
Subject:	Natural computation. -
Online resource:	https://doi.org/10.1007/978-981-97-7344-2
ISBN:	9789819773442

Solving with bees = transformative applications of artificial bee colony algorithm /
Solving with beestransformative applications of artificial bee colony algorithm /[electronic resource] :edited by Khalid Raza. - Singapore :Springer Nature Singapore :2024. - xviii, 199 p. :ill. (chiefly color), digital ;24 cm. - Springer tracts in nature-inspired computing,2524-5538. - Springer tracts in nature-inspired computing..

Fundamentals of Artificial Bee Colony Algorithms and Its Variants -- The Rise of Artificial Bee Colony Algorithms in Data Science and Machine Learning is Notable -- Swarm Intelligence for Optimization: A Bee's-Eye View on Multi-objective and Dynamic Challenges -- Artificial Bee Colony Algorithms in Control Systems, Robotics and Automation -- Integrating Artificial Bee Colony Algorithms for Deep Learning Model Optimization: A Comprehensive Review -- An IoMT Enabled Iterative Artificial Bee Colony Approach Using Federated Learning for Detection of Heart Disease -- Optimal Design of a Biomedical Amplifier for Minimum Offset Using a Modified ABC Algorithm -- Using Honeybees for Gene Expression Profiling: The Artificial Bee Colony Algorithm to Identify Robust Gene Biomarkers for Clinical Diagnosis -- Smart Diagnostics for Diabetic Retinopathy: Integrating Artificial Bee Colony Algorithms into Medical Image Analysis -- Artificial Bee Colony Algorithms in Gene Expression Studies: A Case Study -- Artificial Bee Colony Algorithm in Multi-Omics Analysis: A Case Study.

This book is a comprehensive volume, which delves into the versatile world of Artificial Bee Colony (ABC) algorithms, their variants, and myriad applications in a wide range of fields. This book is designed to be an essential resource for researchers, practitioners, students, and anyone intrigued by the fascinating realm of swarm intelligence and optimization. This book serves as a bridge between the theoretical foundations of ABC algorithms and their practical implementations across diverse domains. The book offers a deep understanding of these algorithms and how they can be harnessed to tackle complex real-world challenges.

ISBN: 9789819773442

Standard No.: 10.1007/978-981-97-7344-2doiSubjects--Topical Terms:

1002233
Natural computation.

LC Class. No.: QA76.9.N37

Dewey Class. No.: 006.382

Solving with bees = transformative applications of artificial bee colony algorithm /
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245 0 0 $a Solving with bees $h [electronic resource] : $b transformative applications of artificial bee colony algorithm / $c edited by Khalid Raza.
260 $a Singapore : $b Springer Nature Singapore : $b Imprint: Springer, $c 2024.
300 $a xviii, 199 p. : $b ill. (chiefly color), digital ; $c 24 cm.
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505 0 $a Fundamentals of Artificial Bee Colony Algorithms and Its Variants -- The Rise of Artificial Bee Colony Algorithms in Data Science and Machine Learning is Notable -- Swarm Intelligence for Optimization: A Bee's-Eye View on Multi-objective and Dynamic Challenges -- Artificial Bee Colony Algorithms in Control Systems, Robotics and Automation -- Integrating Artificial Bee Colony Algorithms for Deep Learning Model Optimization: A Comprehensive Review -- An IoMT Enabled Iterative Artificial Bee Colony Approach Using Federated Learning for Detection of Heart Disease -- Optimal Design of a Biomedical Amplifier for Minimum Offset Using a Modified ABC Algorithm -- Using Honeybees for Gene Expression Profiling: The Artificial Bee Colony Algorithm to Identify Robust Gene Biomarkers for Clinical Diagnosis -- Smart Diagnostics for Diabetic Retinopathy: Integrating Artificial Bee Colony Algorithms into Medical Image Analysis -- Artificial Bee Colony Algorithms in Gene Expression Studies: A Case Study -- Artificial Bee Colony Algorithm in Multi-Omics Analysis: A Case Study.
520 $a This book is a comprehensive volume, which delves into the versatile world of Artificial Bee Colony (ABC) algorithms, their variants, and myriad applications in a wide range of fields. This book is designed to be an essential resource for researchers, practitioners, students, and anyone intrigued by the fascinating realm of swarm intelligence and optimization. This book serves as a bridge between the theoretical foundations of ABC algorithms and their practical implementations across diverse domains. The book offers a deep understanding of these algorithms and how they can be harnessed to tackle complex real-world challenges.
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650 2 4 $a Image Processing. $3 891209
700 1 $a Raza, Khalid. $3 3487085
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856 4 0 $u https://doi.org/10.1007/978-981-97-7344-2
950 $a Intelligent Technologies and Robotics (SpringerNature-42732)