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Advancements in optimization and nature-inspired computing for solutions in contemporary engineering challenges

紀錄類型:	書目-電子資源 : Monograph/item
正題名/作者:	Advancements in optimization and nature-inspired computing for solutions in contemporary engineering challengesedited by Diego Rossit, Carlos Enrique Torres-Aguilar, Adrián Andrés Toncovich.
其他作者:	Rossit, Diego.
出版者:	Singapore :Springer Nature Singapore :2025.
面頁冊數:	xii, 312 p. :ill. (chiefly color), digital ;24 cm.
Contained By:	Springer Nature eBook
標題:	Nature-inspired algorithms.
電子資源:	https://doi.org/10.1007/978-981-96-0706-8
ISBN:	9789819607068$q(electronic bk.)

Advancements in optimization and nature-inspired computing for solutions in contemporary engineering challenges
Advancements in optimization and nature-inspired computing for solutions in contemporary engineering challenges[electronic resource] /edited by Diego Rossit, Carlos Enrique Torres-Aguilar, Adrián Andrés Toncovich. - Singapore :Springer Nature Singapore :2025. - xii, 312 p. :ill. (chiefly color), digital ;24 cm. - Springer tracts in nature-inspired computing,2524-5538. - Springer tracts in nature-inspired computing..

Introduction chapter -- Data mining to build the OD matrix in developing countries: preliminary analysis in an Argentinean case study -- Spatial - Temporal Trajectory Mining for sustainable Mobility and Transport -- Multiobjective evolutionary approach for flight planning of an autonomous fleet of unmanned aerial vehicles in exploration and surveillance missions -- Genetic algorithm for generating alternative corridor locations -- An optimization model for the investment portfolio allocation problem: case study -- Continuous User Authentication System using Different Biometrics -- Automation of Student marking system -- Mini review of models and algorithms for the Cell Switch-Off Optimization problem in 5G/6G telecommunications ultradense networks -- Enhancing Human-Computer Interaction through Vision-Based Hand Gesture Recognition: An OpenCV and Keras Approach -- Sustainable Creations: A Holistic Guide to Optimize Digital Footprints and Foster Climate-Conscious Innovation -- Biometric Insights - Harnessing Nature's Blueprints for Advanced Computing Solutions -- Kalman Filtering Based on Interval Type-2 Evolving Takagi-Sugeno Fuzzy Model Via Multivariable Spectral Analysis of Experimental Data -- A Comparative Analysis of Machine Learning Classifiers in Demand Forecasting -- Optimizing Sorting Algorithms for Small Arrays: A Comprehensive Study of the Chunked Insertion Sort Approach -- Use of Neural Networks to model an inventory system as a family of industrial belts within the supply chain -- A system for making decisions in the subcontracting of transport providers.

This book brings together cutting-edge research, methodologies, and applications in the field of optimization and nature-inspired computing, providing a comprehensive overview of the latest advancements and their applications in addressing contemporary challenges in engineering. The book demonstrates diverse applications of mathematical modeling in various aspects of production, logistic, design, energy, materials, and other engineering areas. The book includes topics in optimization algorithms nature-inspired computing multi-objective optimization hybrid optimization techniques evolutionary algorithms swarm intelligence machine learning for optimization applications of optimization in engineering sustainable engineering solutions big data analytics for optimization metaheuristic approaches cloud computing in optimization cyber-physical systems decision support systems emerging trends in optimization.

ISBN: 9789819607068$q(electronic bk.)

Standard No.: 10.1007/978-981-96-0706-8doiSubjects--Topical Terms:

858794
Nature-inspired algorithms.

LC Class. No.: QA76.9.N37

Dewey Class. No.: 006.382

Advancements in optimization and nature-inspired computing for solutions in contemporary engineering challenges
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505 0 $a Introduction chapter -- Data mining to build the OD matrix in developing countries: preliminary analysis in an Argentinean case study -- Spatial - Temporal Trajectory Mining for sustainable Mobility and Transport -- Multiobjective evolutionary approach for flight planning of an autonomous fleet of unmanned aerial vehicles in exploration and surveillance missions -- Genetic algorithm for generating alternative corridor locations -- An optimization model for the investment portfolio allocation problem: case study -- Continuous User Authentication System using Different Biometrics -- Automation of Student marking system -- Mini review of models and algorithms for the Cell Switch-Off Optimization problem in 5G/6G telecommunications ultradense networks -- Enhancing Human-Computer Interaction through Vision-Based Hand Gesture Recognition: An OpenCV and Keras Approach -- Sustainable Creations: A Holistic Guide to Optimize Digital Footprints and Foster Climate-Conscious Innovation -- Biometric Insights - Harnessing Nature's Blueprints for Advanced Computing Solutions -- Kalman Filtering Based on Interval Type-2 Evolving Takagi-Sugeno Fuzzy Model Via Multivariable Spectral Analysis of Experimental Data -- A Comparative Analysis of Machine Learning Classifiers in Demand Forecasting -- Optimizing Sorting Algorithms for Small Arrays: A Comprehensive Study of the Chunked Insertion Sort Approach -- Use of Neural Networks to model an inventory system as a family of industrial belts within the supply chain -- A system for making decisions in the subcontracting of transport providers.
520 $a This book brings together cutting-edge research, methodologies, and applications in the field of optimization and nature-inspired computing, providing a comprehensive overview of the latest advancements and their applications in addressing contemporary challenges in engineering. The book demonstrates diverse applications of mathematical modeling in various aspects of production, logistic, design, energy, materials, and other engineering areas. The book includes topics in optimization algorithms nature-inspired computing multi-objective optimization hybrid optimization techniques evolutionary algorithms swarm intelligence machine learning for optimization applications of optimization in engineering sustainable engineering solutions big data analytics for optimization metaheuristic approaches cloud computing in optimization cyber-physical systems decision support systems emerging trends in optimization.
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