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Metaheuristics for Big Data

critical challenges: infrastructure, for storage and transportation, and conceptual models. Finally, to extract meaning from Big Data requires;

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Recent Advances in Hybrid Metaheuristics for Data Clustering

intelligence techniques Recent Advances in Hybrid Metaheuristics for Data Clustering offers a guide to the fundamentals of various metaheuristics;

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Metaheuristics for Combinatorial Optimization

was taken into account for the Metaheuristics Competition proposed in MESS 2018, Metaheuristics Summer School, and the top 4 methodologies ranked;

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Machine Learning for Big Data Analysis

for big data analytics. Big data is a term for data sets that are so large or complex that traditional data processing application software;

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Metaheuristics

an efficient context for experienced researchers or readers not familiar with theory, applications and computational developments of the;

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Metaheuristics

engineering design, routing, and scheduling. It presents the main design questions for all families of metaheuristics and clearly illustrates how to;

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Parallel Metaheuristics

can provide useful and practical solutions for a wide range of problems and application domains, with an emphasis on the fields;

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Heuristics

, performance comparisons of metaheuristics, co-operative methods combining different approaches, parallel and distributed metaheuristics for multi;

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Production Research

; machine learning and big data.;

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Production Research

; machine learning and big data.;

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Hybrid Metaheuristics

of interest for all the researchers working on integrating metaheuristics with other areas for solving both optimization and constraint satisfaction;

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Recent Developments in Metaheuristics

chapters in this section cover topics from multi-objective problems with fuzzy data with triangular-valued objective functions, to hyper-heuristics;

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Metaheuristics for Robotics

essentials of what is needed to reformulate control laws into concrete optimization data. The resolution approaches implemented A as well;

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Metaheuristics for Intelligent Electrical Networks

techniques. Metaheuristics for Intelligent Electrical Networks analyzes the use of metaheuristics through independent applications but united by;

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Metaheuristic Applications in Structures and Infrastructures

Due to an ever-decreasing supply in raw materials and stringent constraints on conventional energy sources, demand for lightweight;

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Advances in Metaheuristics

Metaheuristics have been a very active research topic for more than two decades. During this time many new metaheuristic strategies have;

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Hybrid Metaheuristics

The main goal of this book is to provide a state of the art of hybrid metaheuristics. The book provi;...

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Big Data BigData 2020

Architecture, Big Data Modeling, Big Data As A Service, Big Data for Vertical Industries (Government, Healthcare, etc.), Big Data Analytics, Big Data;

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Networking for Big Data

Networking for Big Data supplies an unprecedented look at cutting-edge research on the networking and communication aspects of Big Data;

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Networking for Big Data

Networking for Big Data supplies an unprecedented look at cutting-edge research on the networking and communication aspects of Big Data;

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Metaheuristics for Portfolio Optimization

and strategic Portfolio Optimization models in Finance, that employ Metaheuristics for their effective solutions and demonstrates the results;

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Big Data Visualization

Learn effective tools and techniques to separate big data into manageable and logical components for efficient data visualization About;

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Big Data Management

and challenges. While open source solutions to store big data, like Hadoop, offer platforms for exploring value and insight from big data;

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Big Data and Innovation in Tourism, Travel, and Hospitality

practitioners have to address for effective big data innovation. The book proposes a process-based model to identify and implement big data innovation;

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Multimodal Analytics for Next-Generation Big Data Technologies and Applications

This edited book will serve as a source of reference for technologies and applications for multimodality data analytics in big data;

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Big Data

methods for scientific and social discovery. It covers fundamental issues about Big Data, including efficient algorithmic methods to process data;

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Big Data

methods for scientific and social discovery. It covers fundamental issues about Big Data, including efficient algorithmic methods to process data;

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