Metaheuristics for Enterprise Data Intelligence (eBook, ePUB)

Redaktion: Sakhare, Kaustubh Vaman; Shastri, Apoorva S; Vyas, Vibha

• Format: ePub

Produktbeschreibung

With the emergence of the data economy, information has become integral to business excellence. Every enterprise, irrespective of its domain of interest, carries and processes a lot of data in their day-to-day activities. Converting massive datasets into insightful information plays an important role in developing better business solutions. Data intelligence and its analysis pose several challenges in data representation, building knowledge systems, issue resolution and predictive systems for trend analysis and decisionmaking. The data available could be of any modality, especially when data is associated with healthcare, biomedical, finance, retail, cybersecurity, networking, supply chain management, manufacturing, etc. The optimization of such systems is therefore crucial to leveraging the best outcomes and conclusions. To this end, AI-based nature-inspired optimization methods or approximation-based optimization methods are becoming very powerful. Notable metaheuristics include genetic algorithms, differential evolution, ant colony optimization, particle swarm optimization, artificial bee colony, grey wolf optimizer, political optimizer, cohort intelligence and league championship algorithm. This book provides a systematic discussion of AI-based metaheuristics application in a wide range of areas, including big data intelligence and predictive analytics, enterprise analytics, graph optimization algorithms, machine learning and ensemble learning, computer vision enterprise practices and data benchmarking.

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Produktdetails

• Verlag: Taylor & Francis eBooks
• Erscheinungstermin: 7. August 2024
• Englisch
• ISBN-13: 9781040096505
• Artikelnr.: 72244432

Autorenporträt

Dr Kaustubh Sakhare, Sr. Data Scientist, System Engineering & Production Integration (SEPI), John Deer, Pune, India. Dr Vibha Vyas, Associate Professor, Department of Electronics and Telecommunication, College of Engineering, Pune, India. Dr Apoorva S. Shastri, Research Assistant Professor, Institute of Artificial Intelligence, MIT World Peace University, Pune, India.

Inhaltsangabe

Chapter 1
Terror Attacks Forecast Using Machine Learning and Neo4j Sandbox: A Review Sagar Shinde, Suchitra Khoje, Ankit Raj and Lalitkumar Wadhwa Chapter 2
5G Evolution and Revolution: A Study Namita K. Shinde, Chetan More, Payal Kadam and Vinod Patil Chapter 3
Metaheuristic Algorithms and Its Application in Enterprise Data Radhika D. Joshi, Sheetal Waghchaware and Rushikesh Dudhani Chapter 4
Petrographic Image Classification Accuracy Improvement Using Improved Learning Ashutosh Marathe, Tanuja Tewari and Falguni Vyas Chapter 5
Data Visualization and Dashboard Design for Enterprise Intelligence Nishikant Bhaskar Surwade, Bahubali Shiragapur and Anwar Hussain Chapter 6
Beyond the Hype: Understanding the Potential of ChatGPT in the Articulation of Technical Papers Neha Shaah Chapter 7
Metaheuristics and Deep Learning in Lung Nodule Detection and Classification Rama Vaibhav Kaulgud and Mandar Saundattikar Chapter 8
An Improved Face Recognition Method Using Canonical Correlation Analysis Ganesh D. Jadhav, Suhas Patil, Bhushan M. Borhade and Yogesh Shinde Chapter 9
Guesswork to Results: How ML-Based A/B Testing Is Changing the Game Namita K. Shinde, Payal Kadam, Aditya Choudhary, Bhavay Chopra and Krishnansh Awasthi