Anomaly Detection - Methods, Complexities and Applications

ISBN 10: 1836343590 / ISBN 13: 9781836343592

Published by Intechopen Okt 2025, 2025

About this Item

This item is printed on demand - Print on Demand Titel. Neuware -Anomalies are early whispers of malfunction, intrusion, or even discovery. Anomaly Detection - Methods, Complexities, and Applications offers a concise, practice-oriented guide to turning those whispers into actionable insights. Blending attention¿enhanced supervision, ensemble learning, and variational autöencoders with sector¿specific experience from smart manufacturing, renewable¿rich power grids, secure e¿commerce platforms, and astrophysical observatories, the volume gives readers a panoramic view of data pre¿processing, imbalance handling, explainability, edge deployment, and real¿time analytics. By uniting algorithmic rigor with implementation detail, the book equips engineers, researchers, and graduate students to design resilient monitoring systems, reduce operational risk, and unlock new knowledge from large, noisy datasets.Books on Demand GmbH, Überseering 33, 22297 Hamburg 138 pp. Englisch.

Seller Inventory # 9781836343592

Bibliographic Details

• Title: Anomaly Detection - Methods, Complexities and Applications
• Publisher: Intechopen Okt 2025
• Publication Date: 2025
• Language: English
• ISBN 10: 1836343590
• ISBN 13: 9781836343592
• Binding: Buch
• Condition: Neu
• Dimensions: 260W x 183H x 14D millimeters 260 millimeters width by 183 millimeters height by 14 millimeters depth
• Weight: 500 grams

About this title

Synopsis

Anomalies are early whispers of malfunction, intrusion, or even discovery. Anomaly Detection - Methods, Complexities, and Applications offers a concise, practice-oriented guide to turning those whispers into actionable insights. Blending attention‑enhanced supervision, ensemble learning, and variational auto‑encoders with sector‑specific experience from smart manufacturing, renewable‑rich power grids, secure e‑commerce platforms, and astrophysical observatories, the volume gives readers a panoramic view of data pre‑processing, imbalance handling, explainability, edge deployment, and real‑time analytics. By uniting algorithmic rigor with implementation detail, the book equips engineers, researchers, and graduate students to design resilient monitoring systems, reduce operational risk, and unlock new knowledge from large, noisy datasets.