£146.60

Pricier than usual. £6 more than the 30-day average — we'd wait.

£147 today · 30-day average £141 · all-time low £128

Elsevier Physics-Aware Machine Learning for Energy Systems - Elsevier

Amazon

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£149.99 £125.75 £131.04 £136.33 £141.61 £146.90 £152.19 27 July 2026 13 August 2026 31 August 2026 18 September 2026 06 October 2026
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56 days 9 days 1 day · current 6 days 0 14 28 42 56 £128 £130 £147 £150 Days at Price

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Most common price: £128 (56 days, 77.8%)

Price range: £128 - £150

Price levels: 4 different prices over 72 days

Description

Physics-Aware Machine Learning for Integrated Energy Systems Management is the latest addition to Elsevier's Advances in Intelligent Energy Systems series, providing a comprehensive guide to cutting-edge computational methods for modern sustainable grids. This book takes readers from foundational principles through practical implementation, covering the design and integration of energy systems with machine learning techniques. The content addresses critical topics including sustainability assessment, energy storage optimisation, and physical-economic modelling, whilst offering detailed, step-by-step procedures for applying varied computational approaches. Ideal for engineers, researchers, and professionals working in energy systems, this resource bridges the gap between physics-based models and data-driven machine learning, enabling readers to develop robust solutions for integrated energy management in the contemporary grid landscape.

Key Features

Covers physics-aware machine learning methods specifically designed for integrated energy systems management and modern grid applications.

Elsevier's Advances in Intelligent Energy Systems series provides peer-reviewed, authoritative content on state-of-the-art energy technologies.

Includes detailed procedures and training methodologies from data preparation through to real-world application opportunities.

Addresses sustainability assessment, energy storage systems, and physical-economic modelling for comprehensive energy system design.

Guides readers through computational principles necessary for optimising integrated energy systems in sustainable grid contexts.

Combines machine learning techniques with physics-based modelling for enhanced accuracy in energy systems forecasting and control.

Product Specifications

Format
paperback
Domain
Amazon UK
Release Date
01 August 2025
Listed Since
20 December 2024

Barcode

No barcode data available

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