Get Free Shipping on orders over $79
AI for Decision Intelligence in Critical Systems : Advances in Applied Mathematics - Shahab Saquib Sohail
eTextbook alternate format product

Instant online reading.
Don't wait for delivery!

Go digital and save!

AI for Decision Intelligence in Critical Systems

By: Shahab Saquib Sohail (Editor), Arpita Soni (Editor), Satish Mandavalli (Editor)

Hardcover | 3 August 2026 | Edition Number 1

At a Glance

Hardcover


$616.75

or 4 interest-free payments of $154.19 with

 or 

Available: 3rd August 2026

Preorder. Will ship when available.

This book is a multi-disciplinary reference on how domain-aware artificial intelligence (AI) models can outperform generic approaches by addressing sector-specific complexities. It offers comparative frameworks, reproducible case studies, and real-world applications of emerging AI methods.

Collectively, AI for Decision Intelligence in Critical Systems emphasizes a unifying theme: the effective deployment of AI to strengthen decision-making, enhance system reliability, and mitigate risks in domains where precision, trust, and efficiency are critical.

This edited volume brings together twenty-one chapters of original research, each exploring how AI, machine learning (ML), and deep learning (DL) are shaping innovation across critical domains. The book highlights the application of advanced architecturesâ"including Convolutional Neural Networks (CNNs), Quaternion Neural Networks (QCNNs), Large Language Models (LLMs), and Gradient-Boosted Decision Trees (GBDTs)â"to solve complex, domain-specific challenges.

Concerning computer vision and infrastructure safety, chapters discuss the use of CNNs and QCNNs for automated road crack detection, offering scalable approaches to improving transportation safety while reducing dependence on manual inspections. With regard to software engineering, contributions focus on leveraging ML, DL, and LLMs to enhance software quality assurance, minimize defects, and improve resilience in high-stakes industries. Additional chapters examine ML-driven methods, particularly GBDT, to uncover non-linear drivers of equity valuation across sectors, supporting more accurate forecasts and risk-sensitive decision-making.

Academics and researchers in computer science, AI, and data science, industry professionals in transportation, software engineering, finance, and policymakers seeking to apply AI systems effectively will find this book useful.

More in Mathematics

The Infinite Game : From the bestselling author of Start With Why - Simon Sinek
The Art of Gathering : How We Meet and Why It Matters - Priya Parker
Humble Pi : A Comedy of Maths Errors - Matt Parker

RRP $26.99

$22.99

15%
OFF
The Score : How to Stop Playing Someone Else's Game - C. Thi Nguyen
Antifragile : Things That Gain from Disorder - Nassim Nicholas Taleb

RRP $27.99

$23.75

15%
OFF
Statistics and Data Handling for Biologists : A Student's Guide - Neil Millar
Microsoft Power BI For Dummies : For Dummies (Computer/Tech) - Jack A. Hyman