Practical Graph Intelligence 2

Network Algorithms and Python in Practice

Pramod Singh Rathore, Abhishek Kumar, Priya Batta, Inam Ul Haq

• Publisher: Wiley-ISTE
• Year: 2026
• Print ISBN:
  9781836691624
• Edition: 1
• eBook ISBN:
  9781394479856
• Topic: Computer Science
• Subtopic: Computer Engineering
• Index: Computer Science

Practical Graph Intelligence 2 delivers a comprehensive and application driven exploration of graph-based methods for understanding complex, interconnected data.

This book bridges theory and practice by presenting advanced techniques in graph theory, graph neural networks and network analytics, with a strong focus on real-world implementation. It addresses critical challenges such as scalability, interpretability and dynamic data handling while showcasing applications across healthcare, cybersecurity, social networks and smart systems.

Designed for researchers, practitioners and advanced students, this book highlights emerging trends and practical frameworks that enable efficient, data-driven decision-making. By integrating cutting-edge research with hands-on perspectives, it serves as a valuable resource for developing robust and intelligent graph-based solutions in today's data intensive environments.

Table of contents

• Cover
• Table of Contents
• Title Page
• Copyright Page
• Preface
• Introduction
• 1 Convolutional Neural Networks with Recurrent Layers for Network Intrusion Classification Using NSL-KDD Dataset
• 2 Spectral Graph Convolutional Networks for IoT Device Clustering and Anomalous Node Detection in Complex Network Topologies
• 3 Graph Intelligence-enhanced Quantum-Inspired Hybrid Algorithms for Black–Litterman Portfolio Optimization with Value-at-Risk Constraints
• 4 Graph Intelligence-Assisted Variational Autoencoders and Monte Carlo Simulations for Financial Risk Assessment in the Quantum Computing Era
• 5 Auto-Regressive Integrated Moving Average (ARIMA) with Exogenous Variables and Fourier Features for Stock Volatility Prediction in Graph-Based Financial Networks
• 6 Geometric Brownian Motion and Cox–Ingersoll–Ross Models: Jump-Diffusion Processes in Graph-based Queueing Theory for Network Performance Analysis
• 7 Enhancing Financial Fraud Detection by Leveraging Llama2 NLP and Neo4j Graph Database for Contextual Analysis and Relationship Modeling
• 8 Digital Finance and Financial Inclusion in India: Opportunities and Challenges
• 9 Graph Intelligence-driven Early Risk Prediction in Autistic Children Using Multimodal Neuroimaging (fMRI, sMRI and EEG)
• 10 Susceptible–Infected–Recovered (SIR) Models with Stochastic Differential Equations: Parameter Estimation via Kalman Filtering for Graph-based Epidemic Spread Analysis
• 11 Distributed MapReduce and RDD Abstractions in Apache Spark: Scalable Graph Processing for Petabyte-Scale Datasets
• 12 Beam Processing with Watermarking and Windowing Strategies in Apache Flink for Unbounded Stream Analysis
• 13 PageRank Algorithm Enhanced with Spectral Graph Theory for Multi-Layer Network Optimization in 5G Infrastructure
• 14 Graph Intelligence-enabled AI-driven Multiscale Computational Fluid Dynamics Framework for Predicting Heat and Mass Transfer in Microfluidic Channels Using Hybrid Nano-enhanced Fluids Under Transient Flow Conditions
• 15 AI-enabled Prediction and Inverse Design of Micro-Nano Scale Convective Heat and Mass Transfer Using Physics-informed Neural Networks Integrated with High-Fidelity Nanofluid CFD Simulations
• 16 Intelligent CFD–AI Hybrid Modeling of Multiphase Nanofluid Dynamics in Microfluidic Devices for Ultra-efficient Thermal Management, Energy Harvesting and Advanced Bio-thermal Applications
• 17 Graph Intelligence-enabled Precision Agriculture: Advanced Disease Detection System for Sugarcane Crops Using Intelligent Image Processing
• List of Authors
• Index
• Other titles from ISTE in Computer Engineering
• End User License Agreement