
Nature-inspired Optimization Algorithms and Soft Computing by Rajeev Arya
We have witnessed an explosion of research activity around nature-inspired computing and bio-inspired optimization techniques, which can provide powerful tools for solving learning problems and data analysis in very large data sets. To design and implement optimization algorithms, several methods are used that bring superior performance. However, in some applications, the search space increases exponentially with the problem size. To overcome these limitations and to solve efficiently large scale combinatorial and highly nonlinear optimization problems, more flexible and adaptable algorithms are necessary.
Nature-inspired computing is oriented towards the application of outstanding information-processing aptitudes of the natural realm to the computational domain. The discipline of nature-inspired optimization algorithms is a major field of computational intelligence, soft computing and optimization. Metaheuristic search algorithms with population-based frameworks are capable of handling optimization in high-dimensional real-world problems for several domains including imaging, IoT, smart manufacturing, and healthcare. The integration of intelligence with smart technology enhances accuracy and efficiency. Smart devices and systems are revolutionizing the world by linking innovative thinking with innovative action and innovative implementation.
The aim of this edited book is to review the intertwining disciplines of nature-inspired computing and bio-inspired soft-computing (BISC) and their applications to real world challenges. The contributors cover the interaction between metaheuristics, such as evolutionary algorithms and swarm intelligence, with complex systems. They explain how to better handle different kinds of uncertainties in real-life problems using state-of-art of machine learning algorithms. They also explore future research perspectives to bridge the gap between theory and real-life day-to-day challenges for diverse domains of engineering.
The book will offer valuable insights to researchers and scientists from academia and industry in ICTs, IT and computer science, data science, AI and machine learning, swarm intelligence and complex systems. It is also a useful resource for professionals in related fields, and for advanced students with an interest in optimization and IoT applications.
-
UML for Systems Engineering
-
Generative AI for Multimedia Content Processing, Security and Privacy
-
The Power of Large Language Models and AI in the Digital Age
-
Modelling Enterprise Architectures
-
Knowledge Discovery and Data Mining
-
Generative AI for Sign Language Recognition and Translation
-
Managing Complexity in Software Engineering
-
Semi-custom IC Design and VLSI
-
Ultrascale Computing Systems
-
The Digital Twin Handbook
-
Matrix Factorization for Multimedia Clustering
-
Trustworthy Autonomic Computing
-
AIoT Technologies and Applications for Smart Environments
-
Intelligent Network Design Driven by Big Data Analytics, IoT, AI and Cloud Computing
-
Demystifying Graph Data Science
-
Energy Optimization and Security in Federated Learning for IoT Environments
-
Big Data Recommender Systems
-
Blockchains for Network Security
-
Network Classification for Traffic Management
-
Intelligent Distributed Video Surveillance Systems
-
AI for Emerging Verticals
-
Big Data and Software Defined Networks
-
Security and Privacy for Big Data, Cloud Computing and Applications
-
Intelligent Multimedia Technologies for Financial Risk Management
-
E-learning Methodologies
-
Many-Core Computing
-
Big Data-Enabled Internet of Things
-
Generative AI Unleashed
-
Explainable Artificial Intelligence for Trustworthy Internet of Things
-
Streaming Analytics
-
Edge Computing
-
ReRAM-based Machine Learning
-
Advanced Networking Technologies
-
Virtual Reality and Light Field Immersive Video Technologies for Real-World Applications
-
Federated Learning for Multimedia Data Processing and Security in Industry 5.0
-
Engineering the Metaverse
-
Personal Knowledge Graphs (PKGs)
-
Trusted Platform Modules
-
Explainable Artificial Intelligence (XAI)
-
Earth Observation Data Analytics Using Machine and Deep Learning
-
Graphical Programming Using LabVIEW
-
Computer Vision and Recognition Systems Using Machine and Deep Learning Approaches
-
Managing Internet of Things Applications across Edge and Cloud Data Centres
-
Enabling Technologies for Smart Fog Computing
-
Intelligent Multimedia Processing and Computer Vision
-
Access Control and Security Monitoring of Multimedia Information Processing and Transmission
| SKU | Unavailable |
| ISBN 13 | 9781839535161 |
| ISBN 10 | 1839535164 |
| Title | Nature-inspired Optimization Algorithms and Soft Computing |
| Author | Rajeev Arya |
| Series | Computing And Networks |
| Condition | Unavailable |
| Binding Type | Hardback |
| Publisher | Institution of Engineering and Technology |
| Year published | 2023-10-17 |
| Number of pages | 298 |
| Cover note | Book picture is for illustrative purposes only, actual binding, cover or edition may vary. |
| Note | Unavailable |













































