Nature-Inspired Algorithms and Applications

The book "Nature-Inspired Algorithms and Applications" provides a unified approach to balancing algorithm introduction, theoretical background, and practical implementation, with well-chosen case studies to illustrate how these algorithms work. It covers various nature-inspired algorithms and their multidisciplinary applications in data analytics, pattern recognition, mechanical engineering, electrical engineering, machine learning, image processing, data mining, and wireless networks. The book is a handy reference guide for researchers and graduate students in these fields.

Format: Hardback
Length: 384 pages
Publication date: 14 December 2021
Publisher: John Wiley & Sons Inc

Nature-inspired algorithms and their applications have gained significant attention in recent years, driven by the desire to harness the power of nature for solving complex problems. This book takes a unified approach to balancing algorithm introduction, theoretical background, and practical implementation, providing a comprehensive resource for researchers and practitioners alike.

Inspired by the wonders of the natural world, researchers are actively gathering information that can be developed for practical applications in various fields. This book aims to enhance the readers understanding of this process by showcasing specific nature-inspired algorithms (NIAs) designed to tackle complex real-world problems in data analytics and pattern recognition.

The book covers a wide range of NIAs and their multidisciplinary applications in mechanical engineering, electrical engineering, machine learning, image processing, data mining, and wireless networks. Each chapter delves into detailed discussions of these topics, offering valuable insights and practical examples.

One of the key features of this book is its novel method based on TRIZ (Technique for Innovation) to map real-world problems to nature problems. This approach allows researchers to find innovative solutions by drawing inspiration from the natural world's mechanisms and processes.

The cuckoo search algorithm is another prominent nature-inspired algorithm discussed in the book. It is known for its efficient search capabilities and has been applied to optimization problems, such as finding the best solution in a complex search space.

Performance analysis of nature-inspired algorithms is also covered, with a focus on their effectiveness in breast cancer diagnosis. By leveraging the unique properties of nature, these algorithms can provide accurate and reliable diagnoses, potentially improving patient outcomes.

Nature-inspired computation in data mining is another area explored in the book. By leveraging the principles of biological systems, NIAs can efficiently analyze large datasets and extract valuable insights. This has significant implications in various industries, such as finance, healthcare, and marketing.

Hybrid bat-genetic algorithm-based novel optimal wavelet filter for compression of image data is another exciting application discussed in the book. This algorithm combines the strengths of bat-genetic algorithm and wavelet transform to achieve efficient image compression, which is crucial in various image processing applications, such as medical imaging and surveillance.

Efficiency of finding best solutions through ant colony optimization techniques is also explored in the book. Ant colony optimization is a nature-inspired algorithm that mimics the behavior of ants in finding food sources. It has been applied to various problems, including optimization, scheduling, and routing, and has shown promising results.

Applications of hybridized algorithms and novel algorithms in the field of machine learning are also covered in the book. Machine learning is a rapidly evolving field that relies on algorithms to analyze and interpret data. By incorporating nature-inspired principles, researchers can develop more efficient and effective machine learning models that can solve complex problems.

Overall, this book is a valuable resource for researchers and graduate students in mechanical engineering, electrical engineering, machine learning, image processing, data mining, and wireless networks. It provides a comprehensive overview of nature-inspired algorithms and their applications, offering insights and practical examples that can be applied in real-world scenarios.

The audience for this book includes researchers and graduate students who are interested in exploring the potential of nature-inspired algorithms and their multidisciplinary applications. The book is designed to provide a solid foundation for understanding the principles and techniques of NIAs, enabling readers to develop innovative solutions to complex problems.

Weight: 656g
Dimension: 238 x 151 x 25 (mm)
ISBN-13: 9781119681748