Sachin Sharma – författare

This new volume explores the overlapping behavior of some aspects of computational science, focusing on the intersection of computing hardware, algorithms, mathematics, and data management components. The chapters discuss the various application areas of the computational science techniques such as artificial intelligence, machine learning, data science, quantum computing, image processing, evolutionary algorithms, process simulation, deep learning, big data analysis, etc.

This new volume explores the overlapping behavior of some aspects of computational science, focusing on the intersection of computing hardware, algorithms, mathematics, and data management components. The chapters discuss the various application areas of the computational science techniques such as artificial intelligence, machine learning, data science, quantum computing, image processing, evolutionary algorithms, process simulation, deep learning, big data analysis, etc.

The book’s unified approach of balancing algorithm introduction, theoretical background and practical implementation, complements extensive literature with well-chosen case studies to illustrate how these algorithms work.

Inspired by the world around them, researchers are gathering information that can be developed for use in areas where certain practical applications of nature-inspired computation and machine learning can be applied. This book is designed to enhance the reader’s understanding of this process by portraying certain practical applications of nature-inspired algorithms (NIAs) specifically designed to solve complex real-world problems in data analytics and pattern recognition by means of domain-specific solutions. Since various NIAs and their multidisciplinary applications in the mechanical engineering and electrical engineering sectors; and in machine learning, image processing, data mining, and wireless networks are dealt with in detail in this book, it can act as a handy reference guide.

Among the subjects of the 12 chapters are:

Audience: Researchers and graduate students in mechanical engineering, electrical engineering, machine learning, image processing, data mining, and wireless networks will find this book very useful.

The book’s unified approach of balancing algorithm introduction, theoretical background and practical implementation, complements extensive literature with well-chosen case studies to illustrate how these algorithms work.

Inspired by the world around them, researchers are gathering information that can be developed for use in areas where certain practical applications of nature-inspired computation and machine learning can be applied. This book is designed to enhance the reader’s understanding of this process by portraying certain practical applications of nature-inspired algorithms (NIAs) specifically designed to solve complex real-world problems in data analytics and pattern recognition by means of domain-specific solutions. Since various NIAs and their multidisciplinary applications in the mechanical engineering and electrical engineering sectors; and in machine learning, image processing, data mining, and wireless networks are dealt with in detail in this book, it can act as a handy reference guide.

Among the subjects of the 12 chapters are:

Audience: Researchers and graduate students in mechanical engineering, electrical engineering, machine learning, image processing, data mining, and wireless networks will find this book very useful.

Discusses the impact of AI on organizational transformation which is a mix of computational techniques and management practices, with in-depth analysis about the role of automation & data management, and strategic management in relation to human capital, procurement & production, finance, and marketing.

The impact of AI in restructuring organizational processes is a combination of management practices and computational technology. This book covers the areas like artificial intelligence & its impact on professions, as well as machine learning algorithms and technologies. The context of applications of AI in business process innovation primarily includes new business models, AI readiness and maturity at the organizational, technological, financial, and cultural levels. The book has extensive details on machine learning and the applications such as robotics, blockchain, Internet of Things. Also discussed are the influence of AI on financial strategies and policies, human skills & values, procurement innovation, production innovation, AI in marketing & sales platforms.

Audience

Readers include those working in artificial intelligence, business management studies, technology engineers, senior executives, and human resource managers in all types of business.

Discusses the impact of AI on organizational transformation which is a mix of computational techniques and management practices, with in-depth analysis about the role of automation & data management, and strategic management in relation to human capital, procurement & production, finance, and marketing.

The impact of AI in restructuring organizational processes is a combination of management practices and computational technology. This book covers the areas like artificial intelligence & its impact on professions, as well as machine learning algorithms and technologies. The context of applications of AI in business process innovation primarily includes new business models, AI readiness and maturity at the organizational, technological, financial, and cultural levels. The book has extensive details on machine learning and the applications such as robotics, blockchain, Internet of Things. Also discussed are the influence of AI on financial strategies and policies, human skills & values, procurement innovation, production innovation, AI in marketing & sales platforms.

Audience

Readers include those working in artificial intelligence, business management studies, technology engineers, senior executives, and human resource managers in all types of business.