Pijush Dutta – författare

This book is written in a clear and thorough way to cover both the traditional and modern uses of artificial intelligence and soft computing. It gives an in-depth look at mathematical models, algorithms, and real-world problems that are hard to solve in MATLAB. The book is intended to provide a broad and in-depth understanding of fuzzy logic controllers, genetic algorithms, neural networks, and hybrid techniques such as ANFIS and the GA-ANN model.Features:A detailed description of basic intelligent techniques (fuzzy logic, genetic algorithm and neural network using MATLAB)A detailed description of the hybrid intelligent technique called the adaptive fuzzy inference technique (ANFIS)Formulation of the nonlinear model like analysis of ANOVA and response surface methodologyVariety of solved problems on ANOVA and RSMCase studies of above mentioned intelligent techniques on the different process control systemsThis book can be used as a handbook and a guide for students of all engineering disciplines, operational research areas, computer applications, and for various professionals who work in the optimization area.

This book is written in a clear and thorough way to cover both the traditional and modern uses of artificial intelligence and soft computing. It gives an in-depth look at mathematical models, algorithms, and real-world problems that are hard to solve in MATLAB. The book is intended to provide a broad and in-depth understanding of fuzzy logic controllers, genetic algorithms, neural networks, and hybrid techniques such as ANFIS and the GA-ANN model.Features:A detailed description of basic intelligent techniques (fuzzy logic, genetic algorithm and neural network using MATLAB)A detailed description of the hybrid intelligent technique called the adaptive fuzzy inference technique (ANFIS)Formulation of the nonlinear model like analysis of ANOVA and response surface methodologyVariety of solved problems on ANOVA and RSMCase studies of above mentioned intelligent techniques on the different process control systemsThis book can be used as a handbook and a guide for students of all engineering disciplines, operational research areas, computer applications, and for various professionals who work in the optimization area.

We are pleased to present the proceedings of the International Conference on Advanced Data Analytics and Computing (ICADAC) 2025, a premier platform that brings together researchers, scholars, and industry professionals to share their latest findings, technological advancements, and practical applications in the field of data analytics and intelligent computing. ICADAC 2025 has received a remarkable number of high-quality submissions from across the globe, reflecting the growing interest and ongoing innovation in this dynamic domain. After a rigorous peer-review process by our esteemed technical committee, a curated selection of papers has been included in this volume. These contributions span various topics, including machine learning, artificial intelligence, big data processing, cloud computing, Internet of Things (IoT), cybersecurity, and their applications across various sectors including but not limited to Mechanical Engineering, Civil Engineering, Electrical Engineering, Electronics and Communications Engineering, Computer Science Engineering, Information Technology and other interdisciplinary areas

We are pleased to present the proceedings of the International Conference on Advanced Data Analytics and Computing (ICADAC) 2025, a premier platform that brings together researchers, scholars, and industry professionals to share their latest findings, technological advancements, and practical applications in the field of data analytics and intelligent computing. ICADAC 2025 has received a remarkable number of high-quality submissions from across the globe, reflecting the growing interest and ongoing innovation in this dynamic domain. After a rigorous peer-review process by our esteemed technical committee, a curated selection of papers has been included in this volume. These contributions span various topics, including machine learning, artificial intelligence, big data processing, cloud computing, Internet of Things (IoT), cybersecurity, and their applications across various sectors including but not limited to Mechanical Engineering, Civil Engineering, Electrical Engineering, Electronics and Communications Engineering, Computer Science Engineering, Information Technology and other interdisciplinary areas

The book provides an essential overview of AI techniques in disease management and how these computational methods can lead to further innovations in healthcare. Design and Forecasting Models for Disease Management is a resourceful volume of 13 chapters that elaborates on computational methods and how AI techniques can aid in smart disease management. It contains several statistical and AI techniques that can be used to acquire data on many different diseases. The main objective of this book is to demonstrate how AI techniques work for early disease detection and forecasting useful information for medical experts. As such, this volume intends to serve as a resource to elicit and elaborate on possible intelligent mechanisms for helping detect early signs of diseases. Additionally, the book examines numerous machine learning and data analysis techniques in the biomedical field that are used for detecting and forecasting disease management at the cellular level. It discusses various applications of image segmentation, data analysis techniques, and hybrid machine learning techniques for illnesses, and encompasses modeling, prediction, and diagnosis of disease data. Audience Researchers, engineers and graduate students in the fields of computational biology, information technology, bioinformatics, and epidemiology.