Data Driven Techniques for Advanced Process Monitoring and Supervision

Due to advances in information science and technology in the last decades, we are passing through an era of information explosion and globalization, which has led to the problem of information overloading. At the same time, researches in different area are maturing and a race for knowledge has begun in which boundaries between different disciplines have narrowed. These days interdisciplinary research is very common and involves two fields embedded together to deal with the complexity and sheer quantum of information. This book examines different data-driven techniques for utilization of available data to infer useful information about the state of the systems and processes. Several novel techniques such as Radial Basis based Nonlinear Feature Extraction, Modular Fuzzy Net and Self-Organizing Self-Clustering Network are proposed in this book. These techniques are amalgamation of several existing techniques and utilize their important features to facilitate proactive identification, detection and diagnosis of any abnormal situations.