Transparent Knowledge Discovery from Data

With the rapid development in the human capabilities to both generate and collect data, the discovery of knowledge from data has become a practical and popular research topic. In this book, the knowledge discovery from data is conducted from two overarching viewpoints: first, developing transparent prediction models from the data that represent input-output relationships using a cooperative fuzzy modelling framework; second, based on these developed models, finding the optimal designs (solutions) to achieve a set of predefined objectives using nature-inspired optimisation algorithms. The theoretical aspects behind these two research facets are described and the associated experimental studies are also carried out. This book is therefore addressed to the researchers and practitioners, who are interested in nature-inspired computation and systems modelling with intelligent systems.

Autorentext

Dr Qian Zhang, BEng (Zhejiang University, 2003), PhD (University of Sheffield, 2008), MIET, MIEEE; Research Interests: Nature-Inspired Computation, Evolutionary Computation, Multi-Objective Optimisation, Intelligent Systems and Data-Driven Modelling; Postdoctoral Research Associate at the University of Sheffield, UK.