ABSTRACT
This chapter proposes a framework of reinforcement learning (RL) with generalized optimal wavelet decomposing algorithm (GOWDA) system that can decompose noise intelligently from signals with wavelet transformation and preserve information automatically. Industry 4.0 marks a new era of automation and data exchange that integrates cyber-physical systems, information and communication technology, and cloud computing in manufacturing. Web 4.0 is also known as symbiotic web that enables interaction between humans and machines in symbiosis. Business intelligence and analytics (BI&A) has emerged as an important area reflecting the magnitude and impact of data-related problems to be solved in contemporary business organizations. Machine learning, meanwhile, uses an inductive approach to form a representation of the world based on the data it sees. RL (Reinforcement learning) takes actions toward a specified goal, that is, the value functions are formalized. The chapter considers a simulation study to investigate the performance of the proposed algorithm.
