
Автор: Tin-Chih Toly Chen
Издательство: Springer
Год: 2023
Страниц: 110
Язык: английский
Формат: pdf (true), epub
Размер: 17.5 MB
This book provides a comprehensive overview of the latest developments in Explainable AI (XAI) and its applications in manufacturing. It covers the various methods, tools, and technologies that are being used to make AI more understandable and communicable for factory workers. With the increasing use of AI in manufacturing, there is a growing need to address the limitations of advanced AI methods that are difficult to understand or explain to those without a background in AI. This book addresses this need by providing a systematic review of the latest research and advancements in XAI specifically tailored for the manufacturing industry. Artificial Intelligence (AI) are technologies that enable computers to imitate human behavior. The computing speed, storage capacity, reliability, and interconnectivity of computers combined with human reasoning patterns give AI the ability to solve complex and large-scale problems. Explainable Artificial Intelligence (XAI) is a new trend in AI. We first introduce XAI tools for visualizing operations in ANNs (or DNNs), such as ConvNetJS, TensorFlow, Seq2Seq, and MATLAB, and then mention XAI techniques for evaluating the effect, contribution, or importance of each input on the output, including partial derivation, odd ratio, out-of-bag (OOB) predictor importance, recursive feature elimination (RFE), and SHAP.