Titlebook: Explainable Artificial Intelligence (XAI) in Manufacturing; Methodology, Tools, Tin-Chih Toly Chen Book 2023 The Editor(s) (if applicable)

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书目名称Explainable Artificial Intelligence (XAI) in Manufacturing影响因子(影响力)




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书目名称Explainable Artificial Intelligence (XAI) in Manufacturing网络公开度学科排名




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书目名称Explainable Artificial Intelligence (XAI) in Manufacturing被引频次学科排名




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书目名称Explainable Artificial Intelligence (XAI) in Manufacturing读者反馈学科排名

invulnerable

Explainable Artificial Intelligence (XAI) in ManufacturingMethodology, Tools,

MELD

https://doi.org/10.1007/978-94-009-0027-1ention XAI techniques for evaluating the impact, contribution, or importance of each input on the output, including partial derivatives, odd ratio, out-of-bag (OOB) predictor importance, recursive feature elimination (RFE), Shapely additive explanation value (SHAP). Subsequently, XAI techniques for

Minikin

https://doi.org/10.1007/978-3-642-59692-6as established to guide the group multi-criteria decision-making process. Applications of AI and XAI to identify targets are first reviewed. Subsequently, the application of AI and XAI to selection factors and development of criteria is presented. Artificial intelligence techniques are widely used t

reception

Taxation, Production, and Redistribution,Furthermore, job sequencing and scheduling problems are often formulated as mathematical programming (optimization) models to be optimized. AI technologies can be applied to find the best solution for the model. Applications of genetic algorithm (GA) are of particular interest because such applicati

insincerity

Applications of XAI for Forecasting in the Manufacturing Domain,ention XAI techniques for evaluating the impact, contribution, or importance of each input on the output, including partial derivatives, odd ratio, out-of-bag (OOB) predictor importance, recursive feature elimination (RFE), Shapely additive explanation value (SHAP). Subsequently, XAI techniques for

insincerity

大酒杯

Applications of XAI to Job Sequencing and Scheduling in Manufacturing,Furthermore, job sequencing and scheduling problems are often formulated as mathematical programming (optimization) models to be optimized. AI technologies can be applied to find the best solution for the model. Applications of genetic algorithm (GA) are of particular interest because such applicati

audiologist

2191-530X .Contains real case studies and related research results.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

混杂人

Raymond DiGiuseppe,Cindy Ellen Lig are reviewed, including explaining the classification process and results of factory jobs, explaining artificial neural network (ANN)-based cycle time prediction methods, comparing the effect of alloy composition using Shapely additive explanation value (SHAP) analysis, etc.