Titlebook: Intelligent Decision Making in Quality Management; Theory and Applicati Cengiz Kahraman,Seda Yanik Book 2016 Springer International Publish

LEERY

thrombus

Fallibility

Process Improvement Using Intelligent Six Sigma,ging conditions. The purpose of this chapter is to extend understanding of what performance measures can be applied to processes in order to gain useful information and the emerging application of artificial neural networks to handle concurrent multiple feedback loops.

plasma-cells

Key-Driver Analysis with Extended Back-Propagation Neural Network Based Importance-Performance Analred to traditional approaches. This chapter describes the application of back-propagation neural networks (BPNN) in an extended IPA framework with the goal of discovering key areas of quality improvements. The value of the extended BPNN-based IPA is demonstrated using an empirical case example of airport service quality.

漂亮才會豪華

1868-4394 gement broadly.Introduces new intelligent solution approache.?..This book presents recently developed intelligent techniques with applications and theory in the area of quality management. The involved applications of intelligence include techniques such as fuzzy sets, neural networks, genetic algor

Pelvic-Floor

1868-4394 oblems. The book will serve as an excellent reference for quality managers, researchers, lecturers and postgraduate students in this area. The authors of the chapters are well-known researchers in the area of quality management...?.978-3-319-34317-4978-3-319-24499-0Series ISSN 1868-4394 Series E-ISSN 1868-4408

浮雕

短程旅游

Software Architecture Quality of Service Analysis Based on Optimization Models,tecture based on optimization models. A particular emphasis will be given to two aspects of this problem: (i) the mathematical foundations of QoS tradeoffs and their dependencies on the static and dynamic aspects of a software architecture, and (ii) the automation of architectural decisions driven by optimization models for QoS tradeoffs.

Perceive

保全

,Intelligent Process Control Using Control Charts—I: Control Charts for Variables,ar fuzzy numbers have been used in the development of these charts. Unnatural patterns have been examined under fuzziness. Besides, fuzzy EWMA charts have been also developed in this chapter. For each fuzzy case, we present a numerical example.