**4. Case Studies**

In this section, the effectiveness and the superiority of the designed local densitybased abnormal case removal method were validated by two case studies. Firstly, a numerical simulation was designed, where case descriptions were featured with multiple working conditions and measurement error. Then, an industrial case study, whose data were collected from a cut-made process of cigarette production, was designed to show the effectiveness and the superiority of the abnormal case removal method in industrial operation optimization under the CBR framework. In these case studies, the proposed method was compared with classic CBR and case-based fuzzy reasoning in which the fuzzy membership function and its parameters were determined according to their ability to resist measuring error [18]. The concrete hardware and software are as follows: Intel(R) Core (TM) i5-4590, ROM 8 GB, Windows 10 professional.
