Results 231 to 240 of about 9,783,179 (285)

Smart Irrigation with Fuzzy Decision Support Systems in Trentino Vineyards. [PDF]

Sensors (Basel)
Silvestri R, Vecchio M, Pincheira M, Antonelli F.   +3 more
europepmc   +1 more source

A novel q-ROHFS prospect theory based MABAC method for failure mode risk prioritization in aircraft landing systems. [PDF]

Sci Rep
Köseoğlu A, Altun F, Şahin R.
europepmc   +1 more source

Transferable Deep Reinforcement Learning With Edge-Contour-Depth Fusion for Autonomous Wireless Capsule Endoscopy Navigation. [PDF]

Adv Sci (Weinh)
Wu H, Gao H, Liu Q, Yuan S, Fang H, Su M, Liang B, Yang Y, Bai L, Dong W, Xie D, Su S, Lai J, Cheng SS, Li Z, Zuo X, Ren H.   +16 more
europepmc   +1 more source

Optimizing water use efficiency and fruit quality of watermelon under mulched drip irrigation in arid regions. [PDF]

Front Plant Sci
Liu Z, Zhang H, Yu S, Wang Z, Zhou C, Li H.   +5 more
europepmc   +1 more source

Chaos-Embedded Multi-Objective Intelligent Optimization-Based Explainable Classification Model for Determining Cherry Fruit Fly Infestation Levels Using Pomological Data. [PDF]

Biomimetics (Basel)
Yildirim S, Ozgen I, Alatas B, Yildirim H.   +3 more
europepmc   +1 more source

Fuzzy process control: construction of control charts with fuzzy numbers

Fuzzy Sets and Systems, 2005
This paper presents the construction of fuzzy control charts for a process with fuzzy outcomes derived from the subjective quality ratings provided by a group of experts. The proposed fuzzy process control (FPC) methodology comprises an off-line stage and an on-line stage.
Chi-Bin Cheng
exaly   +3 more sources

Fuzzy EWMA and Fuzzy CUSUM Control Charts

Studies in Fuzziness and Soft Computing, 2016
Exponentially Weighted Moving- Averages (EWMA) and Cumulative-Sum (CUSUM) control charts have the ability of detecting small shifts in the process mean. Classical EWMA and CUSUM charts are not capable to capture the uncertainty in case of incomplete data.
Nihal Erginel, Sevil Senturk
exaly   +3 more sources

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An alternative approach to fuzzy control charts: Direct fuzzy approach

Information Sciences, 2007
zbMATH Open Web Interface contents unavailable due to conflicting licenses.
Cengiz Kahraman, Murat Gülbay
exaly   +4 more sources

Fuzzy theory and quality control charts

2017 IEEE International Conference on Fuzzy Systems (FUZZ-IEEE), 2017
Quality control charts are one of the most important tools of statistical process control, used to analyze the behavior of different processes and to predict possible production failures. The use of a fuzzy approach in the design of control charts has allowed to improve the performance of traditional charts, as well as to be possible of a simple ...
Maria Nela Pastuizaca
exaly   +3 more sources

Fuzzy Shewhart Control Charts

Studies in Fuzziness and Soft Computing, 2016
Process Control is the active correction of a process based on the results of process monitoring. Once the process monitoring tools have detected an assignable cause, this cause is removed to bring the process back into control. This chapter presents the process control techniques under fuzziness.
Cengiz Kahraman, Murat Gülbay, Eda Boltürk   +2 more
exaly   +2 more sources