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Noise Resistant Control Charts for Detecting Periodicity from Correlation

Figshare2025-03-03 更新2026-04-28 收录

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https://figshare.com/articles/dataset/Noise_Resistant_Control_Charts_for_Detecting_Periodicity_from_Correlation/28525364 数据链接链接失效反馈

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Noise Resistant Control Charts for Detecting Periodicity from Correlation

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2025-03-03

农业机械

统计过程控制

ABSTRACT Sugarcane mechanized harvesting can lead to serious risks to the longevity of plantations when improperly operated, and may cause damages and disturbances in the remaining ratoons in the fiel

DataCite Commons2021-03-25 更新120

Reliable Post-Signal Fault Diagnosis for Correlated High-Dimensional Data Streams

高维数据流故障诊断

统计过程控制

Rapid advance of sensor technology is facilitating the collection of high-dimensional data streams (HDS). Apart from real-time detection of potential out-of-control (OC) patterns, post-signal fault di

NIAID Data Ecosystem30

Performance of the mean control charts with generalized sensitizing rules for various probability distribution

统计过程控制

工业质量控制

The current study highlights and resolves the issues of mean control charts with sensitizing rules. The average run length (ARL)-based mean control charts with sensitizing rules involve a restricted a

Taylor & Francis Group2025-06-13 更新20

Run length analysis to evaluate the IBRCC, BRCC, RCC, and IBCC with α = 0.0027.

统计过程控制

控制图性能评估

Run length analysis to evaluate the IBRCC, BRCC, RCC, and IBCC with α = 0.0027.

NIAID Data Ecosystem30

Comparison of the ARL 1 values obtained using the analytical and numerical ARL methods for long-memory SARFIMAX( P , D , Q , r ) s processes with exponential white noise on a CUSUM control chart for ARL 0 = 370 with Φ 1 = 0.1, Φ 2 = 0.2, Θ 1 = 0.1, and ω 1 = 0.5.

统计过程控制

时间序列监控

Comparison of the ARL1 values obtained using the analytical and numerical ARL methods for long-memory SARFIMAX(P, D, Q, r)s processes with exponential white noise on a CUSUM control chart for ARL0 = 3

NIAID Data Ecosystem30

Noise Resistant Control Charts for Detecting Periodicity from Correlation

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