Results 1 to 10 of about 2,525,373 (192)
Improved Random Forest Algorithm Based on Decision Paths for Fault Diagnosis of Chemical Process with Incomplete Data [PDF]
Sensors, 2021 Fault detection and diagnosis (FDD) has received considerable attention with the advent of big data. Many data-driven FDD procedures have been proposed, but most of them may not be accurate when data missing occurs.
Yuequn Zhang, Lei Luo, Xu Ji, Yiyang Dai
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MODIFIED POSSIBILISTIC FUZZY C-MEANS ALGORITHM FOR CLUSTERING INCOMPLETE DATA SETS
Acta Polytechnica, 2021 A possibilistic fuzzy c-means (PFCM) algorithm is a reliable algorithm proposed to deal with the weaknesses associated with handling noise sensitivity and coincidence clusters in fuzzy c-means (FCM) and possibilistic c-means (PCM).
Rustam +7 more
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A Fuzzy C-means Algorithm for Clustering Fuzzy Data and Its Application in Clustering Incomplete Data [PDF]
Journal of Artificial Intelligence and Data Mining, 2020 The fuzzy c-means clustering algorithm is a useful tool for clustering; but it is convenient only for crisp complete data. In this article, an enhancement of the algorithm is proposed which is suitable for clustering trapezoidal fuzzy data.
J. Tayyebi, E. Hosseinzadeh
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Forecasting, 2021 This article considers the estimation of Approximate Dynamic Factor Models with homoscedastic, cross-sectionally correlated errors for incomplete panel data.
Monica Defend +5 more
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Relating incomplete data and incomplete theory [PDF]
Physical Review D, 2004 43 pages, 1 ...
Binetruy, P. +4 more
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On Classification with Incomplete Data [PDF]
IEEE Transactions on Pattern Analysis and Machine Intelligence, 2007 We address the incomplete-data problem in which feature vectors to be classified are missing data (features). A (supervised) logistic regression algorithm for the classification of incomplete data is developed. Single or multiple imputation for the missing data is avoided by performing analytic integration with an estimated conditional density function
David Williams +4 more
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A Combined Residual Detection Method of Reaction Wheel for Fault Detection
Shanghai Jiaotong Daxue xuebao, 2021 A fault detection method of combined residual is proposed to effectively master the health state of the reaction wheels of in-orbit satellite according to the telemetry data. Based on the characteristics of in-orbit telemetry data, in the proposed method,
HE Xiawei, CAI Yunze, YAN Lingling
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Placement with Incomplete Data [PDF]
VLSI Design, 1998 Traditional placement problems are studied under a fully specified cell library and a complete netlist. However, in the first, e.g., 2 years of a 2 – 3 year microprocessor design cycle, the detailed netlist is unavailable. For area and performance estimation, layout must nevertheless be done with incomplete information. Another source of incompleteness
Maogang Wang +2 more
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Partial Convolutional LSTM for Spatiotemporal Prediction of Incomplete Data
IEEE Access, 2020 Advanced data analysis techniques facilitate data-driven spatiotemporal prediction in various fields. However, in real-world data, missing values are inevitable, which causes the data incomplete and makes predictions more challenging.
Hyesook Son, Yun Jang
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RELIABILITY MODELING BASED ON INCOMPLETE DATA: OIL PUMP APPLICATION [PDF]
Management Systems in Production Engineering, 2014 The reliability analysis for industrial maintenance is now increasingly demanded by the industrialists in the world. Indeed, the modern manufacturing facilities are equipped by data acquisition and monitoring system, these systems generates a large ...
Ahmed HAFAIFA +2 more
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