Results 1 to 10 of about 1,015,115 (264)
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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Frontiers in Neuroinformatics, 2022 Multimodality neuroimages have been widely applied to diagnose mild cognitive impairment (MCI). However, the missing data problem is unavoidable. Most previously developed methods first train a generative adversarial network (GAN) to synthesize missing ...
Leiming Jin +5 more
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Vietnam Journal of Computer Science, 2023 In intelligent information systems data play a critical role. The issue of missing data is one of the commonplace problems occurring in data collected in the real world. The problem stems directly from the very nature of data collection.
Mateusz Szczepański +3 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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Ensemble-based Top-k Recommender System Considering Incomplete Data [PDF]
Journal of Artificial Intelligence and Data Mining, 2019 Recommender systems have been widely used in e-commerce applications. They are a subclass of information filtering system, used to either predict whether a user will prefer an item (prediction problem) or identify a set of k items that will be user ...
M. Moradi, J. Hamidzadeh
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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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Development of models and assessment of the world walnut variety fund by fruit quality
Новые технологии, 2023 Walnut (Juglans regia L.) is a particularly significant plant for humans in terms of its useful properties and in the Russian Federation it can be attributed to the most valuable introducers for forestry and horticulture. It is grown in many countries of
S. G. Biganova +3 more
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Fuzzy Prognosis System for Decision Making to Vibrations Monitoring in Gas Turbine
Journal of Mechanical Engineering, 2021 This paper proposes a decision making approach based on the development of a fuzzy prognostic system to ensure the vibrations monitoring of a gas turbine based on real time information obtained from different installed sensors.
Boulanouar Saadat +3 more
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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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