Results 41 to 50 of about 375,352 (295)
Combining Fuzzy C-Means Clustering with Fuzzy Rough Feature Selection
Applied Sciences, 2019 With the rapid development of the network, data fusion becomes an important research hotspot. Large amounts of data need to be preprocessed in data fusion; in practice, the features of datasets can be filtered to reduce the amount of data.
Ruonan Zhao, Lize Gu, Xiaoning Zhu
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Remote Assessment of Ataxia Severity in SCA3 Across Multiple Centers and Time Points
Annals of Clinical and Translational Neurology, EarlyView.ABSTRACT Objective Spinocerebellar ataxia type 3 (SCA3) is a genetically defined ataxia. The Scale for Assessment and Rating of Ataxia (SARA) is a clinician‐reported outcome that measures ataxia severity at a single time point. In its standard application, SARA fails to capture short‐term fluctuations, limiting its sensitivity in trials.
Marcus Grobe‐Einsler +20 more
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Fuzzy Logic in KNIME – Modules for Approximate Reasoning – [PDF]
International Journal of Computational Intelligence SystemsIn this paper we describe the open source data analytics platform KNIME, focusing particularly on extensions and modules supporting fuzzy sets and fuzzy learning algorithms such as fuzzy clustering algorithms, rule induction methods, and interactive ...
MichaelR. Berthold +2 more
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FP-Conv-CM: Fuzzy Probabilistic Convolution C-Means
Mathematics, 2023 Soft computing models based on fuzzy or probabilistic approaches provide decision system makers with the necessary capabilities to deal with imprecise and incomplete information.
Karim El Moutaouakil +3 more
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Arthritis Care &Research, Accepted Article.Objectives Sjögren's disease is an autoimmune disorder that can impact multiple organ systems, including the peripheral nervous system (PNS). PNS manifestations, which can exist concurrently, include mononeuropathies, polyneuropathies, and autonomic nervous system neuropathies. To help patients and providers in the decision‐making process, we developed
Anahita Deboo +19 more
wiley +1 more source
A New Modified Technique to Identify Outlier Values Using Fuzzy Clustering [PDF]
مجلة جامعة الانبار للعلوم الصرفةOutliers within a dataset are data points that substantially differ from the rest of the data. These atypical data points can be attributed to a range of factors, such as errors in measurement, issues with data input, and natural variations in the data ...
Wafaa Hasanain, Saja Sakran
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Approximating a similarity matrix by a latent class model: A reappraisal of additive fuzzy clustering [PDF]
, 2009 Let Q be a given n×n square symmetric matrix of nonnegative elements between 0 and 1, similarities. Fuzzy clustering results in fuzzy assignment of individuals to K clusters.
Bink, M.C.A.M. +3 more
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Current Tracking Adaptive Control of Brushless DC Motors
International Journal of Adaptive Control and Signal Processing, EarlyView.In this paper, the current tracking for Brushless Direct Current motors is approached considering uncertainty in the parameters of the motor's model. An adaptive control scheme to compensate electrical parameters uncertainty is proposed without requiring any knowledge of the mechanical parameters.
Fernanda Ramos‐García +3 more
wiley +1 more source
Fuzzy Information and EngineeringSemi-supervised clustering (SSC) methods have emerged as a notable research area in machine learning. These methods integrate prior knowledge of class distribution into their clustering process.
Shirin Khezri +3 more
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Priority Road Restoration Classification Using Fuzzy C-Means: A Case Study In Samarinda City
Jurnal Teknologi dan Sistem Komputer, 2017 One of the factors traffic accidents is caused by a damaged road. Therefore, road improvements based on the priorities scale is indispensable. This study implements the Fuzzy C-means method.
Novianti Puspitasari +2 more
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