Short-term prediction method of oblique sounding ionosphere MUF based on robust Kalman filter by Guojun LI, Guangfa ZHENG, Changrong YE, Yinping ZHOU

“…To improve the low accuracy of ionospheric frequency forecasting, poor HF communication connectivity, and the severe impact of observational outliers in engineering on forecast accuracy, a short-term prediction method for oblique detection ionospheric MUF based on robust Kalman filtering was proposed.By studying the variation law of the measured MUF data and the causes as well as characteristics of observation errors, and exploiting the ionospheric reference model as a priori information, the state estimation equation of the Kalman filter model was improved.The cost function mechanism was introduced to realize the measurement update of the forecast state through Huber-M estimation, which reduced the influence of the observation outliers on the forecast results and improves the robustness of the proposed method.The simulation results show that the proposed method can effectively suppress the adverse effects caused by the observation outliers and has good robustness and stability.…”
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New Robust Principal Component Analysis for Joint Image Alignment and Recovery via Affine Transformations, Frobenius and L2,1 Norms by Habte Tadesse Likassa

“…The existing algorithms still lack in dealing with the potential impact of outliers and heavy sparse noises for image alignment and recovery. …”
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Robust Stability Best Subset Selection for Autocorrelated Data Based on Robust Location and Dispersion Estimator by Hassan S. Uraibi, Habshah Midi, Sohel Rana

“…Unfortunately, this procedure yields very poor results in the presence of outliers and other contamination in the original data. …”
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A Robust k-Means Clustering Algorithm Based on Observation Point Mechanism by Xiaoliang Zhang, Yulin He, Yi Jin, Honglian Qin, Muhammad Azhar, Joshua Zhexue Huang

“…The k-means algorithm is sensitive to the outliers. In this paper, we propose a robust two-stage k-means clustering algorithm based on the observation point mechanism, which can accurately discover the cluster centers without the disturbance of outliers. …”
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A robust transfer learning approach for high-dimensional linear regression to support integration of multi-source gene expression data. by Lulu Pan, Qian Gao, Kecheng Wei, Yongfu Yu, Guoyou Qin, Tong Wang

“…However, heavy-tail distribution and outliers are common in genomics data, which poses challenges to the effectiveness of current transfer learning approaches. …”
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An optimized data analytics pipeline for improving healthcare diagnosis using ensemble learning by Lomat Haider Chowdhury, Shaira Tabassum, Swakkhar Shatabda, Ashir Ahmed

“…An excessive number of outliers may lead to a skewed and incorrect prediction. …”
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Estimating Systematic Risk: Case For Borsa Istanbul by Filiz Yeşilyurt, Hakan Aygören, M.ensar Yeşilyurt

“…Especially the methods, which are affected by outliers like Ordinary Least Squares OLS , will lead to biased results. …”
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‘What perversity is this?’: Dickens, Emily Brontë, and A [Twisted] Christmas Carol by André L. DeCuir

“…The paper argues that Emily Brontë’s Wuthering Heights holds up a ‘glass darkly’ to Dickens’s A Christmas Carol, amplifying the dark elements of humanity which Dickens would acknowledge more and more in later novels. …”
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Distributed robust RLS estimation algorithm over sensor networks by Kaikai KANG, Zhaoting LIU, Yingbiao YAO

“…In the parameter estimation of the sensor network, there may be impact noise or pulse interference in the measurement environment, which leads to the outliers that greatly deviate from the actual range, so that the effective parameter estimation problem can't be obtained. …”
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Robust kernel extreme learning machines for postgraduate learning performance prediction by Hongxing Gao, Tianzi Xu, Nan Zhang

“…In order to mitigate the impact of outliers, we propose a novel kernel extreme learning machine model that is robust to outliers and name it a robust kernel extreme learning machine (RK-ELM). …”
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A Partial Robust M-Regression-Based Prediction and Fault Detection Method by Jianfang Jiao, Jingxin Zhang, Hamid Reza Karimi

“…However, like many data-based methods, PLS is quite sensitive to outliers, which is a common abnormal characteristic of the measured process data that can significantly affect the monitoring performance of PLS. …”
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Stability analysis of parameters of the GDP components models by Bronislava Kaminskienė, Vitalija Avdejenkova

“…Exceptions are only the time series where residuals had outliers. Suggestion is to evaluate outliers prior to parameters estimation. …”
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Bounded multivariate contaminated normal mixture model with applications to skin cancer detection by Abbas Mahdavi

“… Background & Aim: In real-world datasets, outliers are a common occurrence that can have a significant impact on the accuracy and reliability of statistical analyses. …”
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Research on House Price Prediction based on Machine Learning by Yang Xiangjun

“…Linear regression models are simple and easy to interpret, but may not be accurate enough when dealing with nonlinear relationships and outliers. The advantages of random forests are reflected in higher predictive accuracy, robustness to outliers, and the ability to handle interactions between variables automatically.…”
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New Fuzzy Support Vector Machine for the Class Imbalance Problem in Medical Datasets Classification by Xiaoqing Gu, Tongguang Ni, Hongyuan Wang

“…However, most of the real-world medical datasets usually contain some outliers/noise and data often have class imbalance problems. …”
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Paysage digital : une expérimentation visuelle du sensible sur la Goule aux fées by Corinne Feïss-Jehel, Pierre-Jérôme Jehel

“…It involves a project entitled "Une origine du monde des images. La caverne des Lumière" (An Origin of the World of Images. The Cavern of Light), and a digital series. …”
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A Fuzzy Similarity Elimination Algorithm for Indoor Fingerprint Positioning by Yongle Chen, Wei Liu, Yongping Xiong, Jing Duan, Zhi Li, Hongsong Zhu

“…Due to the K -Means+ algorithm failing to locate the positions of outliers, we also designed a linear sequence matching algorithm to improve the outliers positioning, and reduce the impact of fuzzy similarity. …”
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Subspace Clustering of High-Dimensional Data: An Evolutionary Approach by Singh Vijendra, Sahoo Laxman

“…Our results indicate that removing outliers improves the accuracy of subspace clustering. …”
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New Robust Part-Based Model with Affine Transformations for Facial Landmark Localization and Detection in Big Data by Chentao Zhang, Habte Tadesse Likassa, Peidong Liang, Jielong Guo

“…In contrast to the existing works, the new algorithm incorporates affine transformations with the robust regression to tackle the potential effects of outliers and heavy sparse noises, occlusions and illuminations. …”
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Quality Assessment of Soaps Produced from Palm Bunch Ash-Derived Alkali and Coconut Oil by HO Ogunsuyi, CA Akinnawo

“…The following parameters were determined: free alkali content, total fatty matter, moisture content, lathering ability, cleansing power, matter insoluble in water, matter insoluble in ethanol. …”
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