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Sökning: WFRF:(Bagheri Y)

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1.
  • Burstein, Roy, et al. (författare)
  • Mapping 123 million neonatal, infant and child deaths between 2000 and 2017
  • 2019
  • Ingår i: Nature. - : Nature Publishing Group. - 0028-0836 .- 1476-4687. ; 574:7778, s. 353-358
  • Tidskriftsartikel (refereegranskat)abstract
    • Since 2000, many countries have achieved considerable success in improving child survival, but localized progress remains unclear. To inform efforts towards United Nations Sustainable Development Goal 3.2—to end preventable child deaths by 2030—we need consistently estimated data at the subnational level regarding child mortality rates and trends. Here we quantified, for the period 2000–2017, the subnational variation in mortality rates and number of deaths of neonates, infants and children under 5 years of age within 99 low- and middle-income countries using a geostatistical survival model. We estimated that 32% of children under 5 in these countries lived in districts that had attained rates of 25 or fewer child deaths per 1,000 live births by 2017, and that 58% of child deaths between 2000 and 2017 in these countries could have been averted in the absence of geographical inequality. This study enables the identification of high-mortality clusters, patterns of progress and geographical inequalities to inform appropriate investments and implementations that will help to improve the health of all populations.
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  • Bagheri, Azam, et al. (författare)
  • A Robust Transform-Domain Deep Convolutional Network for Voltage Dip Classification
  • 2018
  • Ingår i: IEEE Transactions on Power Delivery. - : Institute of Electrical and Electronics Engineers (IEEE). - 0885-8977 .- 1937-4208. ; 33:6, s. 2794-2802
  • Tidskriftsartikel (refereegranskat)abstract
    • This paper proposes a novel method for voltage dip classification using deep convolutional neural networks. The main contributions of this paper include: (a) to propose a new effective deep convolutional neural network architecture for automatically learning voltage dip features, rather than extracting hand-crafted features; (b) to employ the deep learning in an effective two-dimensional transform domain, under space-phasor model (SPM), for efficient learning of dip features; (c) to characterize voltage dips by two-dimensional SPM-based deep learning, which leads to voltage dip features independent of the duration and sampling frequency of dip recordings; (d) to develop robust automatically-extracted features that are insensitive to training and test datasets measured from different countries/regions.Experiments were conducted on datasets containing about 6000 measured voltage dips spread over seven classes measured from several different countries. Results have shown good performance of the proposed method: average classification rate is about 97% and false alarm rate is about 0.50%. The test results from the proposed method are compared with the results from two existing dip classification methods. The proposed method is shown to out-perform these existing methods.
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  • Bagheri, Azam, et al. (författare)
  • Big data from smart grids
  • 2018
  • Ingår i: 2017 IEEE PES Innovative Smart Grid Technologies Conference Europe, ISGT-Europe 2017. - New York : Institute of Electrical and Electronics Engineers (IEEE). - 9781538619537
  • Konferensbidrag (refereegranskat)abstract
    • This paper gives a general introduction to “Big Data” in general and to Big Data in smart grids in particular. Large amounts of data (Big Data) contains a lots of information, however developing the analytics to extract such information is a big challenge due to some of the particular characteristics of Big Data. This paper investigates some existing analytic algorithms, especially deep learning algorithms, as tools for handling Big Data. The paper also explains the potential for deep learning application in smart grids.
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  • Bagheri, Azam, et al. (författare)
  • Generative Adversarial Model-Guided Deep Active Learning for Voltage Dip Labelling
  • 2019
  • Ingår i: 2019 IEEE Milan PowerTech. - : IEEE. - 9781538647226
  • Konferensbidrag (refereegranskat)abstract
    • In many real applications, the ground truths of class labels from voltage dip sequences used for training a voltage dip classification system are unknown, and require manual labelling by human experts. This paper proposes a novel deep active learning method for automatic labelling of voltage dip sequences used for the training process. We propose a novel deep active learning method, guided by a generative adversarial network (GAN), where the generator is formed by modelling data with a Gaussian mixture model and provides the estimated probability distribution function (pdf) where the query criterion of the deep active learning method is built upon. Furthermore, the discriminator is formed by a support vector machine (SVM). The proposed method has been tested on a voltage dip dataset (containing 916 dips) measured in a European country. The experiments have resulted in good performance (classification rate 83% and false alarm 3.2%), which have demonstrated the effectiveness of the proposed method.
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  • Bagheri, Azam, et al. (författare)
  • Improved characterization of multi-stage voltage dips based on the space phasor model
  • 2018
  • Ingår i: Electric power systems research. - : Elsevier. - 0378-7796 .- 1873-2046. ; 154, s. 319-328
  • Tidskriftsartikel (refereegranskat)abstract
    • This paper proposes a method for characterizing voltage dips based on the space phasor model of the three phase-to-neutral voltages, instead of the individual voltages. This has several advantages. Using a K-means clustering algorithm, a multi-stage dip is separated into its individual event segments directly instead of first detecting the transition segments. The logistic regression algorithm fits the best single-segment characteristics to every individual segment, instead of extreme values being used for this, as in earlier methods. The method is validated by applying it to synthetic and measured dips. It can be generalized for application to both single- and multi-stage dips.
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  • Resultat 1-10 av 20
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