Diagnosis and clustering of power transformer winding fault types by cross‐correlation and clustering analysis of FRA results

Abbasi, Ali Reza; Mahmoudi, Mohammad Reza; Avazzadeh, Z.

doi:10.1049/iet-gtd.2018.5812

Cited by 70 publications

(28 citation statements)

References 31 publications

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“…The clustering results indicated that the distribution of spreading in Spain and Italy was approximately similar and differed from other countries. For future works, the authors suggest the researchers categorize the statistical models including regression and time series models and artificial intelligence models that can be fitted on Covid-19 datasets [31] , [32] , [33] , [34] , [35] , [36] , [37] , [38] , [39] , [40] , [41] , [42] , [43] , [44] , [45] , [46] , [47] , [48] , [49] , [50] , [51] , [52] , [53] , [54] , [55] , [56] , [57] , [58] , [59] , [60] , [61] .…”

Section: Discussionmentioning

confidence: 99%

Fuzzy clustering method to compare the spread rate of Covid-19 in the high risks countries

Mahmoudi

Băleanu

Mansor

et al. 2020

Chaos, Solitons & Fractals

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The numbers of confirmed cases of new coronavirus (Covid-19) are increased daily in different countries. To determine the policies and plans, the study of the relations between the distributions of the spread of this virus in other countries is critical. In this work, the distributions of the spread of Covid-19 in Unites States America, Spain, Italy, Germany, United Kingdom, France, and Iran were compared and clustered using fuzzy clustering technique. At first, the time series of Covid-19 datasets in selected countries were considered. Then, the relation between spread of Covid-19 and population's size was studied using Pearson correlation. The effect of the population's size was eliminated by rescaling the Covid-19 datasets based on the population's size of USA. Finally, the rescaled Covid-19 datasets of the countries were clustered using fuzzy clustering. The results of Pearson correlation indicated that there were positive and significant between total confirmed cases, total dead cases and population's size of the countries. The clustering results indicated that the distribution of spreading in Spain and Italy was approximately similar and differed from other countries.

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Section: Discussionmentioning

confidence: 99%

Fuzzy clustering method to compare the spread rate of Covid-19 in the high risks countries

Mahmoudi

Băleanu

Mansor

et al. 2020

Chaos, Solitons & Fractals

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“…Since January until now (18 April 2020), this epidemic changed to pandemic in the whole of the world and the number of patients with this disease and the number of deaths due to this disease is increasing day by day in most of countries, particularly in France [2] , [3] , [4] , [5] , Germany [6] , Iran [7] , Italy [8] , [9] , [10] , Spain [11] , United Kingdom [12] , [13] , [14] , and Unites States America [15] . The modeling of the different natural phenomena were studied using different data analysis techniques, such as statistical and mathematical modeling containing time series analysis, regression modeling, optimization and numerical analysis [16] , [17] , [18] , [19] , [20] , [21] , [22] , [23] , [24] , [25] , [26] , [27] , [28] , [29] , [30] , [31] , [32] , [33] , [34] , [35] , [36] , [37] , [38] , [39] , [40] , and artificial intelligence modeling containing deep learning, machine learning and clustering [41] , [42] , [43] , [44] , [45] , [46] . Because of different social, economic and environmental effects of Covid-19, it is critical to study and compare the spread rate of this disease in different countries.…”

Section: Introductionmentioning

confidence: 99%

Principal component analysis to study the relations between the spread rates of COVID-19 in high risks countries

Mahmoudi

Heydari

Qasem

et al. 2021

Alexandria Engineering Journal

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124

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In this research, the number of patients with Covid-19 and the number of deaths due to this disease in France, Germany, Iran, Italy, Spain, United Kingdom, and Unites States America are considered. First, the relations between the considered countries are studied using Pearson’s correlation. Then, based on the spread rate of Covid-19, these countries are categorized using principal component analysis.

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“…Since each cluster consists of some points, numerous amalgamation techniques like Ward's technique, average linkage, complete linkage, and simple linkage can be applied to compute the distance and similarity between different points [32][33][34]. In real-world applications, squared Euclidean distances and Ward's method are usually selected.…”

Section: Clustering Methodologymentioning

confidence: 99%

Clustering the Adsorbents of Horizontal Series Filtration in Greywater Treatment

2020

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One of the important alternative water resources for non-potable purposes is greywater (GW), which must be cleaned of contaminants. In this regard, the clustering analysis of materials consisting of sand (S), zeolite (Z), peat (P) and granular activated carbon (GAC) within a horizontal series filter (HSF) was used for removal of chemical oxygen demand (COD), biochemical oxygen demand (BOD), total dissolved solids (TDS), and turbidity in GW taken from the Fasa University Student Hostel, Iran. The hierarchical clustering technique was applied to classify the adsorbents. The findings indicated that there were significant differences (more than 95%) between these materials. According to the similarity of level 95%, for COD, BOD, TDS, and turbidity removal, these adsorbents could be separately clustered in three, three, two, and three clusters, respectively. In addition, by considering the simultaneous changes of COD, BOD, TDS, and turbidity together, these adsorbents could be clustered in three different clusters. This paper proposed an efficient method to select the best combination of adsorbents for eliminating of COD, BOD, TDS, and turbidity from GW. Generally, based on the quality of treated greywater and literature, reusing greywater can be implemented for agriculture, artificial recharge of aquifers, desertification, and preventing the dust creation in arid areas such as southern Iran.

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Diagnosis and clustering of power transformer winding fault types by cross‐correlation and clustering analysis of FRA results

Cited by 70 publications

References 31 publications

Fuzzy clustering method to compare the spread rate of Covid-19 in the high risks countries

Fuzzy clustering method to compare the spread rate of Covid-19 in the high risks countries

Principal component analysis to study the relations between the spread rates of COVID-19 in high risks countries

Clustering the Adsorbents of Horizontal Series Filtration in Greywater Treatment

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