Variation of Ozone in the Pantanal Environment Based on Probability Distributions

Souza, Amaury de; Júnior, José Francisco de Oliveira; Abreu, Marcel Carvalho; Aristone, Flávio; Oliveira, Ana Paula Garcia; Nunes, Raquel Soares Casaes; Cavazzana, Guilherme Henrique; Santos, Cícero Manoel dos; Reis, Carlos José dos; Dumka, Umesh

doi:10.1080/01919512.2022.2041392

Cited by 2 publications

(1 citation statement)

References 55 publications

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“…To measure the goodness of fit of the model (goodness-of-fit test), it is preferable to use the distance between the empirical cumulative distribution function (eCDF) [18], [40]- [42] and the cumulative distribution function of the selected distribution. such as the Kolmogorov-Smirnov test, Anderson-Darling test, root mean square error (RMSE), coefficient of determination (R²) [43], [44], and eCDF derived from the estimation. The goodnessof-fit test is useful for comparing performance between different models and is used to analyze data with a single model type.…”

Section: Introductionmentioning

confidence: 99%

Predictive Reliability Analysis of Power Distribution Systems Considering the Effects of Seasonal Factors on Outage Data Using Weibull Analysis Combined With Polynomial Regression

Dechgummarn,

Fuangfoo,

Kampeerawat

2023

IEEE Access

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In this study, the reliability of power distribution systems is analyzed using a novel strategy of predictive reliability analysis based on the lifetime failure rate cycle in a bathtub curve shape and considering the standard Weibull distribution to determine the trend of the failure rate in each period using median rank regression for parameter estimation. The proposed strategy consists of three processes. The first process involves separating the external and internal factors that influence power outages in the power distribution system from the seasonal multimodal shape in the empirical distribution of the dataset using a bisection algorithm of residuals of polynomial regression. Second, clustering and characterization of each component in the power distribution system according to the condition of the total factor bathtub curve leads to the introduction of the use of shape parameters as the total factor deterioration index (TFDI) with linear regression trends of log scale shape parameters of the useful period. A simple approximation of the system's overall total factor bathtub curve using a sixty-year forecast is the final process presented that can be used in reliability planning to address lifecycle risks. The actual time-to-outage dataset between 2015 and 2020 of the Provincial Electricity Authority, Region 1, Northeastern Thailand, which covers the area of distribution line life in the three periods of the bathtub curve, was used as the test data. The numerical results obtained from the proposed process provide a comprehensive prediction of the reliability of the electrical distribution system for risk response planning. The results show the proportion and amount of internal deterioration versus external disturbances, helps to group components according to health and usability and prioritizes them according to risk. Furthermore, it clarifies the important moments of status transition. All of these factors make it possible to improve reliability in the right place at the right time. Every method that we have chosen to improve for use in analysis is simple, provides a clear visualization of every step, and can be used in practice.

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Section: Introductionmentioning

confidence: 99%

Predictive Reliability Analysis of Power Distribution Systems Considering the Effects of Seasonal Factors on Outage Data Using Weibull Analysis Combined With Polynomial Regression

Dechgummarn,

Fuangfoo,

Kampeerawat

2023

IEEE Access

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Satellite measurement data-based assessment of spatiotemporal characteristics of ultraviolet index (UVI) over the state of Johor, Malaysia

Valappil,

Ahmad,

Hamza

2024

Asian J. Atmos. Environ

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The study examines the spatiotemporal and statistical characteristics of the daily ultraviolet index (UVI) over the Johor state of Malaysia. The datasets utilized in this study are the Ozone Monitoring Instrument (OMI)/Aura satellite’s daily UVI observations between October 2004 and March 2023. The innovative trend analysis (ITA) method is employed to identify the statistical trend of daily UVI. Basic statistics of daily, monthly, and seasonal UVI are also carried out to better characterize UVI in the study area. The daily UVI data collected for the analysis exhibit wide variability, with more than 80% of the daily UVI data falling above UVI 8, indicating the severity of UV radiation (UVR) reaching the study area. The monthly and seasonal UVI also display highly varying characteristics, as observed in the daily data. The pixel-based analysis of ITA results indicates a significant increasing and decreasing trend of daily UVI in the region, with values varying between − 9.42 × 10−6 and 3.79 × 10−5. However, for the study area as a whole, UVI shows a significant increasing trend of 4.50 × 10−5. The influence of parameters such as cloud optical thickness (COT), solar zenith angle (SZA), and O3 column on the strength of UVR reaching the study area is also investigated. Based on the results, the study area is characterized by low thickness, broken clouds, and sometimes cloudless conditions. Overall, the results show that UVI in the study area is increasing, and therefore, proper health guidelines and direct UVR exposure regulations need to be implemented to reduce serious health risks associated with UVR exposure. Graphical Abstract

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Variation of Ozone in the Pantanal Environment Based on Probability Distributions

Cited by 2 publications

References 55 publications

Predictive Reliability Analysis of Power Distribution Systems Considering the Effects of Seasonal Factors on Outage Data Using Weibull Analysis Combined With Polynomial Regression

Predictive Reliability Analysis of Power Distribution Systems Considering the Effects of Seasonal Factors on Outage Data Using Weibull Analysis Combined With Polynomial Regression

Satellite measurement data-based assessment of spatiotemporal characteristics of ultraviolet index (UVI) over the state of Johor, Malaysia

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