Evaluation of weibull parameter estimators for wind speed of Jumla, Nepal

Weibull Probability Distribution Function (PDF) is widely used across world for estimation of wind power. Weibull function is a two parameter probability distribution function. The methods employed for the evaluation of these two parameters are critical for the efficient use of Weibull PDF. In the present study, three different Weibull PDF parameter estimators have been evaluated. For this purpose, the daily averaged wind speed data of Jumla Station, Nepal for period of 10 year (2004 – 2014: 2012 excluded) is studied. The parameter estimator evaluated in this study are Method of Moments (MoM), Least Square Error Method (LSEM) and Power Density Method (PDM). It has been found that Method of Moments (MoM) is the best estimator for evaluating Weibull Parameters.

Development and Evaluation of a Fluctuating Plume Model for Odor Impact Assessment

For environmental odor nuisance, it is extremely important to identify the instantaneous concentration statistics. In this work, a Fluctuating Plume Model for different statistical moments is proposed. It provides data in terms of mean concentrations, variance, and intensity of concentration. The 90th percentile peak-to-mean factor, R90, was tested here by comparing it with the experimental results (Uttenweiler field experiment), considering different Probability Distribution Functions (PDFs): Gamma and the Modified Weibull. Seventy-two percent of the simulated mean concentration values fell within a factor 2 compared to the experimental ones: the model was judged acceptable. Both the modelled results for standard deviation, σC, and concentration intensity, Ic, overestimate the experimental data. This evidence can be due to the non-ideality of the measurement system. The propagation of those errors to the estimation of R90 is complex, but the ranges covered are quite repeatable: the obtained values are 1–3 for the Gamma, 1.5–4 for Modified Weibull PDF, and experimental ones from 1.4 to 3.6.

ADJUSTMENT OF PROBABILITY FUNCTIONS TO WATER EXCESS AND DEFICIT IN SOYBEANS CULTIVATED IN LOWLAND SOILS

ADJUSTMENT OF PROBABILITY FUNCTIONS TO WATER EXCESS AND DEFICIT IN SOYBEANS CULTIVATED IN LOWLAND SOILS MATEUS POSSEBON BORTOLUZZI¹; ARNO BERNARDO HELDWEIN²; ROBERTO TRENTIN³; ASTOR HENRIQUE NIED²; JOCÉLIA ROSA DA SILVA4 E LEIDIANA DA ROCHA4 1 Faculdade de Agronomia e Medicina Veterinária, Universidade de Passo Fundo, BR 285, São José, 99052-900, Passo Fundo, RS, Brasil. [email protected] 2 Departamento de Fitotecnia, Universidade Federal de Santa Maria, Avenida Roraima, n° 1000, Camobi, 97010-900, Santa Maria, RS, Brasil. [email protected]; [email protected] 3Departmento de Fitotecnia, UFPel, Campus Universitário, s/n, 96010-610, Capão do Leão, RS, Brasil. [email protected] 4 Programa de Pós-graduação em Agronomia, Universidade Federal de Santa Maria, Avenida Roraima, n° 1000, Camobi, 97010-900, Santa Maria, RS, Brasil. [email protected]; [email protected] 1 ABSTRACT The objective of this study was to verify the fit of exponential, gamma, lognormal, normal and weibull probability density functions (pdf) to water deficit and excess accumulated data during soybean subperiods and development cycle. Historical series of meteorological data obtained from Pelotas and Santa Maria meteorological stations (RS) were utilized. The soybean development simulation was performed for cultivars from the relative maturity group (RMG) between 5.9-6.8, 6.9-7.3 and 7.4-8.0 on eleven sowing dates from September 21 to December 31. Daily sequential water balance was calculated with water excess (days) and water deficit (mm) data to adjust each pdf to the observed data. The better adjustment frequency for water excess data in the soybean cycle was obtained with normal pdf in Santa Maria and weibull and gamma in Pelotas. Regardless of the location, the lognormal pdf presented the best fit for the water deficit data in the soybean cycle. In both locations, normal and weibull pdf demonstrated the best performance for water excess in the subperiods gamma, lognormal and exponential pdf for the water deficit. Keywords: Glycine max, risk analysis, sowing date, historical series. BORTOLUZZI, M. P.; HELDWEIN, A. B.; TRENTIN, R.; NIED, A. H.; DA SILVA, J. R.; DA ROCHA, L. AJUSTE DE FUNÇÕES DE PROBABILIDADE AO EXCESSO E DÉFICIT HÍDRICO NA SOJA EM TERRAS BAIXAS 2 RESUMO O objetivo deste trabalho foi verificar o ajuste das funções densidade de probabilidade (fdp) exponencial, gama, lognormal, normal e weibull aos dados de déficit e excesso hídrico, acumulados durante subperíodos e ciclo de desenvolvimento da soja. Foram utilizadas séries históricas de dados meteorológicos obtidos das estações meteorológicas de Pelotas e de Santa Maria, RS. Foi simulado o desenvolvimento da soja, para cultivares de grupo de maturidade relativa (GMR) entre 5.9–6.8, 6.9–7.3 e 7.4–8.0 em onze datas de semeadura compreendidas entre 21 de setembro e 31 de dezembro. Calculou-se o balanço hídrico sequencial diário, sendo obtidos os dados de excesso hídrico (dias) e déficit hídrico (mm) para ajustar cada fdp aos dados observados. A maior frequência de ajuste para os dados de excesso hídrico no ciclo da soja foi obtida para a fdp normal em Santa Maria e fdp weibull e gama para Pelotas. A fdp lognormal foi a que melhor se ajustou aos dados de déficit hídrico no ciclo da soja, independentemente do local. Em ambos os locais, a fdp normal e a weibull apresentaram o melhor desempenho para o excesso hídrico nos subperíodos e as fdps gama, lognormal e exponencial para o déficit hídrico. Palavras-chave: Glycine max, análise de risco, data de semeadura, séries históricas.

Comparing Johnson’s SB and Weibull Functions to Model the Diameter Distribution of Forest Plantations through ALS Data

The analysis of the diameter distribution is important for forest management since the knowledge of tree density and growing stock by diameter classes is essential to define management plans and to support operational decisions. The modeling of diameter distributions from airborne laser scanning (ALS) data has been performed through the two-parameter Weibull probability density function (PDF), but the more flexible PDF Johnson’s SB has never been tested for this purpose until now. This study evaluated the performance of the Johnson’s SB to predict the diameter distributions based on ALS data from two of the most common forest plantations in the northwest of the Iberian Peninsula (Eucalyptus globulus Labill. and Pinus radiata D. Don). The Weibull PDF was taken as a benchmark for the diameter distributions prediction and both PDFs were fitted with ALS data. The results show that the SB presented a comparable performance to the Weibull for both forest types. The SB presented a slightly better performance for the E. globulus, while the Weibull PDF had a small advantage when applied to the P. radiata data. The Johnson’s SB PDF is more flexible but also more sensitive to possible errors arising from the higher number of stand variables needed for the estimation of the PDF parameters.

Determination of Yearly Wind Energy Potential and Extraction of Wind Energy Using Wind Turbine for Coastal Cities of Baluchistan, Pakistan

04 March, 2019 Accepted: 24 April, 2019Abstract: Wind energy assessment of Ormara, Gwadar and Lasbela wind sites which are located in provinceBaluchistan is presented. The daily averaged wind speed data for the three sites is recorded for a period of four yearsfrom 2010-2013 at mast heights 7 m, 9.6 m and 23 m. Measured wind data are extrapolated to heights 60 m (Ormara),80 m (Gwadar) and 60 m (Lasbela). Yearly averaged wind speeds are modeled using a two parameters Weibullfunction whose shape (k) and scale (c) parameters are computed using seven well known numerical iterative methods.Reliability of the fitting process is assessed by employing three goodness-of-fit test statistics, namely, RMSE, R2 and χ2tests. Tests indicate that MLE, MLM and EPFM outperformed other Weibull parameter estimation methods for a betterfit behavior. Yearly Weibull pdf and cdf are obtained and Weibull wind characteristics are determined. Wind turbinesEcotecnia 60/1.67 MW and Nordex S77 1500 kW are used to extract wind energy on yearly basis. Estimated yearlyWeibull power densities are in the range 623.00 - 700.13 W/m2, 276.04 – 307.55 W/m2 and 66.85 – 75.93 W/m2 forOrmara, Gwadar and Lasbela respectively. Extracted wind energy values for Ormara and Gwadar using wind turbinesare reported as ca. 8623 kWh and ca. 4622 kWh, respectively.

Determination of Yearly Wind Energy Potential and Extraction of Wind Energy Using Wind Turbine for Coastal Cities of Baluchistan, Pakistan

04 March, 2019 Accepted: 24 April, 2019Abstract: Wind energy assessment of Ormara, Gwadar and Lasbela wind sites which are located in provinceBaluchistan is presented. The daily averaged wind speed data for the three sites is recorded for a period of four yearsfrom 2010-2013 at mast heights 7 m, 9.6 m and 23 m. Measured wind data are extrapolated to heights 60 m (Ormara),80 m (Gwadar) and 60 m (Lasbela). Yearly averaged wind speeds are modeled using a two parameters Weibullfunction whose shape (k) and scale (c) parameters are computed using seven well known numerical iterative methods.Reliability of the fitting process is assessed by employing three goodness-of-fit test statistics, namely, RMSE, R2 and χ2tests. Tests indicate that MLE, MLM and EPFM outperformed other Weibull parameter estimation methods for a betterfit behavior. Yearly Weibull pdf and cdf are obtained and Weibull wind characteristics are determined. Wind turbinesEcotecnia 60/1.67 MW and Nordex S77 1500 kW are used to extract wind energy on yearly basis. Estimated yearlyWeibull power densities are in the range 623.00 - 700.13 W/m2, 276.04 – 307.55 W/m2 and 66.85 – 75.93 W/m2 forOrmara, Gwadar and Lasbela respectively. Extracted wind energy values for Ormara and Gwadar using wind turbinesare reported as ca. 8623 kWh and ca. 4622 kWh, respectively.

Basic Equations and Computing Procedures for Frailty Modeling of Carcinogenesis: Application to Pancreatic Cancer Data

Modeling of cancer hazards at age t deals with a dichotomous population, a small part of which (the fraction at risk) will get cancer, while the other part will not. Therefore, we conditioned the hazard function, h( t), the probability density function (pdf), f( t), and the survival function, S( t), on frailty α in individuals. Assuming α has the Bernoulli distribution, we obtained equations relating the unconditional (population level) hazard function, hU( t), cumulative hazard function, HU( t), and overall cumulative hazard, H0, with the h( t), f( t), and S( t) for individuals from the fraction at risk. Computing procedures for estimating h( t), f( t), and S( t) were developed and used to ft the pancreatic cancer data collected by SEER9 registries from 1975 through 2004 with the Weibull pdf suggested by the Armitage-Doll model. The parameters of the obtained excellent fit suggest that age of pancreatic cancer presentation has a time shift about 17 years and five mutations are needed for pancreatic cells to become malignant.