Lean Data Science Research Life Cycle: A Concept for Data Analysis Software Development

Shcherbakov, Maxim; Shcherbakova, Nataliya; Brebels, Adriaan; Janovsky, Timur; Камаев, В. А.

doi:10.1007/978-3-319-11854-3_61

Cited by 27 publications

(31 citation statements)

References 8 publications

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“…The main drawbacks of the use of RMSE solely in calculating model performance are the scale dependency (if the model includes variables with different scales or magnitudes, then absolute error measures could not be applied), the high influence of outliers in data on the model performance evaluation, and the low reliability (the results could be different depending on the different fraction of data) [53]. For these reasons, Table 5 shows not only absolute model error statistical indicators, such as BIAS and RMSE, but also indicators based on percentage errors, such as NBIAS and NRMSE.…”

Section: Resultsmentioning

confidence: 99%

Wave Climate at Shallow Waters along the Abu Dhabi Coast

Hamza

Lusito

Ligorio

et al. 2018

Water

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High-resolution, reliable global atmospheric and oceanic numerical models can represent a key factor in designing a coastal intervention. At the present, two main centers have the capabilities to produce them: the National Oceanic and Atmospheric Administration (NOAA) in the U.S.A. and the European Centre for Medium-Range Weather Forecasts (ECMWF). The NOAA and ECMWF wave models are developed, in particular, for different water regions: deep, intermediate, and shallow water regions using different types of spatial and temporal grids. Recently, in the Arabian Gulf (also named Persian Gulf), the Abu Dhabi Municipality (ADM) installed an ADCP (Acoustic Doppler Current Profiler) to observe the atmospheric and oceanographic conditions (water level, significant wave height, peak wave period, water temperature, and wind speed and direction) at 6 m water depth, in the vicinity of the shoreline of the Saadiyat beach. Courtesy of Abu Dhabi Municipality, this observations dataset is available; the recorded data span the period from June 2015 to January 2018 (included), with a time resolution of 10 min and 30 min for the atmospheric and oceanographic variables, respectively. At the ADCP deployment location (ADMins), the wave climate has been determined using wave propagation of the NOAA offshore wave dataset by means of the Simulating WAves Nearshore (SWAN) numerical model, the NOAA and ECMWF wave datasets at the closest grid point in shallow water conditions, and the SPM ’84 hindcasting method with the NOAA wind dataset used as input. It is shown that the best agreement with the observed wave climate is obtained using the SPM ’84 hindcasting method for the shallow water conditions.

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Section: Resultsmentioning

confidence: 99%

Wave Climate at Shallow Waters along the Abu Dhabi Coast

Hamza

Lusito

Ligorio

et al. 2018

Water

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“…Según Chai y Draxler (2014), el RMSE es la medida más popular del error, también conocida como «función de pérdida cuadrática». Sobre la misma medida de error Lakshmivarahan et al (2017) y Shcherbakov et al (2013) definen al RMSE como el promedio entre los valores absolutos de los errores del pronóstico, y se utiliza como un criterio de selección para el mejor ajuste de modelos de series de tiempo. Su forma de cálculo se lo hace a partir de la ecuación 4.…”

Section: Materials Y Métodosunclassified

Uso de las TIC y relación con los Objetivos de Desarrollo Sostenible en Ecuador

Ibujés-Villacís

Crespo

2019

ret

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En 2015, en el foro de la Organización de las Naciones Unidas (ONU) se aprobaron los 17 Objetivos de Desarrollo Sostenible (ODS) para cumplirse hasta el año 2030. Conviene preguntarse si Ecuador está encauzado a lograr esos objetivos, apoyándose en el uso de las tecnologías de la información y la comunicación (TIC). En tal virtud, el objetivo de esta investigación es conocer el estado actual y perspectivas de la Sociedad de la Información (SI) en relación con el logro de las metas de los ODS, mediante el análisis de la información histórica y pronósticos de los indicadores SI, y actuaciones de investigación, desarrollo e innovación (I+D+i) en Ecuador. La metodología de investigación tiene un enfoque cuantitativo, no experimental y longitudinal. Se utilizaron fuentes de información secundarias como reportes nacionales y extranjeros que contienen índices estadísticos anuales, que convertidos en series de tiempo permitieron analizar pronósticos y determinar la tendencia futura de esos indicadores. Como resultados se encontró que el comportamiento de indicadores de uso de las TIC e indicadores de I+D+i están relacionados en forma directa o indirecta con el cumplimiento de las metas de los ODS cuarto, quinto, octavo y noveno. Se obtuvo como conclusión que, por un lado, la tendencia de cinco indicadores de la SI sintonizan con el logro de las metas de los ODS, mientras que otros tres indicadores requieren un fuerte impulso para cambiar la tendencia y lograr su meta asociada; y, por otro lado, la necesidad de que los diferentes actores de la sociedad ecuatoriana se comprometan a trabajar a partir de las potencialidades del uso de las TIC y actuaciones en I+D+i con el fin de lograr los ODS.

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“…As stated by Shcherbakov, et al [18], forecast error measurement can be used to estimate the quality of forecasting methods and to choose the best forecasting mechanism. There are many forecast error measurements, but we will use only two widely known scale-independent error measurements, i.e.…”

Section: Forecast Error Measurementmentioning

confidence: 99%

New Estimation Rules for Unknown Parameters on Holt-Winters Multiplicative Method

Hansun

2017

J. Math. Fund. Sci.

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Abstract. The Holt-Winters method is a well-known forecasting method used in time-series analysis to forecast future data when a trend and seasonal pattern is detected. There are two variations, i.e. the additive and the multiplicative method. Prior study by Vercher, et al. in [1] has shown that choosing the initial conditions is very important in exponential smoothing models, including the Holt-Winters method. Accurate estimates of initial conditions can result in better forecasting results. In this research, we propose new estimation rules for initial conditions for the Holt-Winters multiplicative method. The estimation rules were derived from the original initial conditions combined with the weighted moving average method. From the experimental results it was found that the new approach of the Holt-Winters multiplicative method can outperform the original Holt-Winters multiplicative method.

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Lean Data Science Research Life Cycle: A Concept for Data Analysis Software Development

Cited by 27 publications

References 8 publications

Wave Climate at Shallow Waters along the Abu Dhabi Coast

Wave Climate at Shallow Waters along the Abu Dhabi Coast

Uso de las TIC y relación con los Objetivos de Desarrollo Sostenible en Ecuador

New Estimation Rules for Unknown Parameters on Holt-Winters Multiplicative Method

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