Zobrazeno 1 - 10
of 45
pro vyhledávání: '"WILFREDO ALFONSO-MORALES"'
Publikováno v:
Journal of Industrial Engineering and Management, Vol 16, Iss 2, Pp 363-381 (2023)
Purpose: This work aims to evaluate demand forecasting models to determine if using exogenous factors and machine learning techniques helps improve performance compared to univariate statistical models, allowing manufacturing companies to manage dema
Externí odkaz:
https://doaj.org/article/83ae1ca5e0ed4e16b05d7a27956e07d3
Publikováno v:
Energies, Vol 16, Iss 23, p 7878 (2023)
Electricity is crucial for daily life due to the number of activities that depend on it. To forecast future electric load, which changes over time and depends on various factors, grid operators (GOs) must create forecasting models for various time ho
Externí odkaz:
https://doaj.org/article/f2464a0b186248a798ff505e8bd103cd
Autor:
Camilo Ocampo-Marulanda, Cristhian Fernández-Álvarez, Wilmar L. Cerón, Teresita Canchala, Yesid Carvajal-Escobar, Wilfredo Alfonso-Morales
Publikováno v:
Ain Shams Engineering Journal, Vol 13, Iss 5, Pp 101739- (2022)
Long and temporal time-consistency rainfall time series are essential for studying climate; nevertheless, raingauge stations are unevenly distributed across southwestern Colombia. This research paper assesses the consistency of the satellite rainfall
Externí odkaz:
https://doaj.org/article/e427fdd018d0413faa447d819dcbab1a
Autor:
TERESITA CANCHALA, CAMILO OCAMPO-MARULANDA, WILFREDO ALFONSO-MORALES, YESID CARVAJAL-ESCOBAR, WILMAR L. CERÓN, EDUARDO CAICEDO-BRAVO
Publikováno v:
Anais da Academia Brasileira de Ciências, Vol 94, Iss 4 (2022)
Abstract The knowledge of rainfall regimes is a relevant requirement for many activities such as water resources planning, risk management, agriculture activities management, and other hydrologic applications. The present study has consisted of valid
Externí odkaz:
https://doaj.org/article/ffe259c8509c4df69934b0e7c2de84a0
Publikováno v:
AIMS Energy, Vol 8, Iss 4, Pp 627-651 (2020)
Planning and operation of Smart energetic have become more complex to analyse due to structural changes in the energy sector. The inclusion of distributed generation sources, generation with renewable sources, storage systems, and the dislocation of
Externí odkaz:
https://doaj.org/article/5212f852078946d78aa09eae1b8f7db6
Autor:
Camilo Ocampo-Marulanda, Wilmar L. Cerón, Alvaro Avila-Diaz, Teresita Canchala, Wilfredo Alfonso-Morales, Mary T. Kayano, Roger R. Torres
Publikováno v:
Data in Brief, Vol 39, Iss , Pp 107592- (2021)
Changes observed in the current climate and projected for the future significantly concern researchers, decision-makers, and the general public. Climate indices of extreme rainfall events are a trend assessment tool to detect climate variability and
Externí odkaz:
https://doaj.org/article/263d51955934447ab2ba4693e8008b64
Publikováno v:
Sensors, Vol 21, Iss 16, p 5308 (2021)
This paper presents the implementation of nonlinear canonical correlation analysis (NLCCA) approach to detect steady-state visual evoked potentials (SSVEP) quickly. The need for the fast recognition of proper stimulus to help end an SSVEP task in a B
Externí odkaz:
https://doaj.org/article/6efb43ac3a66486b97f1e4b75c383596
Publikováno v:
Sensors, Vol 21, Iss 16, p 5650 (2021)
The Advanced Metering Infrastructure (AMI) data represent a source of information in real time not only about electricity consumption but also as an indicator of other social, demographic, and economic dynamics within a city. This paper presents a Da
Externí odkaz:
https://doaj.org/article/8ce6f00d2110450abe8fac1219b457ba
Autor:
Teresita Canchala-Nastar, Yesid Carvajal-Escobar, Wilfredo Alfonso-Morales, Wilmar Loaiza Cerón, Eduardo Caicedo
Publikováno v:
Data in Brief, Vol 26, Iss , Pp - (2019)
The success of many projects linked to the management and planning of water resources depends mainly on the quality of the climatic and hydrological data that is provided. Nevertheless, the missing data are frequently found in hydroclimatic variables
Externí odkaz:
https://doaj.org/article/d4737e5debfc47129b4c0e7246257709
Autor:
Teresita Canchala, Wilfredo Alfonso-Morales, Yesid Carvajal-Escobar, Wilmar L. Cerón, Eduardo Caicedo-Bravo
Publikováno v:
Water, Vol 12, Iss 9, p 2628 (2020)
Improving the accuracy of rainfall forecasting is relevant for adequate water resources planning and management. This research project evaluated the performance of the combination of three Artificial Neural Networks (ANN) approaches in the forecastin
Externí odkaz:
https://doaj.org/article/1fdde5b12f7c4ba38df79defe3879251