Zobrazeno 1 - 10
of 14
pro vyhledávání: '"Efrain Noa-Yarasca"'
Publikováno v:
Machine Learning and Knowledge Extraction, Vol 6, Iss 3, Pp 1633-1652 (2024)
Accurate aboveground vegetation biomass forecasting is essential for livestock management, climate impact assessments, and ecosystem health. While artificial intelligence (AI) techniques have advanced time series forecasting, a research gap in predic
Externí odkaz:
https://doaj.org/article/046d849d9b054cbabd46b7db918085c2
Publikováno v:
Agronomy, Vol 14, Iss 2, p 349 (2024)
Timely forecasting of aboveground vegetation biomass is crucial for effective management and ensuring food security. However, research on predicting aboveground biomass remains scarce. Artificial intelligence (AI) methods could bridge this research g
Externí odkaz:
https://doaj.org/article/8b4361213b3e4ca7af2132e85e70f721
Autor:
Efrain Noa Yarasca, khoi Nguyen
Publikováno v:
Pesquimat, Vol 21, Iss 1, Pp 1-10 (2018)
In this work, two search algorithms Expectimax and Monte Carlo Tree Search (MCTS) were developed to solve the well-known “2048" puzzle online-game and compare their results. In both cases, five heuristics were employed to obtain favorable tile posi
Externí odkaz:
https://doaj.org/article/b2106097738c4762aba968539e3d642e
Este material suplementario contiene tablas, figuras y la base de datos (temperatura del agua del río Ichu y temperatura del aire de la estación Huancavelica-Perú) del artículoEvaluación y Predicción de la Temperatura del Agua en un río en los
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::1f959b0d2e42240862c964e51ad9a8f1
Autor:
null Efrain Noa-Yarasca, null Diana Chaca Ayuque, null Hugo A. Galvan Ccora, null Ivan A. Ayala Bizarro, null Ada Arancibia
Publikováno v:
Journal of Environmental Science and Engineering B. 11
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::4d213fe3c29d8f428d51522cb6a6d994
https://doi.org/10.17265/2162-5263/2022.05.001
https://doi.org/10.17265/2162-5263/2022.05.001
Autor:
Efrain Noa-Yarasca
This repository contains the necessary data and code to replicate and simulate the improved stream temperature model that supports the paper "An Improved Model of Shade-affected Stream Temperature in Soil & Water Assessment Tool". The SWAT model corr
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::7b14de35765f9274d81a1fbb3e260f9a
Stream temperatures have been increasing worldwide, in some cases reaching unsustainable levels for aquatic life. Riparian revegetation has been identified as a strategy for managing stream temperatures by blocking direct solar radiation. In this stu
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::7acf6cf90367f303a047a2b3198ba36e
https://hess.copernicus.org/preprints/hess-2022-116/
https://hess.copernicus.org/preprints/hess-2022-116/