|
|
|
|
|
Saeed Samadianfard, Salar Jarhan, Ely Salwana, Amir Mosavi, Shahaboddin Shamshirband and Shatirah Akib
Advancement in river flow prediction systems can greatly empower the operational river management to make better decisions, practices, and policies. Machine learning methods recently have shown promising results in building accurate models for river flow...
ver más
|
|
|
|
|
|
|
|
|
|
|
Francisca Lanai Ribeiro Torres, Luana Medeiros Marangon Lima, Michelle Simões Reboita, Anderson Rodrigo de Queiroz and José Wanderley Marangon Lima
Streamflow forecasting plays a crucial role in the operational planning of hydro-dominant power systems, providing valuable insights into future water inflows to reservoirs and hydropower plants. It relies on complex mathematical models, which, despite t...
ver más
|
|
|
|
|
|
|
|
|
|
|
Yiming Chen and Shuang Liang
In the field of education, cognitive diagnosis is crucial for achieving personalized learning. The widely adopted DINA (Deterministic Inputs, Noisy And gate) model uncovers students? mastery of essential skills necessary to answer questions correctly. Ho...
ver más
|
|
|
|
|
|
|
|
|
|
|
Yufeng Wang, Xue Chen and Feng Xue
Spatial epidemiology investigates the patterns and determinants of health outcomes over both space and time. Within this field, Bayesian spatiotemporal models have gained popularity due to their capacity to incorporate spatial and temporal dependencies, ...
ver más
|
|
|
|
|
|
|
|
|
|
|
Ajmalud Din, Rozina Gul, Hamayoon Khan, Julian Garcia-Abadillo Velasco, Reyna Persa, Julio Isidro y Sánchez and Diego Jarquin
Chickpea is the second most important legume crop in pulses, and its performance is greatly influenced by environmental factors inducing a change in the response patterns, complicating the selection of the best cultivar(s). The genotype-by-environment (G...
ver más
|
|
|
|
|
|
|
|
|
|
|
Yunzhou Chen, Shumin Wang, Ziying Gu and Fan Yang
Spatial population distribution data is the discretization of demographic data into spatial grids, which has vital reference significance for disaster emergency response, disaster assessment, emergency rescue resource allocation, and post-disaster recons...
ver más
|
|
|
|
|
|
|
|
|
|
|
Yu Yao and Quan Qian
We develop the online process parameter design (OPPD) framework for efficiently handling streaming data collected from industrial automation equipment. This framework integrates online machine learning, concept drift detection and Bayesian optimization t...
ver más
|
|
|
|
|
|
|
|
|
|
|
Yalin Yang, Yanan Wu and May Yuan
In-person social events bring people to places, while people and places influence where and what social events occur. Knowing what people do and where they build social relationships gives insights into the distribution and availability of places for soc...
ver más
|
|
|
|
|
|
|
|
|
|
|
Saile Zhang, Qingzhen Yang, Rui Wang and Xufei Wang
The use of traditional optimization methods in engineering design problems, specifically in aerodynamic and infrared stealth optimization for engine nozzles, requires a large number of objective function evaluations, therefore introducing a considerable ...
ver más
|
|
|
|
|
|
|
|
|
|
|
Krzysztof Drachal and Michal Pawlowski
This study firstly applied a Bayesian symbolic regression (BSR) to the forecasting of numerous commodities? prices (spot-based ones). Moreover, some features and an initial specification of the parameters of the BSR were analysed. The conventional approa...
ver más
|
|
|
|
|
|