A review of recent machine learning advances for forecasting harmful algal blooms and shellfish contamination
Harmful algal blooms (HABs) are among the most severe ecological marine problems
worldwide. Under favorable climate and oceanographic conditions, toxin-producing …
worldwide. Under favorable climate and oceanographic conditions, toxin-producing …
[HTML][HTML] Data science, machine learning and big data in digital journalism: A survey of state-of-the-art, challenges and opportunities
Digital journalism has faced a dramatic change and media companies are challenged to use
data science algorithms to be more competitive in a Big Data era. While this is a relatively …
data science algorithms to be more competitive in a Big Data era. While this is a relatively …
A survey of ensemble learning: Concepts, algorithms, applications, and prospects
Ensemble learning techniques have achieved state-of-the-art performance in diverse
machine learning applications by combining the predictions from two or more base models …
machine learning applications by combining the predictions from two or more base models …
A novel framework for ultra-short-term interval wind power prediction based on RF-WOA-VMD and BiGRU optimized by the attention mechanism
M Yu, D Niu, T Gao, K Wang, L Sun, M Li, X Xu - Energy, 2023 - Elsevier
With resource shortages and global warming becoming increasingly serious, it is urgent to
accelerate the transition to green and low-carbon energy. Wind power, as a kind of green …
accelerate the transition to green and low-carbon energy. Wind power, as a kind of green …
[HTML][HTML] 基于优化负样本采样策略的梯度提升决策树与随机森林的汶川同震滑坡易发性评价
郭衍昊， 窦杰， 向子林， 马豪， 董傲男， 罗万祺 - 地质科技通报, 2024 - dzkjqb.cug.edu.cn
强震诱发的滑坡具有数量多, 分布广, 规模大等特点, 严重威胁人民生命财产安全.
滑坡易发性评价能够快速预测灾害空间分布, 对于减轻震后灾害的危险性具有重要意义 …
滑坡易发性评价能够快速预测灾害空间分布, 对于减轻震后灾害的危险性具有重要意义 …
[PDF][PDF] Science and Business
NM Abdulkareem, AM Abdulazeez - International Journal, 2021 - academia.edu
Machine Learning is a significant technique to realize Artificial Intelligence. The Random
Forest Algorithm can be considered as one of the Machine Learning's representative …
Forest Algorithm can be considered as one of the Machine Learning's representative …
Designing a sustainable bioethanol supply chain network: A combination of machine learning and meta-heuristic algorithms
Bioethanol demands have increased during the last decade due to unexpected events
worldwide. It is among the renewable energy sources that are utilized to replace fossil-fuel …
worldwide. It is among the renewable energy sources that are utilized to replace fossil-fuel …
Short-term electricity price forecasting based on similarity day screening, two-layer decomposition technique and Bi-LSTM neural network
K Wang, M Yu, D Niu, Y Liang, S Peng, X Xu - Applied Soft Computing, 2023 - Elsevier
Electricity price forecasting (EPF) has been challenged by the widespread grid integration of
renewable energy (RE), so it is critical to develop a highly accurate and reliable EPF model …
renewable energy (RE), so it is critical to develop a highly accurate and reliable EPF model …
An interpretable machine learning approach for hepatitis b diagnosis
Hepatitis B is a potentially deadly liver infection caused by the hepatitis B virus. It is a serious
public health problem globally. Substantial efforts have been made to apply machine …
public health problem globally. Substantial efforts have been made to apply machine …
[HTML][HTML] Land surface dynamics and meteorological forcings modulate land surface temperature characteristics
This study examines the effect of land cover, vegetation health, climatic forcings, elevation
heat loads, and terrain characteristics (LVCET) on land surface temperature (LST) …
heat loads, and terrain characteristics (LVCET) on land surface temperature (LST) …