|
|
|
|
|
Haekyung Park and Dong Kun Lee
Korea experienced an unexpected drought in the southern Seoul metropolitan area from 2015 to 2017. After that, the Korean government has been drafting various policies to mitigate the effects of drought. However, these are primarily long-term drought pol...
ver más
|
|
|
|
|
|
|
|
|
|
|
Wen Tian, Yining Zhang, Ying Zhang, Haiyan Chen and Weidong Liu
To fully leverage the spatiotemporal dynamic correlations in air traffic flow and enhance the accuracy of traffic flow prediction models, thereby providing a more precise basis for perceiving congestion situations in the air route network, a study was co...
ver más
|
|
|
|
|
|
|
|
|
|
|
Shuting Xu and Jinming Xu
The construction of deep foundation pits in subway stations can affect the settlement of existing buildings adjacent to the pits to varying degrees. In this paper, the Long Short-Term Memory neural network prediction model of building settlement caused b...
ver más
|
|
|
|
|
|
|
|
|
|
|
Zhiqing Guo, Xiaohui Chen, Ming Li, Yucheng Chi and Dongyuan Shi
Peanut leaf spot is a worldwide disease whose prevalence poses a major threat to peanut yield and quality, and accurate prediction models are urgently needed for timely disease management. In this study, we proposed a novel peanut leaf spot prediction me...
ver más
|
|
|
|
|
|
|
|
|
|
|
Mingze Li, Bing Li, Zhigang Qi, Jiashuai Li and Jiawei Wu
Predicting ship trajectories plays a vital role in ensuring navigational safety, preventing collision incidents, and enhancing vessel management efficiency. The integration of advanced machine learning technology for precise trajectory prediction is emer...
ver más
|
|
|
|
|
|
|
|
|
|
|
Seyed Mohammad Hashemi, Ruxandra Mihaela Botez and Georges Ghazi
Accurate aircraft trajectory prediction is fundamental for enhancing air traffic control systems, ensuring a safe and efficient aviation transportation environment. This research presents a detailed study on the efficacy of the Random Forest (RF) methodo...
ver más
|
|
|
|
|
|
|
|
|
|
|
Yin Tang, Lizhuo Zhang, Dan Huang, Sha Yang and Yingchun Kuang
In view of the current problems of complex models and insufficient data processing in ultra-short-term prediction of photovoltaic power generation, this paper proposes a photovoltaic power ultra-short-term prediction model named HPO-KNN-SRU, based on a S...
ver más
|
|
|
|
|
|
|
|
|
|
|
Feifei He, Qinjuan Wan, Yongqiang Wang, Jiang Wu, Xiaoqi Zhang and Yu Feng
Accurately predicting hydrological runoff is crucial for water resource allocation and power station scheduling. However, there is no perfect model that can accurately predict future runoff. In this paper, a daily runoff prediction method with a seasonal...
ver más
|
|
|
|
|
|
|
|
|
|
|
Yahui Hu, Jiaqi Yan, Ertai Cao, Yimeng Yu, Haiming Tian and Heyuan Huang
The statistical analysis of civil aircraft accidents reveals that the highest incidence of mishaps occurs during the approach and landing stages. Predominantly, these accidents are marked by abnormal energy states, leading to critical situations like sta...
ver más
|
|
|
|
|
|
|
|
|
|
|
Tianao Qin, Ruixin Chen, Rufu Qin and Yang Yu
Time series prediction is an effective tool for marine scientific research. The Hierarchical Temporal Memory (HTM) model has advantages over traditional recurrent neural network (RNN)-based models due to its online learning and prediction capabilities. G...
ver más
|
|
|
|
|
|