Flood prediction using machine learning models: Literature review
Floods are among the most destructive natural disasters, which are highly complex to model.
The research on the advancement of flood prediction models contributed to risk reduction …
The research on the advancement of flood prediction models contributed to risk reduction …
Advancements in condition monitoring and fault diagnosis of rotating machinery: A comprehensive review of image-based intelligent techniques for induction motors
Recently, condition monitoring (CM) and fault detection and diagnosis (FDD) techniques for
rotating machinery (RM) have witnessed substantial advancements in recent decades …
rotating machinery (RM) have witnessed substantial advancements in recent decades …
[HTML][HTML] Urban pluvial flooding prediction by machine learning approaches–a case study of Shenzhen city, China
Urban pluvial flooding is a threatening natural hazard in urban areas all over the world,
especially in recent years given its increasing frequency of occurrence. In order to prevent …
especially in recent years given its increasing frequency of occurrence. In order to prevent …
[HTML][HTML] A multi-strategy-mode waterlogging-prediction framework for urban flood depth
Flooding is one of the most disruptive natural disasters, causing substantial loss of life and
property damage. Coastal cities in Asia face floods almost every year due to monsoon …
property damage. Coastal cities in Asia face floods almost every year due to monsoon …
Ensemble learning technology for coastal flood forecasting in internet-of-things-enabled smart city
W Dai, Y Tang, Z Zhang, Z Cai - International Journal of Computational …, 2021 - Springer
Flooding is becoming a prominent issue in coastal cities, flood forecasting is the key to
solving this problem. However, the lack and imbalance of research data and the insufficient …
solving this problem. However, the lack and imbalance of research data and the insufficient …
Flood prediction using IoT and artificial neural networks with edge computing
Flood disasters affect millions of people across the world by causing severe loss of life and
colossal damage to property. Internet of Things (IoT) has been applied in areas such as …
colossal damage to property. Internet of Things (IoT) has been applied in areas such as …
Energy-based damage localization under ambient vibration and non-stationary signals by ensemble empirical mode decomposition and Mahalanobis-squared …
H Sarmadi, A Entezami… - Journal of Vibration …, 2020 - journals.sagepub.com
Damage localization of damaged structures is an important issue in structural health
monitoring. In data-based methods based on statistical pattern recognition, it is necessary to …
monitoring. In data-based methods based on statistical pattern recognition, it is necessary to …
Development of a Three‐Stage Hybrid Model by Utilizing a Two‐Stage Signal Decomposition Methodology and Machine Learning Approach to Predict Monthly Runoff …
Precise and reliable hydrological runoff prediction plays a significant role in the optimal
management of hydropower resources. Nevertheless, the hydrological runoff practically …
management of hydropower resources. Nevertheless, the hydrological runoff practically …
[PDF][PDF] Applicability of a three-stage hybrid model by employing a two-stage signal decomposition approach and a deep learning methodology for runoff forecasting at …
The optimal management of hydropower resources is highly dependent on accurate and
reliable hydrological runoff forecasting. The development of a suitable runoff-forecasting …
reliable hydrological runoff forecasting. The development of a suitable runoff-forecasting …
Novel time–frequency mode decomposition and information fusion for bearing fault diagnosis under varying-speed condition
Rolling bearing fault diagnosis is significant in rotating machinery daily maintenance.
However, it is still difficult to diagnose the weak fault of rolling bearing under variable speed …
However, it is still difficult to diagnose the weak fault of rolling bearing under variable speed …