The formation and impact of landslide dams–State of the art
The blocking of river courses by mass movements is very common in mountainous areas
with deep and narrow valleys. Landslide dams may pose serious threats to people and their …
with deep and narrow valleys. Landslide dams may pose serious threats to people and their …
Neural network-based parametric system identification: A review
Parametric system identification, which is the process of uncovering the inherent dynamics
of a system based on the model built with the observed inputs and outputs data, has been …
of a system based on the model built with the observed inputs and outputs data, has been …
[PDF][PDF] 基于机器学习的设备剩余寿命预测方法综述
裴洪， 胡昌华， 司小胜， 张建勋， 庞哲楠， 张鹏 - 机械工程学报, 2019 - qikan.cmes.org
随着科学技术的发展和生产工艺的进步, 当代设备日益朝着大型化, 复杂化,
自动化以及智能化方向发展. 为保障设备安全性与可靠性, 剩余寿命(Remaining useful life …
自动化以及智能化方向发展. 为保障设备安全性与可靠性, 剩余寿命(Remaining useful life …
A two-stage method based on extreme learning machine for predicting the remaining useful life of rolling-element bearings
Z Pan, Z Meng, Z Chen, W Gao, Y Shi - Mechanical Systems and Signal …, 2020 - Elsevier
Rolling-element bearing is one of the main parts of rotating equipment. In order to avoid the
mechanical equipment damage caused by the sudden failure of rolling-element bearings, it …
mechanical equipment damage caused by the sudden failure of rolling-element bearings, it …
Electricity price forecasting by a hybrid model, combining wavelet transform, ARMA and kernel-based extreme learning machine methods
Z Yang, L Ce, L Lian - Applied Energy, 2017 - Elsevier
Electricity prices have rather complex features such as high volatility, high frequency,
nonlinearity, mean reversion and non-stationarity that make forecasting very difficult …
nonlinearity, mean reversion and non-stationarity that make forecasting very difficult …
Continuous online sequence learning with an unsupervised neural network model
The ability to recognize and predict temporal sequences of sensory inputs is vital for survival
in natural environments. Based on many known properties of cortical neurons, hierarchical …
in natural environments. Based on many known properties of cortical neurons, hierarchical …
[HTML][HTML] Estimation of moment and rotation of steel rack connections using extreme learning machine
The estimation of moment and rotation in steel rack connections could be significantly
helpful parameters for designers and constructors in the initial designing and construction …
helpful parameters for designers and constructors in the initial designing and construction …
An intrusion detection system using network traffic profiling and online sequential extreme learning machine
Abstract Anomaly based Intrusion Detection Systems (IDS) learn normal and anomalous
behavior by analyzing network traffic in various benchmark datasets. Common challenges …
behavior by analyzing network traffic in various benchmark datasets. Common challenges …
Forecasting of groundwater level fluctuations using ensemble hybrid multi-wavelet neural network-based models
Accurate prediction of groundwater level (GWL) fluctuations can play an important role in
water resources management. The aims of the research are to evaluate the performance of …
water resources management. The aims of the research are to evaluate the performance of …
RETRACTED ARTICLE: Potential of soft computing approach for evaluating the factors affecting the capacity of steel–concrete composite beam
Abstract Evaluation of the parameters affecting the shear strength and ductility of steel–
concrete composite beam is the goal of this study. This study focuses on predicting the future …
concrete composite beam is the goal of this study. This study focuses on predicting the future …