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Domain adaptation framework with ensemble of fuzzy rules-based ELMs for remote-sensing image classification
The domain adaptation (DA) transfer learning technique can accurately classify land cover in remote-sensing (RS) images, even with a small number of...
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Multilayer extreme learning machine-based unsupervised deep feature representation for heartbeat classification
Heartbeat classification plays an important role in identifying cardiac arrhythmias. Although automated heartbeat classification approaches have been...
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Weighted ensembles of artificial neural networks based on Gaussian mixture modeling for truck productivity prediction at open-pit mines
The truck haulage data from open-pit mine sites are usually massive and multidimensional with multi-peak Gaussian distributions. Artificial neural...
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A two-stage model for stock price prediction based on variational mode decomposition and ensemble machine learning method
Accurate stock price prediction is critical for investment decisions in the stock market. To improve the performance of stock price prediction, this...
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Research on Combination Forecasting Method of Short-Term Electric Load in Nuclear Power Industrial Park
Accurate short-term electric load forecasting results are of important reference value to the energy system scheduling optimization and economic...
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An ELM-Based Ensemble Strategy for POI Recommendation
The prosperity of Location-Based Social Networks (LBSNs) facilitates a promising focus on personalized POI recommendation. The check-in activity is a...
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Unleashing the power of machine learning in cancer analysis: a novel gene selection and classifier ensemble strategy
PurposeGlobally, cancer is the second largest cause of mortality. For the improvement of cancer diagnosis, gene expression data plays a significant...
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Bio-inspired voting ensemble weighted extreme learning machine classifier for the detection of Parkinson’s disease
PurposeParkinson’s disease (PD) is a common neurological disorder. As early detection of the PD can help to control the disease, an automated...
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Hybrid WCA–PSO Optimized Ensemble Extreme Learning Machine and Wavelet Transform for Detection and Classification of Epileptic Seizure from EEG Signals
Epilepsy seizures are sudden, chaotic neurological functions. The complexity of the brain is revealed via electroencephalography (EEG). Visual...
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Rotation transformation-based selective ensemble of one-class extreme learning machines
Extreme learning machine (ELM) possesses merits of rapid learning speed and good generalization ability. However, due to the random initialization of...
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Proposition of new ensemble data-intelligence model for evapotranspiration process simulation
Due to climatic change, a variation in meteorological aspects influences the water requirement for crops, evapotranspiration, and water allocation of...
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Vibration Fault Analysis of Hydropower Units Based on Extreme Learning Machine Optimized by Improved Sparrow Search Algorithm
PurposeIn view of the complex non-linear relationship between vibration characteristics and fault types of hydropower units (HU), a fault diagnostic...
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A Tailored Complex Medical Decision Analysis Model for Diabetic Retinopathy Classification Based on Optimized Un-Supervised Feature Learning Approach
Diabetic Retinopathy has become a major medical concern all over the world. The only way to reduce the chances of vision loss due to diabetic...
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Arrhythmia Identification and Classification using Runge Kutta Optimizer-Based Hyperparameter Optimization for Long Short Term Memory
Arrhythmia denotes to the abnormalities in the rhythm of the heartbeat experienced by individuals. The arrhythmia potentially causes fatal...
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Automated X-ray recognition of solder bump defects based on ensemble-ELM
Solder bumps realize the mechanical and electrical interconnection between chips and substrates in surface mount components, such as flip chip, wafer...
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A Novel ELM Ensemble for Time Series Prediction
This paper presents a novel methodology for time series prediction. It is based on Extreme Learning Machines and an adaptive ensemble techniques. It...
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A novel analytical redundancy method based on decision-level fusion for aero-engine sensors
This paper addresses sensors’ analytical redundancy by a decision-level data fusion approach to improve the aero-engine control system reliability in...
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An adaptive extreme learning machine based on an active learning method for structural reliability analysis
The metamodel-assisted reliability method opens a promising way to achieve efficient structural reliability assessment for structures with...
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Ensemble Based Error Minimization Reduction for ELM
For better behavior of Extreme Learning Machine (ELM) in the limited condition that the number of training samples less than proper, an error...
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A New Feature Selection Method for Driving Fatigue Detection Using EEG Signals
This study aims to extract the high-level features of driving fatigue using electroencephalography (EEG). The commonly used feature selection method...