A comparative evaluation for identifying the suitability of extreme learning machine to predict horizontal global solar radiation
S Shamshirband, K Mohammadi, L Yee… - … and sustainable energy …, 2015 - Elsevier
In this paper, the extreme learning machine (ELM) is employed to predict horizontal global
solar radiation (HGSR). For this purpose, the capability of developed ELM method is …
solar radiation (HGSR). For this purpose, the capability of developed ELM method is …
Using self-adaptive evolutionary algorithm to improve the performance of an extreme learning machine for estimating soil temperature
In this study, the self-adaptive evolutionary (SaE) agent is employed to structure the
contributing elements to process the management of extreme learning machine (ELM) …
contributing elements to process the management of extreme learning machine (ELM) …
Extreme learning machine based prediction of daily dew point temperature
K Mohammadi, S Shamshirband, S Motamedi… - … and Electronics in …, 2015 - Elsevier
The dew point temperature is a significant element particularly required in various
hydrological, climatological and agronomical related researches. This study proposes an …
hydrological, climatological and agronomical related researches. This study proposes an …
A new technique for ECG signal classification genetic algorithm Wavelet Kernel extreme learning machine
The examination and classification of Electrocardiogram (ECG) records have become
particularly significant for diagnosing heart diseases. Machine learning methods are widely …
particularly significant for diagnosing heart diseases. Machine learning methods are widely …
Comparative analysis of reference evapotranspiration equations modelling by extreme learning machine
M Gocic, D Petković, S Shamshirband… - … and Electronics in …, 2016 - Elsevier
This study presents an extreme learning machine (ELM) approach, for estimating monthly
reference evapotranspiration (ET 0) in two weather stations in Serbia (Nis and Belgrade …
reference evapotranspiration (ET 0) in two weather stations in Serbia (Nis and Belgrade …
Evaluation of prediction and forecasting models for evapotranspiration of agricultural lands in the Midwest US
Evapotranspiration (ET) prediction and forecasting play a vital role in improving water use in
agriculturally intensive areas. Metrological and biophysical predictors that drive ET in …
agriculturally intensive areas. Metrological and biophysical predictors that drive ET in …
[PDF][PDF] 基于MO-PLP-ELM 及电容层析成像的两相流流型辨识
张立峰， 朱炎峰 - 计量学报, 2021 - jlxb.china-csm.org
提出一种基于多目标优化并行感知器的极限学习机(MO PLP ELM) 及电容层析成像(ECT)
技术的两相流流型辨识算法. 首先, 为保证样本具有代表性, 采用随机思想生成7 …
技术的两相流流型辨识算法. 首先, 为保证样本具有代表性, 采用随机思想生成7 …
A novel ECG signal classification method using DEA-ELM
Electrocardiogram (ECG) signals represent the electrical mobility of the human heart. In
recent years, computer-aided systems have helped to cardiologists in the detection …
recent years, computer-aided systems have helped to cardiologists in the detection …
A fast incremental extreme learning machine algorithm for data streams classification
S Xu, J Wang - Expert systems with applications, 2016 - Elsevier
Data streams classification is an important approach to get useful knowledge from massive
and dynamic data. Because of concept drift, traditional data mining techniques cannot be …
and dynamic data. Because of concept drift, traditional data mining techniques cannot be …
Examination of the ECG signal classification technique DEA-ELM using deep convolutional neural network features
The accurate separation of ECG signals has become crucial to identify heart diseases.
Machine learning methods are widely used to separate ECG signals. The aim of this study …
Machine learning methods are widely used to separate ECG signals. The aim of this study …