A Review of multilayer extreme learning machine neural networks
Abstract The Extreme Learning Machine is a single-hidden-layer feedforward learning
algorithm, which has been successfully applied in regression and classification problems in …
algorithm, which has been successfully applied in regression and classification problems in …
[HTML][HTML] A hybrid stock trading framework integrating technical analysis with machine learning techniques
In this paper, a novel decision support system using a computational efficient functional link
artificial neural network (CEFLANN) and a set of rules is proposed to generate the trading …
artificial neural network (CEFLANN) and a set of rules is proposed to generate the trading …
Design and implementation of a hybrid model based on two-layer decomposition method coupled with extreme learning machines to support real-time environmental …
Accurate prediction of water quality parameters plays a crucial and decisive role in
environmental monitoring, ecological systems sustainability, human health, aquaculture and …
environmental monitoring, ecological systems sustainability, human health, aquaculture and …
An improved cuckoo search based extreme learning machine for medical data classification
Abstract Machine learning techniques are being increasingly used for detection and
diagnosis of diseases for its accuracy and efficiency in pattern classification. In this paper …
diagnosis of diseases for its accuracy and efficiency in pattern classification. In this paper …
Dissolved oxygen prediction using a new ensemble method
Prediction of dissolved oxygen which is an important water quality (WQ) parameter is crucial
for aquatic managers who have responsibility for the ecosystem health's maintenance and …
for aquatic managers who have responsibility for the ecosystem health's maintenance and …
Application of machine learning methods in photovoltaic output power prediction: A review
W Zhang, Q Li, Q He - Journal of Renewable and Sustainable Energy, 2022 - pubs.aip.org
As the proportion of photovoltaic (PV) power generation rapidly increases, accurate PV
output power prediction becomes more crucial to energy efficiency and renewable energy …
output power prediction becomes more crucial to energy efficiency and renewable energy …
[HTML][HTML] Stock market prediction using Firefly algorithm with evolutionary framework optimized feature reduction for OSELM method
Forecasting future trends of the stock market using the historical data is the exigent demand
in the field of academia as well as business. This work has explored the feature optimization …
in the field of academia as well as business. This work has explored the feature optimization …
Modelling long-term groundwater fluctuations by extreme learning machine using hydro-climatic data
M Alizamir, O Kisi… - Hydrological sciences …, 2018 - Taylor & Francis
The ability of the extreme learning machine (ELM) is investigated in modelling groundwater
level (GWL) fluctuations using hydro-climatic data obtained for Hormozgan Province …
level (GWL) fluctuations using hydro-climatic data obtained for Hormozgan Province …
A self adaptive differential harmony search based optimized extreme learning machine for financial time series prediction
This paper proposes a hybrid learning framework called Self Adaptive Differential Harmony
Search Based Optimized Extreme Learning Machine (SADHS-OELM) for single hidden layer …
Search Based Optimized Extreme Learning Machine (SADHS-OELM) for single hidden layer …
Extreme learning machine for ranking: generalization analysis and applications
The extreme learning machine (ELM) has attracted increasing attention recently with its
successful applications in classification and regression. In this paper, we investigate the …
successful applications in classification and regression. In this paper, we investigate the …