Extreme learning machines: a new approach for modeling dissolved oxygen (DO) concentration with and without water quality variables as predictors

An extreme learning machine model for the simulation of monthly mean streamflow water level in eastern Queensland

(2016) Ravinesh C Deo et al.   ENVIRONMENTAL MONITORING AND ASSESSMENT

Stream-flow forecasting using extreme learning machines: A case study in a semi-arid region in Iraq

(2016) Zaher Mundher Yaseen et al.   JOURNAL OF HYDROLOGY

Forecasting daily streamflow using online sequential extreme learning machines

(2016) Aranildo R. Lima et al.   JOURNAL OF HYDROLOGY

Estimation of dissolved oxygen by using neural networks and neuro fuzzy computing techniques

(2016) Murat Ay et al.   KSCE Journal of Civil Engineering

Discharge forecasting using an Online Sequential Extreme Learning Machine (OS-ELM) model: A case study in Neckar River, Germany

(2016) Basant Yadav et al.   MEASUREMENT

Online Sequential Extreme Learning Machine for watermarking in DWT domain

(2016) Ram Pal Singh et al.   NEUROCOMPUTING

Prediction of Water-Level in the Urmia Lake Using the Extreme Learning Machine Approach

(2016) Jalal Shiri et al.   WATER RESOURCES MANAGEMENT

Extreme Learning Machines: A new approach for prediction of reference evapotranspiration

(2015) Shafika Sultan Abdullah et al.   JOURNAL OF HYDROLOGY

Development of wavelet-ANN models to predict water quality parameters in Hilo Bay, Pacific Ocean

(2015) Mohamad Javad Alizadeh et al.   MARINE POLLUTION BULLETIN

Trends in extreme learning machines: A review

(2015) Gao Huang et al.   NEURAL NETWORKS

MD-ELM: Originally Mislabeled Samples Detection using OP-ELM Model

(2015) Anton Akusok et al.   NEUROCOMPUTING

What are Extreme Learning Machines? Filling the Gap Between Frank Rosenblatt’s Dream and John von Neumann’s Puzzle

(2015) Guang-Bin Huang   Cognitive Computation

Modelling hourly dissolved oxygen concentration (DO) using dynamic evolving neural-fuzzy inference system (DENFIS)-based approach: case study of Klamath River at Miller Island Boat Ramp, OR, USA

(2014) Salim Heddam   ENVIRONMENTAL SCIENCE AND POLLUTION RESEARCH

Generalized regression neural network-based approach for modelling hourly dissolved oxygen concentration in the Upper Klamath River, Oregon, USA

(2014) Salim Heddam   ENVIRONMENTAL TECHNOLOGY

Modeling of Dissolved Oxygen in River Water Using Artificial Intelligence Techniques

(2014) O. Kisi   Journal of Environmental Informatics

Robust empirical modeling of dissolved oxygen in small rivers and streams: Scaling by a single reference observation

(2014) Omar I. Abdul-Aziz et al.   JOURNAL OF HYDROLOGY

Online sequential extreme learning machine with kernels for nonstationary time series prediction

(2014) Xinying Wang et al.   NEUROCOMPUTING

Regression model-based predictions of diel, diurnal and nocturnal dissolved oxygen dynamics after wavelet denoising of noisy time series

(2014) F. Evrendilek et al.   PHYSICA A-STATISTICAL MECHANICS AND ITS APPLICATIONS

Spatiotemporal modeling of saturated dissolved oxygen through regressions after wavelet denoising of remotely and proximally sensed data

(2014) F. Evrendilek et al.   Earth Science Informatics

Input selection and optimisation for monthly rainfall forecasting in Queensland, Australia, using artificial neural networks

(2013) John Abbot et al.   ATMOSPHERIC RESEARCH

Prediction of dissolved oxygen content in river crab culture based on least squares support vector regression optimized by improved particle swarm optimization

(2013) Shuangyin Liu et al.   COMPUTERS AND ELECTRONICS IN AGRICULTURE

A hybrid WA–CPSO-LSSVR model for dissolved oxygen content prediction in crab culture

(2013) Shuangyin Liu et al.   ENGINEERING APPLICATIONS OF ARTIFICIAL INTELLIGENCE

Modeling hourly dissolved oxygen concentration (DO) using two different adaptive neuro-fuzzy inference systems (ANFIS): a comparative study

(2013) Salim Heddam   ENVIRONMENTAL MONITORING AND ASSESSMENT

Monitoring diel dissolved oxygen dynamics through integrating wavelet denoising and temporal neural networks

(2013) Fatih Evrendilek et al.   ENVIRONMENTAL MONITORING AND ASSESSMENT

Monthly water quality forecasting and uncertainty assessment via bootstrapped wavelet neural networks under missing data for Harbin, China

(2013) Yi Wang et al.   ENVIRONMENTAL SCIENCE AND POLLUTION RESEARCH

Long-term time series prediction using OP-ELM

(2013) Alexander Grigorievskiy et al.   NEURAL NETWORKS

Extreme learning machines for soybean classification in remote sensing hyperspectral images

(2013) Ramón Moreno et al.   NEUROCOMPUTING

Study of short-term water quality prediction model based on wavelet neural network

(2012) Longqin Xu et al.   MATHEMATICAL AND COMPUTER MODELLING

Extreme Learning Machine for Regression and Multiclass Classification

(2011) Guang-Bin Huang et al.   IEEE TRANSACTIONS ON SYSTEMS MAN AND CYBERNETICS PART B-CYBERNETICS

Depth-Integrated Estimation of Dissolved Oxygen in a Lake

(2011) A. Akkoyunlu et al.   JOURNAL OF ENVIRONMENTAL ENGINEERING

Prediction of dissolved oxygen in reservoirs using adaptive network-based fuzzy inference system

(2011) Vesna Ranković et al.   JOURNAL OF HYDROINFORMATICS

Extreme learning machines: a survey

(2011) Guang-Bin Huang et al.   International Journal of Machine Learning and Cybernetics

OPELM and OPKNN in long-term prediction of time series using projected input data

(2010) Dušan Sovilj et al.   NEUROCOMPUTING

A hybrid neural network and ARIMA model for water quality time series prediction

(2009) Durdu Ömer Faruk   ENGINEERING APPLICATIONS OF ARTIFICIAL INTELLIGENCE

OP-ELM: Optimally Pruned Extreme Learning Machine

(2009) Yoan Miche et al.   IEEE TRANSACTIONS ON NEURAL NETWORKS