4.7 Article

A novel interval decomposition correlation particle swarm optimization-extreme learning machine model for short-term and long-term water quality prediction

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A novel PSO-KELM based soil liquefaction potential evaluation system using CPT and Vs measurements

Zening Zhao et al.

Summary: This study proposes a novel soil liquefaction potential evaluation system combining CPT and Vs measurements, using the machine learning model PSO-KELM to assess soil liquefaction potential, and develops a new probabilistic model to improve prediction accuracy.

SOIL DYNAMICS AND EARTHQUAKE ENGINEERING (2021)

Article Water Resources

Performance of machine learning methods in predicting water quality index based on irregular data set: application on Illizi region (Algerian southeast)

Saber Kouadri et al.

Summary: Groundwater quality appraisal is essential for safe drinking water sources, and the study utilized 8 artificial intelligence algorithms to predict water quality index in Illizi region, southeast Algeria. Key drivers influencing WQI were identified as total dissolved solids (TDS) and total hardness (TH), with different input combinations and analysis strategies impacting time consumption and error rates in WQI computation.

APPLIED WATER SCIENCE (2021)

Article Environmental Sciences

Time-series temperature analyses indicate conduction and diffusion are dominant heat-transfer processes in fine sediment, low-flow streams

Chester G. Scotch et al.

Summary: The study utilized thermal methods, Darcy's law, and electrical resistivity evaluations to improve understanding of flow and transport processes in low permeability, low-flow coastal streams. The seasonal-trend decomposition using Loess (STL) method was tested and validated as a means to differentiate between advection and conduction. Results showed that conduction and diffusion are dominant processes of heat and solute transfer in fine-sediment streambeds, providing insights into groundwater-stream interaction and water resources in semiarid coastal areas.

SCIENCE OF THE TOTAL ENVIRONMENT (2021)

Article Thermodynamics

A multi-step ahead photovoltaic power prediction model based on similar day, enhanced colliding bodies optimization, variational mode decomposition, and deep extreme learning machine

Qing Li et al.

Summary: The study proposed a similar day-based ultrashort-term multi-step ahead prediction model of photovoltaic power, which combines various optimization methods and algorithms. Experimental results demonstrated that the model has high accuracy in multi-step prediction, strong intelligence capabilities, and can be easily applied and popularized in practical projects.

ENERGY (2021)

Article Environmental Sciences

Comprehensive water quality evaluation based on kernel extreme learning machine optimized with the sparrow search algorithm in Luoyang River Basin, China

Chenguang Song et al.

Summary: A water quality evaluation model based on KELM and optimized with SSA in the Luoyang River Basin outperformed other benchmark models, showing fast learning speed and good generalization performance. The hybrid model can successfully overcome nonstationarity, randomness, and nonlinearity in water quality data and provide valuable insights for water environment protection and management planning in the basin.

ENVIRONMENTAL EARTH SCIENCES (2021)

Article Computer Science, Artificial Intelligence

A VMD-EWT-LSTM-based multi-step prediction approach for shield tunneling machine cutterhead torque

Gang Shi et al.

Summary: This study proposes a novel hybrid multi-step prediction model based on VMD-EWT-LSTM, which accurately predicts the cutterhead torque of shield tunneling machine in multiple time steps and demonstrates higher accuracy compared to other methods.

KNOWLEDGE-BASED SYSTEMS (2021)

Article Engineering, Environmental

Comparison of the performance of decision tree (DT) algorithms and extreme learning machine (ELM) model in the prediction of water quality of the Upper Green River watershed

Jagadeesh Anmala et al.

Summary: The study investigates the prediction of stream water quality parameters using decision trees, with the quantitative prediction of water quality parameters in the Upper Green River watershed. Multivariate statistical techniques, including artificial neural networks, have been used to gain a deeper understanding of stream water quality status.

WATER ENVIRONMENT RESEARCH (2021)

Article Environmental Sciences

Dissolved oxygen prediction using a new ensemble method

Ozgur Kisi et al.

ENVIRONMENTAL SCIENCE AND POLLUTION RESEARCH (2020)

Article Computer Science, Artificial Intelligence

A novel hybrid model based on multi-objective Harris hawks optimization algorithm for daily PM2.5 and PM10 forecasting

Pei Du et al.

APPLIED SOFT COMPUTING (2020)

Article Engineering, Geological

High performance prediction of soil compaction parameters using multi expression programming

Han-Lin Wang et al.

ENGINEERING GEOLOGY (2020)

Article Computer Science, Information Systems

Parameters Analysis of Sample Entropy, Permutation Entropy and Permutation Ratio Entropy for RR Interval Time Series

Jian Yin et al.

INFORMATION PROCESSING & MANAGEMENT (2020)

Article Multidisciplinary Sciences

Chlorine Soft Sensor Based on Extreme Learning Machine for Water Quality Monitoring

Mohamed Djerioui et al.

ARABIAN JOURNAL FOR SCIENCE AND ENGINEERING (2019)

Article Engineering, Environmental

Multi-step water quality forecasting using a boosting ensemble multi-wavelet extreme learning machine model

Rahim Barzegar et al.

STOCHASTIC ENVIRONMENTAL RESEARCH AND RISK ASSESSMENT (2018)

Article Automation & Control Systems

Nonlinear System Modeling Using RBF Networks for Industrial Application

Xi Meng et al.

IEEE TRANSACTIONS ON INDUSTRIAL INFORMATICS (2018)

Article Engineering, Civil

An adaptive middle and long-term runoff forecast model using EEMD-ANN hybrid approach

Qiao-Feng Tan et al.

JOURNAL OF HYDROLOGY (2018)

Article Engineering, Mechanical

Sparsity guided empirical wavelet transform for fault diagnosis of rolling element bearings

Dong Wang et al.

MECHANICAL SYSTEMS AND SIGNAL PROCESSING (2018)

Article Computer Science, Artificial Intelligence

Characterizing dynamics of absence seizure EEG with spatial-temporal permutation entropy

Ke Zeng et al.

NEUROCOMPUTING (2018)

Article Biodiversity Conservation

ELM evaluation model of regional groundwater quality based on the crow search algorithm

Dong Liu et al.

ECOLOGICAL INDICATORS (2017)

Review Multidisciplinary Sciences

Probabilistic machine learning and artificial intelligence

Zoubin Ghahramani

NATURE (2015)

Article Engineering, Mechanical

Permutation entropy: A nonlinear statistical measure for status characterization of rotary machines

Ruqiang Yan et al.

MECHANICAL SYSTEMS AND SIGNAL PROCESSING (2012)

Article Multidisciplinary Sciences

Global threats to human water security and river biodiversity

C. J. Voeroesmarty et al.

NATURE (2010)