Water Quality Prediction Based on Machine Learning and Comprehensive Weighting Methods

Water Quality Prediction Based on Machine Learning and Comprehensive Weighting Methods

In the context of escalating global environmental concerns, the importance of preserving water resources and upholding ecological equilibrium has become increasingly apparent. As a result, the monitoring and prediction of water quality have emerged as vital tasks in achieving these objectives. Howev...

Full description

Bibliographic Details
Main Authors:	Xianhe Wang, Ying Li, Qian Qiao, Adriano Tavares, Yanchun Liang
Format:	Article
Language:	English
Published:	MDPI AG 2023-08-01
Series:	Entropy
Subjects:	water quality prediction comprehensive weight-based approach feature selection machine learning LSTM
Online Access:	https://www.mdpi.com/1099-4300/25/8/1186

Similar Items

A Review of Feature Selection Methods for Machine Learning-Based Disease Risk Prediction
by: Nicholas Pudjihartono, et al.
Published: (2022-06-01)

Machine learning approach for the prediction of macrosomia
by: Xiaochen Gu, et al.
Published: (2024-08-01)

Impacts of Feature Selection on Predicting Machine Failures by Machine Learning Algorithms
by: Francisco Elânio Bezerra, et al.
Published: (2024-04-01)

Innovations in Stroke Identification: A Machine Learning-Based Diagnostic Model Using Neuroimages
by: Muhammad Asim Saleem, et al.
Published: (2024-01-01)

Hyperspectral Image Classification Using Comprehensive Evaluation Model of Extreme Learning Machine Based on Cumulative Variation Weights
by: Yuping Yin, et al.
Published: (2020-01-01)

Email spam detection by deep learning models using novel feature selection technique and BERT
by: Ghazala Nasreen, et al.
Published: (2024-06-01)

Optimising Insider Threat Prediction: Exploring BiLSTM Networks and Sequential Features
by: Phavithra Manoharan, et al.
Published: (2024-11-01)

Expressway Exit Station Short-Term Traffic Flow Prediction With Split Traffic Flows According Originating Entry Stations
by: Housong Ruan, et al.
Published: (2021-01-01)

Cocrystal Prediction Using Machine Learning Models and Descriptors
by: Medard Edmund Mswahili, et al.
Published: (2021-02-01)

Predicting the academic progression in student’s standpoint using machine learning
by: M. S. Sassirekha, et al.
Published: (2022-12-01)

A Predictive Model of Reading Comprehension Based on MEG Imaginary Coherence Functional Connections
by: Limin ZHAO, et al.
Published: (2023-09-01)

MVHS-LSTM: The Comprehensive Traffic Flow Prediction Based on Improved LSTM via Multiple Variables Heuristic Selection
by: Chang Guo, et al.
Published: (2024-03-01)

A Novel Hybrid Strategy Using Three-Phase Feature Extraction and a Weighted Regularized Extreme Learning Machine for Multi-Step Ahead Wind Speed Prediction
by: Jujie Wang, et al.
Published: (2018-02-01)

A Novel Approach to Improve Software Defect Prediction Accuracy Using Machine Learning
by: Iqra Mehmood, et al.
Published: (2023-01-01)

Dropout Prediction Model for College Students in MOOCs Based on Weighted Multi-feature and SVM
by: Zhang Yujiao, et al.
Published: (2023-09-01)

Bearing Fault Feature Selection Method Based on Weighted Multidimensional Feature Fusion
by: Yazhou Li, et al.
Published: (2020-01-01)

Sentiment Analysis Based Requirement Evolution Prediction
by: Lingling Zhao, et al.
Published: (2019-02-01)

Cooperative prediction method of gas emission from mining face based on feature selection and machine learning
by: Jie Zhou, et al.
Published: (2022-07-01)

A deep learning approach for classifying and predicting children's nutritional status in Ethiopia using LSTM-FC neural networks
by: Getnet Bogale Begashaw, et al.
Published: (2025-01-01)

Prediction of NOx Concentration at SCR Inlet Based on BMIFS-LSTM
by: Meiyan Song, et al.
Published: (2022-04-01)

Penggunaan Feature Selection di Algoritma Support Vector Machine untuk Sentimen Analisis Komisi Pemilihan Umum
by: Imam Santoso, et al.
Published: (2019-12-01)

Benchmarking Machine Translation Efficacy for Teaching EAP Reading Comprehension Skills
by: V. Mirzaeian, et al.
Published: (2023-12-01)

Extracting Optimal Number of Features for Machine Learning Models in Multilayer IoT Attacks
by: Badeea Al Sukhni, et al.
Published: (2024-12-01)

A review on coal and gas outburst prediction based on machine learning
by: Sheng XUE, et al.
Published: (2024-03-01)

Analysis of traditional machine learning approaches on heart attacks prediction
by: Micheal BERDINANTH, et al.
Published: (2024-03-01)

Comprehensive Harmonic Responsibility Calculation Based on Different Weighting Methods
by: Mingxing Tian, et al.
Published: (2019-11-01)

GETdb: A comprehensive database for genetic and evolutionary features of drug targets
by: Qi Zhang, et al.
Published: (2024-12-01)

Robust identification key predictors of short- and long-term weight status in children and adolescents by machine learning
by: Hengyan Liu, et al.
Published: (2024-09-01)

Machine learning algorithms for predicting the risk of fracture in patients with diabetes in China
by: Sijia Chu, et al.
Published: (2023-07-01)

Prediction of Severity of COVID-19-Infected Patients Using Machine Learning Techniques
by: Aziz Alotaibi, et al.
Published: (2021-03-01)

Efficient Machine Learning Models for Early Stage Detection of Autism Spectrum Disorder
by: Mousumi Bala, et al.
Published: (2022-05-01)

Application of machine learning algorithms and feature selection in rapeseed (Brassica napus L.) breeding for seed yield
by: Masoud Shahsavari, et al.
Published: (2023-06-01)

Phishing Website Detection Using Deep Learning Models
by: Ume Zara, et al.
Published: (2024-01-01)

A Hybrid Approach for Forecasting Occupancy of Building’s Multiple Space Types
by: Iqra Rafiq, et al.
Published: (2024-01-01)

Formwork material selection and optimization by a comprehensive integrated subjective–objective criteria weighting MCDM model
by: Tamene Taye Worku
Published: (2025-01-01)

Modification of Hidden Layer Weight in Extreme Learning Machine Using Gain Ratio
by: Anggraeny Fetty Tri, et al.
Published: (2016-01-01)

Optimizing Machine Learning Algorithms for Improving Prediction of Bridge Deck Deterioration: A Case Study of Ohio Bridges
by: Armin Rashidi Nasab, et al.
Published: (2023-06-01)

A Machine Learning Model for the Prediction of COVID-19 Severity Using RNA-Seq, Clinical, and Co-Morbidity Data
by: Sahil Sethi, et al.
Published: (2024-06-01)

Bug Severity Prediction Algorithm Using Topic-Based Feature Selection and CNN-LSTM Algorithm
by: Jungyeon Kim, et al.
Published: (2022-01-01)

Brain Signals to Actions Using Machine Learning
by: Dimitris Angelakis, et al.
Published: (2023-10-01)