4.7 Article

Saltwater intrusion early warning in Pearl river Delta based on the temporal clustering method

相关参考文献

注意:仅列出部分参考文献,下载原文获取全部文献信息。
Article Neurosciences

Prediction of patients with idiopathic generalized epilepsy from healthy controls using machine learning from scalp EEG recordings

F. A. Escobar-Ipuz et al.

Summary: Epilepsy detection is crucial for patients, researchers, and medical staff. In this study, machine learning techniques, specifically the extreme gradient boosting (XGB) method, were used to differentiate patients with idiopathic generalized epilepsy from healthy controls based on interictal electroencephalographic recordings. The XGB method achieved higher accuracy and better prediction of distinct features in EEG signals compared to other machine learning methods tested. This research demonstrates the potential of machine learning techniques in assisting clinicians with the identification and prediction of generalized epilepsy from scalp EEG studies.

BRAIN RESEARCH (2023)

Article Archaeology

Fire risk level prediction of timber heritage buildings based on entropy and XGBoost

Yating Lei et al.

Summary: Historic timber-structure buildings pose various fire threats and predicting their fire risk based on historical fire events is challenging due to limited data. This study proposes a machine learning-based solution using a fire risk index to predict the fire risk level of timber heritage buildings.

JOURNAL OF CULTURAL HERITAGE (2023)

Article Public, Environmental & Occupational Health

Adverse childhood experiences and clustering of high-risk behaviors among high school students: a cross-sectional study

M. Diedrick et al.

Summary: This study examined the link between adverse childhood experiences (ACEs) and clustering of high-risk behaviors in high school students. The cross-sectional study surveyed a sample of students from 99 high schools in Nevada. Results showed a strong association between cumulative ACE score and the count of high-risk behavior domains.

PUBLIC HEALTH (2023)

Article Computer Science, Artificial Intelligence

An integrated optimization and machine learning approach to predict the admission status of emergency patients

Abdulaziz Ahmed et al.

Summary: This work proposes a framework for optimizing machine learning algorithms and demonstrates its practicality through a case study in the healthcare domain. The framework addresses the crowding problem by proactively planning the patient boarding process. By training and testing on a large dataset of patient records, the study compares the performance of different algorithms and finds that the newly proposed algorithms outperform the traditional ones in terms of AUC.

EXPERT SYSTEMS WITH APPLICATIONS (2022)

Article Engineering, Multidisciplinary

Dam deformation early warning model based on cluster analysis and spatiotemporal data fusion

Wei Lei et al.

Summary: This paper proposes a dam deformation early warning model based on spatiotemporal data fusion for hydraulic concrete structures. The model considers the correlation between different measuring points and explores the relationship between monitoring points using cluster analysis. By using the cross-sectional series fusion model and time series fusion model, the variation of overall horizontal displacements or the structural deflection curve for dams can be extracted, and the conformity of monitoring points with the operation regulation can be judged. Additionally, this method can be used to analyze the critical environmental factors affecting dam deformation.

MEASUREMENT (2022)

Article Construction & Building Technology

Risk assessment for musculoskeletal disorders based on the characteristics of work posture

Jingluan Wang et al.

Summary: This study introduces a novel WMSD prediction method based on the dynamic characteristics of working posture, utilizing three artificial intelligence algorithms. Using video data and a specific dataset for training, the method shows potential for real-time risk assessment.

AUTOMATION IN CONSTRUCTION (2021)

Article Environmental Sciences

SWOT risk analysis towards sustainable aquifer management along the Eastern Mediterranean

G. Rachid et al.

Summary: This study examined the risks of seawater intrusion in data scarce aquifers along the Eastern Mediterranean by conducting a SWOT analysis. It found alarming signs of SWI in some areas, with varying levels of adaptive capabilities across different countries. The study also showed a positive correlation between risks and the status of SWI, providing an effective decision-making tool for regions with data scarcity.

JOURNAL OF ENVIRONMENTAL MANAGEMENT (2021)

Review Environmental Sciences

Saltwater intrusion into groundwater systems in the Mekong Delta and links to global change

Xiao Han et al.

Summary: Climate warming in the Tibetan Plateau has led to changes in temperature, wind, and rainfall patterns in Southeast Asia, causing significant environmental impacts in the lower reach of the Mekong River basin. Saltwater intrusion has become a major issue in the densely populated Mekong Delta in southern Vietnam, posing threats to freshwater supply and ecosystem degradation. Addressing these challenges requires further research on hydrogeological information, groundwater monitoring, modeling, and identification of effective engineering techniques.

ADVANCES IN CLIMATE CHANGE RESEARCH (2021)

Article Engineering, Civil

An integrated framework of input determination for ensemble forecasts of monthly estuarine saltwater intrusion

Pengyu Lu et al.

Summary: This study proposes a tailor-made method for ensemble forecasts of monthly estuarine saltwater intrusion by using a combination of Pearson's Coefficient and Maximal Information Coefficient to determine the initial set of candidates and reducing the dimension of the input data sets through Principal Component Analysis. The results indicated that the proposed method achieved the highest forecast accuracy with a Nash-Sutcliffe coefficient of 0.78.

JOURNAL OF HYDROLOGY (2021)

Article Engineering, Civil

Coupling wavelet transform and artificial neural network for forecasting estuarine salinity

Fanhan Zhou et al.

JOURNAL OF HYDROLOGY (2020)

Article Engineering, Environmental

Forecasting salinity time series using RF and ELM approaches coupled with decomposition techniques

Jiayu Hu et al.

STOCHASTIC ENVIRONMENTAL RESEARCH AND RISK ASSESSMENT (2019)

Article Computer Science, Artificial Intelligence

Time-series clustering based on linear fuzzy information granules

Lingzi Duan et al.

APPLIED SOFT COMPUTING (2018)

Article Marine & Freshwater Biology

Three dimensional model evaluation of physical alterations of the Caloosahatchee River and Estuary: Impact on salt transport

Detong Sun et al.

ESTUARINE COASTAL AND SHELF SCIENCE (2016)

Review Computer Science, Information Systems

Time-series clustering - A decade review

Saeed Aghabozorgi et al.

INFORMATION SYSTEMS (2015)

Review Engineering, Civil

Artificial intelligence based models for stream-flow forecasting: 2000-2015

Zaher Mundher Yaseen et al.

JOURNAL OF HYDROLOGY (2015)

Article Water Resources

Seawater intrusion processes, investigation and management: Recent advances and future challenges

Adrian D. Werner et al.

ADVANCES IN WATER RESOURCES (2013)

Article Environmental Sciences

Numerical Simulation and Analysis of Saltwater Intrusion Lengths in the Pearl River Delta, China

Wei Zhang et al.

JOURNAL OF COASTAL RESEARCH (2013)

Article Environmental Sciences

Time series modeling and prediction of salinity in the Caloosahatchee River Estuary

Chelsea Qiu et al.

WATER RESOURCES RESEARCH (2013)

Article Geosciences, Multidisciplinary

Dynamics of saltwater intrusion in the Modaomen Waterway of the Pearl River Estuary

Wang Biao et al.

SCIENCE CHINA-EARTH SCIENCES (2012)

Article Geography, Physical

Long-term change in tidal dynamics and its cause in the Pearl River Delta, China

Wei Zhang et al.

GEOMORPHOLOGY (2010)

Article Plant Sciences

World salinization with emphasis on Australia

P Rengasamy

JOURNAL OF EXPERIMENTAL BOTANY (2006)