Machine learning for hydrologic sciences: An introductory overview
The hydrologic community has experienced a surge in interest in machine learning in recent
years. This interest is primarily driven by rapidly growing hydrologic data repositories, as …
years. This interest is primarily driven by rapidly growing hydrologic data repositories, as …
Linear and non-linear SVM prediction for fresh properties and compressive strength of high volume fly ash self-compacting concrete
Support vector machines (SVMs) have recently been used to model the properties of low
volume fly ash self-compacting concrete (LVF-SCC) by means of kernel functions to …
volume fly ash self-compacting concrete (LVF-SCC) by means of kernel functions to …
Applications of various data-driven models for the prediction of groundwater quality index in the Akot basin, Maharashtra, India
Data-driven models are important to predict groundwater quality which is controlling human
health. The water quality index (WQI) has been developed based on the physicochemical …
health. The water quality index (WQI) has been developed based on the physicochemical …
[BOOK][B] Machine learning for spatial environmental data: theory, applications, and software
M Kanevski, V Timonin, A Pozdnukhov - 2009 - taylorfrancis.com
This book discusses machine learning algorithms, such as artificial neural networks of
different architectures, statistical learning theory, and Support Vector Machines used for the …
different architectures, statistical learning theory, and Support Vector Machines used for the …
Generalization performance of support vector machines and neural networks in runoff modeling
Effective one-day lead runoff prediction is one of the significant aspects of successful water
resources management in arid region. For instance, reservoir and hydropower systems call …
resources management in arid region. For instance, reservoir and hydropower systems call …
Prediction of weighted arithmetic water quality index for urban water quality using ensemble machine learning model
Urban water quality index (WQI) is an important factor for assessment quality of groundwater
in the urban and rural area. In this research, the Weighted Arithmetic Water Quality Index …
in the urban and rural area. In this research, the Weighted Arithmetic Water Quality Index …
A comparative study of groundwater level forecasting using data-driven models based on ensemble empirical mode decomposition
Y Gong, Z Wang, G Xu, Z Zhang - Water, 2018 - mdpi.com
The reliable and accurate prediction of groundwater levels is important to improve water-use
efficiency in the development and management of water resources. Three nonlinear time …
efficiency in the development and management of water resources. Three nonlinear time …
Comparative study of SVMs and ANNs in aquifer water level prediction
M Behzad, K Asghari, EA Coppola Jr - Journal of Computing in Civil …, 2010 - ascelibrary.org
In this research, a data-driven modeling approach, support vector machines (SVMs), is
compared to artificial neural networks (ANNs) for predicting transient groundwater levels in a …
compared to artificial neural networks (ANNs) for predicting transient groundwater levels in a …
Many‐objective groundwater monitoring network design using bias‐aware ensemble Kalman filtering, evolutionary optimization, and visual analytics
This study contributes the Adaptive Strategies for Sampling in Space and Time (ASSIST)
framework for improving long‐term groundwater monitoring decisions across space and …
framework for improving long‐term groundwater monitoring decisions across space and …
Estimation of daily stage–discharge relationship by using data-driven techniques of a perennial river, India
Modeling the stage-discharge relationship in river flow is crucial in controlling floods,
planning sustainable development, managing water resources and economic development …
planning sustainable development, managing water resources and economic development …