☆ 4.5 Article

Forecasting of stage-discharge in a non-perennial river using machine learning with gamma test

HELIYON (2023)

Related references

Note: Only part of the references are listed.
Article

A novel hybrid AIG-SVR model for estimating daily reference evapotranspiration

Ehsan Mirzania et al.

Arabian Journal of Geosciences (2023)

Add to Collection
Article Computer Science, Artificial Intelligence

GLUE analysis of meteorological-based crop coefficient predictions to derive the explicit equation

Ahmed Elbeltagi et al.

Summary: The present study applied the GLUE approach to assess uncertainties in both model structure and input parameters, aiming to derive an explicit equation for calculating the monthly K-c of maize. Equations were developed from the best hybrid MLP model using minimal meteorological data in four regions of Egypt. The results showed that the hybrid MLP-RSO model outperformed other models in terms of stability and reliability, providing a fundamental guideline for deriving mathematical equations from easily available meteorological variables in different regions and climates.

NEURAL COMPUTING & APPLICATIONS (2023)

Add to Collection
Article Environmental Sciences

Performance of Machine Learning Techniques for Meteorological Drought Forecasting in the Wadi Mina Basin, Algeria

Mohammed Achite et al.

Summary: Drought negatively impacts water resources, land and soil degradation, desertification, agricultural productivity, and food security. The standardized precipitation index (SPI) is crucial for predicting meteorological droughts and managing water resources. Five machine learning models, including support vector machine (SVM), were used to model SPI at different timescales. The SVM model was found to be the most effective for predicting SPI, and satisfactory results were achieved when applying it to sub-basin 2. The suggested model outperformed other models in estimating drought and can be helpful for predicting drought on different timescales and managing water resources.

WATER (2023)

Add to Collection
Article Engineering, Civil

A Novel Hybrid Algorithms for Groundwater Level Prediction

Mohsen Saroughi et al.

Summary: Estimating groundwater levels (GWL) accurately and reliably is crucial for maximizing water resource utilization and reducing water consumption. This case study developed a simulation-optimization hybrid model using the honey badger algorithm (HBA) to optimize parameters of artificial neural networks (ANNs) and support vector regressions (SVRs) for predicting GWL in the Shabestar plain in Iran. The HBA-ANN and HBA-SVR models showed very good agreement with measured data, making them suitable for GWL forecasting based on the study's outcomes. Advanced AI techniques can accurately estimate groundwater systems, saving resources and conventional labor.

IRANIAN JOURNAL OF SCIENCE AND TECHNOLOGY-TRANSACTIONS OF CIVIL ENGINEERING (2023)

Add to Collection
Article Meteorology & Atmospheric Sciences

Enhancing monthly lake levels forecasting using heuristic regression techniques with periodicity data component: application of Lake Michigan

Vahdettin Demir

Summary: This study investigates the accuracy of three different techniques, MARS, LSSVR, and M5-tree, for estimating monthly lake levels with the periodicity component. The study uses data from Lake Michigan and finds that MARS generally outperforms LSSVR and M5-tree, and including the periodicity component improves the accuracy of the models.

THEORETICAL AND APPLIED CLIMATOLOGY (2022)

Add to Collection
Article Environmental Sciences

A Hybrid Model for Streamflow Forecasting in the Basin of Euphrates

Huseyin Cagan Kilinc et al.

Summary: River flow modeling is crucial for water resource management and sustainability. In recent years, scientists have used artificial neural networks and deep learning-based hybrid models for flow predictions. This study proposes a hybrid LSTM-GA model for streamflow forecasting and evaluates its performance using statistical metrics. The results show that the LSTM-GA model provides promising accuracy and outperforms the benchmark model and linear regression model.

WATER (2022)

Add to Collection
Article Agronomy

Methods to estimate evapotranspiration in humid and subtropical climate conditions

Dinesh Kumar Vishwakarma et al.

Summary: Selecting appropriate reference evapotranspiration (ETo) methods is crucial for managing water resources efficiently. This study evaluated thirty empirical ETo models and found that radiation-based models demonstrated higher accuracy in predicting ETo compared to temperature-based and mass transfer-based models. Among the tested models, the FAO56-PM method performed the best.

AGRICULTURAL WATER MANAGEMENT (2022)

Add to Collection
Article

Meta-learner methods in forecasting regulated and natural river flow

Sareh Sayari et al.

Arabian Journal of Geosciences (2022)

Add to Collection
Article

Forecasting of suspended sediment concentration in the Pindari-Kafni glacier valley in Central Himalayan region considering the impact of precipitation: using soft computing approach

Pankaj Chauhan et al.

Arabian Journal of Geosciences (2022)

Add to Collection
Article Environmental Sciences

Least square support vector machine-based variational mode decomposition: a new hybrid model for daily river water temperature modeling

Salim Heddam et al.

Summary: This study evaluates the contribution of variational mode decomposition (VMD) to the improvement of machine learning models for predicting river water temperature. The results show that applying VMD as a preprocessing technique significantly enhances the accuracy of the models.

ENVIRONMENTAL SCIENCE AND POLLUTION RESEARCH (2022)

Add to Collection
Article Engineering, Environmental

Modelling daily reference evapotranspiration based on stacking hybridization of ANN with meta-heuristic algorithms under diverse agro-climatic conditions

Ahmed Elbeltagi et al.

Summary: This study investigated the performance of five AI-based models for ET0 estimation and found that ANN-M5P and ANN-Bagging algorithms performed well in different models.

STOCHASTIC ENVIRONMENTAL RESEARCH AND RISK ASSESSMENT (2022)

Add to Collection
Article Green & Sustainable Science & Technology

Development of Novel Hybrid Models for Prediction of Drought- and Stress-Tolerance Indices in Teosinte Introgressed Maize Lines Using Artificial Intelligence Techniques

Amarjeet Kumar et al.

Summary: This study used various artificial intelligence algorithms to predict the drought tolerance and stress tolerance indices in maize and found that the genetic algorithm-based hybrid models performed better in predicting these indices.

SUSTAINABILITY (2022)

Add to Collection
Article Engineering, Multidisciplinary

Development of prediction model for phosphate in reservoir water system based machine learning algorithms

Sarmad Dashti Latif et al.

Summary: This study proposes the use of machine learning algorithms to predict the concentration of phosphate (PO4) in water bodies. The results show that the artificial neural network (ANN) model outperforms other models in terms of accuracy. This model can be used as a reliable tool for managing eutrophication problems.

AIN SHAMS ENGINEERING JOURNAL (2022)

Add to Collection
Article Water Resources

Data intelligence and hybrid metaheuristic algorithms-based estimation of reference evapotranspiration

Ahmed Elbeltagi et al.

Summary: This study addresses the challenge of limited climatic data in developing countries and applies five machine learning algorithms to predict daily reference evapotranspiration. It identifies the most influential climatic parameters and finds that the AR-M5P model performs better in predicting ET0 values compared to other algorithms.

APPLIED WATER SCIENCE (2022)

Add to Collection
Article Water Resources

Modeling stage-discharge-sediment using support vector machine and artificial neural network coupled with wavelet transform

Manish Kumar et al.

Summary: The assessment of sediment load carried by rivers is crucial in the planning and design of water resource projects. This study used five different data-driven techniques to model the daily suspended sediment concentration (SSC). The results showed that the wavelet-based support vector machine (WSVM) model was the most reliable and accurate model for predicting SSC.

APPLIED WATER SCIENCE (2022)

Add to Collection
Article Meteorology & Atmospheric Sciences

Evaluation of Data-driven Hybrid Machine Learning Algorithms for Modelling Daily Reference Evapotranspiration

Nand Lal Kushwaha et al.

Summary: This study compares different models and algorithms for estimating reference evapotranspiration (ET0). The model performances were found to be superior with the inclusion of more meteorological input variables. The A(d)R6 model, which included all selected variables, outperformed other models during testing. The A(d)R algorithm alone captured about 86% of the observed data's variance, while hybrid combinations with A(d)R as a constituent showed better prediction accuracies but still inferior to A(d)R as an individual performer.

ATMOSPHERE-OCEAN (2022)

Add to Collection
Article Environmental Sciences

Pre- and post-dam river water temperature alteration prediction using advanced machine learning models

Dinesh Kumar Vishwakarma et al.

Summary: Dams have a significant impact on river hydrology, particularly on water temperature. This study used machine learning models to predict the daily water temperature of the Yangtze River in Chongqing and compared the performance of different models. The results showed that the M5P model performed the best. These findings are valuable for planning new reservoirs and managing water flow and temperature.

ENVIRONMENTAL SCIENCE AND POLLUTION RESEARCH (2022)

Add to Collection
Article Environmental Sciences

Potential for seasonal flood forecasting in West Africa using climate indexes

Jean Hounkpe et al.

Summary: This study investigates the potential of using climate indicators for predicting flood discharge in West Africa. Forecasting models based on simple and multiple linear regressions between climate indexes and annual maximum discharge show promising results. The western dipole mode index is found to be the most skillful individual climate index, while combining multiple climate indexes outperforms individual indexes. The study opens up possibilities for seasonal flood forecasting in West Africa.

JOURNAL OF FLOOD RISK MANAGEMENT (2022)

Add to Collection
Article Water Resources

Climate change impacts on the flow regime and water quality indicators using an artificial neural network (ANN): a case study in Saskatchewan, Canada

Amin Hassanjabbar et al.

Summary: In this study, the impacts of climate change on the water quantity and quality of the Qu'Appelle River in Saskatchewan, Canada were investigated using the artificial neural network (ANN) method. The study found that climate change would lead to a heterogeneous change in precipitation and temperature patterns, causing serious degradation in the river discharge as well as dissolved oxygen (DO) and total dissolved solids (TDS) concentration levels, resulting in deterioration in the sustainability of the river system and ecological health of the region.

JOURNAL OF WATER AND CLIMATE CHANGE (2022)

Add to Collection
Article Green & Sustainable Science & Technology

An Integrated Statistical-Machine Learning Approach for Runoff Prediction

Abhinav Kumar Singh et al.

Summary: This study uses data-driven models for rainfall-runoff prediction in the Gola watershed and evaluates the performance of four heuristic methods. The results show that the RF model outperforms the other models and has higher accuracy.

SUSTAINABILITY (2022)

Add to Collection
Article Geography, Physical

Ensemble machine learning models based on Reduced Error Pruning Tree for prediction of rainfall-induced landslides

Binh Thai Pham et al.

Summary: This study developed highly accurate ensemble machine learning models for spatial prediction of rainfall-induced landslides in the Uttarkashi district, India. The D-REPT model was identified as the most accurate, providing insights for engineers and modelers to develop more advanced predictive models.

INTERNATIONAL JOURNAL OF DIGITAL EARTH (2021)

Add to Collection
Article Environmental Sciences

Application of stacking hybrid machine learning algorithms in delineating multi-type flooding in Bangladesh

Mahfuzur Rahman et al.

Summary: The study assessed multi-type flood probabilities at a national scale in Bangladesh using various machine learning algorithms and found that the LWLR-RF algorithm performed the best in predicting flood probabilities. The constructed probability maps can guide future flood risk management and sustainable land-use planning.

JOURNAL OF ENVIRONMENTAL MANAGEMENT (2021)

Add to Collection
Review Engineering, Environmental

Recent advances in artificial intelligence and machine learning for nonlinear relationship analysis and process control in drinking water treatment: A review

Lei Li et al.

Summary: Artificial intelligence (AI) plays a crucial role in drinking water treatment, providing technical support, optimizing operational processes, and solving complex problems. The review examines the application of AI technologies in water treatment and discusses future challenges and research directions.

CHEMICAL ENGINEERING JOURNAL (2021)

Add to Collection
Article Meteorology & Atmospheric Sciences

Evaporation estimation from climatic factors

PANKAJ KUMAR et al.

Mausam (2021)

Add to Collection
Article Environmental Sciences

Assessment of transportation system disruption and accessibility to critical amenities during flooding: Iowa case study

Yazeed Alabbad et al.

Summary: This study investigates the impact of flooding on road networks and accessibility to critical amenities in major communities in Iowa. Flooding can disrupt road systems, leading to edge and node losses as well as difficulty in reaching critical services. Vulnerability to flooding varies among cities, with some experiencing significant impacts and risks to key facilities.

SCIENCE OF THE TOTAL ENVIRONMENT (2021)

Add to Collection
Article Environmental Sciences

Flood Mitigation in the Transboundary Chenab River Basin: A Basin-Wise Approach from Flood Forecasting to Management

Sikandar Ali et al.

Summary: The study utilized HEC-HMS and HEC-RAS models for flood forecasting and inundation modeling in the Chenab River basin, showcasing their effectiveness in improving accuracy and achieving an overall accuracy of over 90%.

REMOTE SENSING (2021)

Add to Collection
Article Computer Science, Artificial Intelligence

Daily streamflow forecasting in Sobradinho Reservoir using machine learning models coupled with wavelet transform and bootstrapping

Samuel Vitor Saraiva et al.

Summary: This study conducted a comparative analysis of a set of machine learning models, including an ANN and an SVM coupled with wavelet transform and data resampling. Results showed that the ANN outperformed the SVM in terms of accuracy, with the best performing combination being the BWNN method. The BWNN method yielded lower mean square error and higher R-2 and MAE coefficients for streamflow forecasting 3 to 15 days ahead.

APPLIED SOFT COMPUTING (2021)

Add to Collection
Article Environmental Sciences

Data Intelligence Model and Meta-Heuristic Algorithms-Based Pan Evaporation Modelling in Two Different Agro-Climatic Zones: A Case Study from Northern India

Nand Lal Kushwaha et al.

Summary: Precise quantification of evaporation is crucial for crop modeling, irrigation scheduling, and agricultural water management. Data-driven models using meta-heuristics algorithms have gained attention from researchers worldwide. This study examined the performance of models employing four meta-heuristic algorithms in simulating daily pan evaporation in different climatic regions in India and found that the SVM algorithm performed the best compared to other algorithms.

ATMOSPHERE (2021)

Add to Collection
Review Radiology, Nuclear Medicine & Medical Imaging

Artificial intelligence and machine learning for medical imaging: A technology review

Ana Barragan-Montero et al.

Summary: Artificial intelligence has become a popular buzzword in recent years, particularly in the field of medical imaging analysis, where it is now a mainstream tool for tasks such as diagnosis, segmentation, and classification. Ensuring the safe and efficient use of clinical AI applications relies on informed practitioners who understand the basic technological pillars of AI and the state-of-the-art machine learning methods.

PHYSICA MEDICA-EUROPEAN JOURNAL OF MEDICAL PHYSICS (2021)

Add to Collection
Article Green & Sustainable Science & Technology

Ecological impacts of run -of -river hydropower plants ? Current status and future prospects on the brink of energy transition

Alban Kuriqi et al.

Summary: The widespread perception of small run-of-river hydropower plants as renewable energy sources has led to their global proliferation, but such schemes may have negative impacts on fluvial ecosystems. Different types of small run-of-river hydropower schemes have varying ecological impacts, with diversion weir and pondage schemes being less eco-friendly compared to dam-toe schemes. Environmental flows are crucial for ecosystem conservation in rivers affected by hydropower operations.

RENEWABLE & SUSTAINABLE ENERGY REVIEWS (2021)

Add to Collection
Article Engineering, Environmental

A comparative study of wavelet and empirical mode decomposition-based GPR models for river discharge relationship modeling at consecutive hydrometric stations

Kiyoumars Roushangar et al.

Summary: The study evaluated the application of Gaussian Process Regressions in predicting the daily river stage-discharge relationship, and used Wavelet Transform and Ensemble Empirical Mode Decomposition techniques to enhance model efficiency. The integrated WT and EEMD-GPR models produced more accurate results, with data processing improving model capability by 25% to 40%.

WATER SUPPLY (2021)

Add to Collection
Article Engineering, Environmental

Predictive modelling of the stage-discharge relationship using Gene-Expression Programming

Prashant Birbal et al.

Summary: Researcher utilized Gene-Expression Programming (GEP) modeling technique to accurately model the stage-discharge relationship of the Arouca River, showing exceptional performance in the evaluation metrics.

WATER SUPPLY (2021)

Add to Collection
Review Environmental Sciences

Urban flood risks and emerging challenges in a Chinese delta: The case of the Pearl River Delta

Faith Ka Shun Chan et al.

Summary: By the 2050s, over 120 million people are expected to settle in the Pearl River Delta, with rapid urbanization leading to increased flood risks in coastal cities. There is a need for long-term flood risk management practices and better regional strategies to address the challenges posed by urban floods and climate change.

ENVIRONMENTAL SCIENCE & POLICY (2021)

Add to Collection
Article Engineering, Civil

Real-time reservoir flood control operation enhanced by data assimilation

Jingwen Zhang et al.

Summary: Real-time Optimization Model Enhanced by Data Assimilation (ROMEDA) is proposed as a human-machine interactive method for optimizing reservoir operations. Through a case study, it is found that ROMEDA shows better performance on flood risk mitigation and water use benefit, making it a promising approach for real-time reservoir operation integrating human expertise and computational modeling.

JOURNAL OF HYDROLOGY (2021)

Add to Collection
Article Environmental Sciences

Machine learning for hydrologic sciences: An introductory overview

Tianfang Xu et al.

Summary: In recent years, the hydrologic community has shown a growing interest in machine learning, driven by the expansion of hydrologic data repositories and the success of machine learning in academic and commercial applications. This overview introduces commonly used machine learning algorithms and deep learning architectures in a non-technical manner, with a focus on applications in hydrologic sciences. The challenges of extrapolating robustness, physical interpretability, and small sample size in hydrologic applications are also highlighted.

WILEY INTERDISCIPLINARY REVIEWS-WATER (2021)

Add to Collection
Article Geosciences, Multidisciplinary

Hydrologically informed machine learning for rainfall-runoff modelling: towards distributed modelling

Herath Mudiyanselage Viraj Vidura Herath et al.

Summary: Machine learning and data science models, while successful in many commercial fields, have limited success in certain scientific fields due to lack of interpretability and physical consistency, leading to the emergence of new modelling paradigms focused on blending existing scientific knowledge with learning algorithms.

HYDROLOGY AND EARTH SYSTEM SCIENCES (2021)

Add to Collection
Article Environmental Sciences

Evaluation of tree regression analysis for estimation of river basin discharge

Parveen Sihag et al.

Summary: This study compared and evaluated different modeling methods for daily discharge of the Baitarani River, and proposed the Bagged M5P model as the most effective. The Bagged M5P model outperformed ARIMA, RF, and M5P, recording high correlation coefficient, low mean absolute error, and root mean square error on the testing dataset.

MODELING EARTH SYSTEMS AND ENVIRONMENT (2021)

Add to Collection
Article Computer Science, Interdisciplinary Applications

Combining machine learning and process engineering physics towards enhanced accuracy and explainability of data-driven models

Timur Bikmukhametov et al.

COMPUTERS & CHEMICAL ENGINEERING (2020)

Add to Collection
Article Computer Science, Information Systems

Daily Water Level Prediction of Zrebar Lake (Iran): A Comparison between M5P, Random Forest, Random Tree and Reduced Error Pruning Trees Algorithms

Viet-Ha Nhu et al.

ISPRS INTERNATIONAL JOURNAL OF GEO-INFORMATION (2020)

Add to Collection
Article Engineering, Civil

Long-term rainfall prediction using atmospheric synoptic patterns in semiarid climates with statistical and machine learning methods

Javier Diez-Sierra et al.

JOURNAL OF HYDROLOGY (2020)

Add to Collection
Article Environmental Sciences

Monthly evapotranspiration estimation using optimal climatic parameters: efficacy of hybrid support vector regression integrated with whale optimization algorithm

Yazid Tikhamarine et al.

ENVIRONMENTAL MONITORING AND ASSESSMENT (2020)

Add to Collection
Article Environmental Sciences

Assessment of Ecological and Hydro-Geomorphological Alterations under Climate Change Using SWAT and IAHRIS in the Eo River in Northern Spain

Julio Perez-Sanchez et al.

WATER (2020)

Add to Collection
Article Green & Sustainable Science & Technology

Estimation of Daily Stage-Discharge Relationship by Using Data-Driven Techniques of a Perennial River, India

Manish Kumar et al.

SUSTAINABILITY (2020)

Add to Collection
Article Computer Science, Theory & Methods

Crypto-ransomware early detection model using novel incremental bagging with enhanced semi-random subspace selection

Bander Ali Saleh Al-rimy et al.

FUTURE GENERATION COMPUTER SYSTEMS-THE INTERNATIONAL JOURNAL OF ESCIENCE (2019)

Add to Collection
Article Water Resources

Investigation of discharge coefficient of trapezoidal labyrinth weirs using artificial neural networks and support vector machines

Reza Norouzi et al.

APPLIED WATER SCIENCE (2019)

Add to Collection
Article Energy & Fuels

Optimal Deep Learning LSTM Model for Electric Load Forecasting using Feature Selection and Genetic Algorithm: Comparison with Machine Learning Approaches

Salah Bouktif et al.

ENERGIES (2018)

Add to Collection
Article Environmental Sciences

Mapping forest change using stacked generalization: An ensemble approach

Sean P. Healey et al.

REMOTE SENSING OF ENVIRONMENT (2018)

Add to Collection
Article Environmental Sciences

Impacts of climate and land use changes on flood risk management for the Schijn River, Belgium

Tahmina Akter et al.

ENVIRONMENTAL SCIENCE & POLICY (2018)

Add to Collection
Article Engineering, Civil

Quantifying hourly suspended sediment load using data mining models: Case study of a glacierized Andean catchment in Chile

Khabat Khosravi et al.

JOURNAL OF HYDROLOGY (2018)

Add to Collection
Proceedings Paper Engineering, Civil

A Spreadsheet Approach for Prediction of Rating Curve Parameters

Mohammad Muzzammil et al.

HYDROLOGIC MODELING (2018)

Add to Collection
Article Environmental Sciences

The 'dirty dozen' of freshwater science: detecting then reconciling hydrological data biases and errors

Robert L. Wilby et al.

WILEY INTERDISCIPLINARY REVIEWS-WATER (2017)

Add to Collection
Article Engineering, Civil

Predication of discharge coefficient of cylindrical weir-gate using adaptive neuro fuzzy inference systems (ANFIS)

Abbas Parsaie et al.

FRONTIERS OF STRUCTURAL AND CIVIL ENGINEERING (2017)

Add to Collection
Article Water Resources

Calibration of mass transfer-based models to predict reference crop evapotranspiration

Mohammad Valipour

APPLIED WATER SCIENCE (2017)

Add to Collection
Article Environmental Sciences

Assessing total water storage and identifying flood events over Tonle Sap basin in Cambodia using GRACE and MODIS satellite observations combined with hydrological models

N. Tangdamrongsub et al.

REMOTE SENSING OF ENVIRONMENT (2016)

Add to Collection
Article Engineering, Civil

Enhancing Long-Term Streamflow Forecasting and Predicting using Periodicity Data Component: Application of Artificial Intelligence

Zaher Mundher Yaseen et al.

WATER RESOURCES MANAGEMENT (2016)

Add to Collection
Article Environmental Sciences

Stage-discharge rating curves based on satellite altimetry and modeled discharge in the Amazon basin

Adrien Paris et al.

WATER RESOURCES RESEARCH (2016)

Add to Collection
Article Water Resources

Modeling of stage-discharge relationship for Gharraf River, southern Iraq using backpropagation artificial neural networks, M5 decision trees, and Takagi-Sugeno inference system technique: a comparative study

Alaa M. Al-Abadi

APPLIED WATER SCIENCE (2016)

Add to Collection
Article Water Resources

Optimal parameters for the Green-Ampt infiltration model under rainfall conditions

Li Chen et al.

JOURNAL OF HYDROLOGY AND HYDROMECHANICS (2015)

Add to Collection
Article Construction & Building Technology

An artificial neural network model for predicting compression strength of heat treated woods and comparison with a multiple linear regression model

Sebahattin Tiryaki et al.

CONSTRUCTION AND BUILDING MATERIALS (2014)

Add to Collection
Article Water Resources

Review of methods used to estimate catchment response time for the purpose of peak discharge estimation

Ockert J. Gericke et al.

HYDROLOGICAL SCIENCES JOURNAL-JOURNAL DES SCIENCES HYDROLOGIQUES (2014)

Add to Collection
Article Engineering, Civil

Determination of Optimal Unit Hydrographs and Green-Ampt Parameters for Watersheds

Daniel Che et al.

JOURNAL OF HYDROLOGIC ENGINEERING (2014)

Add to Collection
Article Engineering, Geological

Comparison Between Neural Networks and Multiple Regression Analysis to Predict Rock Fragmentation in Open-Pit Mines

Iman Enayatollahi et al.

ROCK MECHANICS AND ROCK ENGINEERING (2014)

Add to Collection
Article Engineering, Civil

Wavelet Bootstrap Multiple Linear Regression Based Hybrid Modeling for Daily River Discharge Forecasting

Vinit Sehgal et al.

WATER RESOURCES MANAGEMENT (2014)

Add to Collection
Article Engineering, Civil

Application of excel solver for parameter estimation of the nonlinear Muskingum models

Reza Barati

KSCE JOURNAL OF CIVIL ENGINEERING (2013)

Add to Collection
Article Computer Science, Artificial Intelligence

Comparison of multi-objective evolutionary neural network, adaptive neuro-fuzzy inference system and bootstrap-based neural network for flood forecasting

Amal Kant et al.

NEURAL COMPUTING & APPLICATIONS (2013)

Add to Collection
Article Water Resources

Hierarchical neurofuzzy model for real-time flood forecasting

Sagarika Rath et al.

INTERNATIONAL JOURNAL OF RIVER BASIN MANAGEMENT (2013)

Add to Collection
Article Computer Science, Artificial Intelligence

Development of stage-discharge rating curve using model tree and neural networks: An application to Peachtree Creek in Atlanta

Tapesh K. Ajmera et al.

EXPERT SYSTEMS WITH APPLICATIONS (2012)

Add to Collection
Article Engineering, Civil

Modeling of Suspended Sediment Concentration at Kasol in India Using ANN, Fuzzy Logic, and Decision Tree Algorithms

A. R. Senthil Kumar et al.

JOURNAL OF HYDROLOGIC ENGINEERING (2012)

Add to Collection
Article Computer Science, Artificial Intelligence

Naive random subspace ensemble with linear classifiers for real-time classification of fMRI data

Catrin O. Plumpton et al.

PATTERN RECOGNITION (2012)

Add to Collection
Article Engineering, Civil

Stage and Discharge Forecasting by SVM and ANN Techniques

S. K. Aggarwal et al.

WATER RESOURCES MANAGEMENT (2012)

Add to Collection
Article Water Resources

Stage-discharge uncertainty derived with a non-stationary rating curve in the Choluteca River, Honduras

I. Westerberg et al.

HYDROLOGICAL PROCESSES (2011)

Add to Collection
Article Engineering, Civil

A wavelet-support vector machine conjunction model for monthly streamflow forecasting

Ozgur Kisi et al.

JOURNAL OF HYDROLOGY (2011)

Add to Collection
Article Computer Science, Artificial Intelligence

The practical research on flood forecasting based on artificial neural networks

Li-Hua Feng et al.

EXPERT SYSTEMS WITH APPLICATIONS (2010)

Add to Collection
Article Engineering, Multidisciplinary

Risk-based optimization of large flood-diversion systems using genetic algorithms

Abbas Afshar et al.

ENGINEERING OPTIMIZATION (2009)

Add to Collection
Article Engineering, Civil

Daily Pan Evaporation Modeling in a Hot and Dry Climate

J. Piri et al.

JOURNAL OF HYDROLOGIC ENGINEERING (2009)

Add to Collection
Article Engineering, Civil

New Approach for Stage-Discharge Relationship: Gene-Expression Programming

Aytac Guven et al.

JOURNAL OF HYDROLOGIC ENGINEERING (2009)

Add to Collection
Article Engineering, Civil

Decomposition of the mean squared error and NSE performance criteria: Implications for improving hydrological modelling

Hoshin V. Gupta et al.

JOURNAL OF HYDROLOGY (2009)

Add to Collection
Article Engineering, Civil

Theoretical development of stage-discharge ratings for subcritical open-channel flows

A. R. Schmidt et al.

JOURNAL OF HYDRAULIC ENGINEERING (2008)

Add to Collection
Article Engineering, Civil

Field-derived relationships for flow velocity and resistance in high-gradient streams

Francesco Comiti et al.

JOURNAL OF HYDROLOGY (2007)

Add to Collection
Article Engineering, Civil

Multi-time scale stream flow predictions: The support vector machines approach

T Asefa et al.

JOURNAL OF HYDROLOGY (2006)

Add to Collection
Article Engineering, Civil

Flow forecasting for a Hawaii stream using rating curves and neural networks

GB Sahoo et al.

JOURNAL OF HYDROLOGY (2006)

Add to Collection
Review Biodiversity Conservation

The concepts of bias, precision and accuracy, and their use in testing the performance of species richness estimators, with a literature review of estimator performance

BA Walther et al.

ECOGRAPHY (2005)

Add to Collection
Article Engineering, Civil

Discharge rating curve extension - A new approach

C Sivapragasam et al.

WATER RESOURCES MANAGEMENT (2005)

Add to Collection
Article Water Resources

A fast method of flood discharge estimation

YC Chen et al.

HYDROLOGICAL PROCESSES (2004)

Add to Collection
Article Engineering, Civil

M5 model trees and neural networks: Application to flood forecasting in the upper reach of the Huai River in China

DP Solomatine et al.

JOURNAL OF HYDROLOGIC ENGINEERING (2004)

Add to Collection
Article Computer Science, Interdisciplinary Applications

Identification of support vector machines for runoff modelling

M Bray et al.

JOURNAL OF HYDROINFORMATICS (2004)

Add to Collection
Article Engineering, Civil

River flow forecasting: use of phase-space reconstruction and artificial neural networks approaches

B Sivakumar et al.

JOURNAL OF HYDROLOGY (2002)

Add to Collection
Article Computer Science, Theory & Methods

Hybrid fuzzy least-squares regression analysis and its reliability measures

YHO Chang

FUZZY SETS AND SYSTEMS (2001)

Add to Collection
Article Meteorology & Atmospheric Sciences

Summarizing multiple aspects of model performance in a single diagram.

KE Taylor

JOURNAL OF GEOPHYSICAL RESEARCH-ATMOSPHERES (2001)

Add to Collection
Webinars Posters Questions Hubs Funding Journals Papers Connect Collections Reviewers About Us FAQs Mobile App Privacy Policy Terms of Use
© Peeref 2019-2024. All rights reserved.