Search Results - water estimation ((method algorithm) OR (((path algorithm) OR (based algorithm))))
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Simulated Kalman Filter algorithms for solving optimization problems
Published 2019“…These algorithms are inspired by the estimation capability of the well-known Kalman filter estimation method. …”
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Development of real-time navigation system by using pure pursuit guidance for unmanned surface vehicle
Published 2024“…The Pure Pursuit algorithm works by focusing on the nearby path relative to the USV's position, guiding it with steering directions based on its current position and orientation. …”
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Model selection approaches of water quality index data
Published 2016“…In order to select the best model, it is vital to ensure that proper estimation method is chosen in the modelling process.Different estimators have been proposed for the estimation of parameters of a model, including the least square and iterative estimators.This study aims to evaluate the forecasting performances of two algorithms on water quality index (WQI) of a river in Malaysia based on root mean square error (RMSE) and geometric root mean square error (GRMSE).Feasible generalised least squares (FGLS) and iterative maximum likelihood (ML) estimation methods are used in the algorithms, respectively.The results showed that SUREMLE-Autometrics has surpassed SURE-Autometrics; another simultaneous selection procedure of multipleequation models.Two individual selections, namely Autometrics-SUREMLE and Autometrics-SURE, though showed consistency only for GRMSE.All in all, ML estimation is a more appropriate method to be employed in this seemingly unrelated regression equations (SURE) model selection.…”
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Multiple equations model selection algorithm with iterative estimation method
Published 2016“…This estimation method is equivalent to maximum likelihood estimation at convergence. …”
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Assessment of Satellite Derived Bathymetry from Spot 7 satellite imagery / Hanim Fazira Abd Hamid
Published 2020“…The objectives are (1) to estimate water depth from Spot 7 satellite image using Ratio Transformation Algorithm and (2) to assess estimated water depth with In-Situ data measurement. …”
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Improving the Muskingum flood routing method using a hybrid of particle swarm optimization and bat algorithm
Published 2023“…Decision making; Disaster prevention; Floods; Routing algorithms; Water resources; Absolute deviations; Bat algorithms; Comparative analysis; Computational time; Flood routing; Muskingum models; Particle swarm optimization algorithm; Swarm algorithms; Particle swarm optimization (PSO); accuracy assessment; algorithm; comparative study; decision making; flood; flood forecasting; flood routing; numerical method; optimization; parameter estimation; water resource; United Kingdom; United States…”
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Optimization of multipurpose reservoir operation using evolutionary algorithms / Mohammed Heydari
Published 2017“…An improved particle swarm algorithm (HPSOGA) is used to solve complex problems of water resources optimization. …”
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Optimization of operational policies for the Minab Reservoir, Southern Iran
Published 2012“…Through the hedging rule optimization an algorithm was developed to determine the benefit of water release and the water conserved in the reservoir. …”
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Sediment load forecasting from a biomimetic optimization perspective: Firefly and Artificial Bee Colony algorithms empowered neural network modeling in �oruh River
Published 2025“…The hybrid model is a novel approach for estimating sediment load based on various input variables. …”
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Extended multiple models selection algorithms based on iterative feasible generalized least squares (IFGLS) and expectation-maximization (EM) algorithm
Published 2019“…Therefore, in this study SUREAutometrics is improvised using two MLE methods, which are iterative feasible generalized least squares (IFGLS) and expectation-maximization (EM) algorithm, named as SURE(IFGLS)-Autometrics and SURE(EM)-Autometrics algorithms. …”
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Mixed Unscented Kalman Filter and differential evolution for parameter identification
Published 2013“…UKF have known to be a typical estimation technique used to estimate the state vectors and parameters of nonlinear dynamical systems and DE is one of the most powerful stochastic real-parameter optimization algorithms. …”
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Subsea Pipeline Corrosion Estimation by Restoring and Enhancing Degraded Underwater Images
Published 2018“…This paper presents a new method for subsea pipeline corrosion estimation by using colour information of corroded pipe. …”
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Subsea Pipeline Corrosion Estimation by Restoring and Enhancing Degraded Underwater Images
Published 2018“…This paper presents a new method for subsea pipeline corrosion estimation by using colour information of corroded pipe. …”
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Oil spill detection and characterization from satellite image using artificial neural network algorithm
Published 2014“…The objective of the algorithm is to classify every pixel of the image whether it is sea water or oil based on its intensity. …”
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Time series modeling of water level at Sulaiman Station, Klang River, Malaysia
Published 2010“…The estimation of parameters of the model is accomplished using the hybrid learning algorithm consisting of standard neural network backpropagation algorithm and least squares method. …”
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3D bathymetry reconstruction from airborne topsar polarized data
Published 2007“…The new method is based on integration between Fuzzy B-spline and Volterra algorithm. …”
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Modelling monthly pan evaporation utilising Random Forest and deep learning algorithms
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Applications of Data-driven Models for Daily Discharge Estimation Based on Different Input Combinations
Published 2023“…Decision trees; Errors; Flood control; Floods; Mean square error; Statistical tests; Agriculture management; Burhabalang river; Daily discharge; Data-driven model; Discharge estimation; Flood management; Training and testing; Water flood; Water industries; Water resources management; Rivers; algorithm; error analysis; estimation method; flood control; modeling; river discharge; river flow; India…”
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