Search Results - (( variable estimation techniques algorithm ) OR ( parameter optimization _ algorithm ))
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1
A hybrid genetic algorithm and linear regression for prediction of NOx emission in power generation plant
Published 2023Subjects:Conference paper -
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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“…This study combined models such as the artificial neural network (ANN) algorithm with the Firefly algorithm (FA) and Artificial Bee Colony (ABC) optimization techniques for the estimation of monthly SL values in the �oruh River in Northeastern Turkey. …”
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A decomposed streamflow non-gradientbased artificial intelligence forecasting algorithm with factoring in aleatoric and epistemic variables / Wei Yaxing
Published 2024“…Firefly algorithm outperformed the other metaheuristic algorithms used to solve this proposed hybrid artificial intelligence model regarding parameter sensitivity. …”
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Thesis -
4
Power System State Estimation In Large-Scale Networks
Published 2010“…The developed program is suitable either to estimate the UPFC controller parameters or to estimate these parameter values in order to achieve the given control specifications in addition to the power system state variables.…”
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5
Use of AR Block Processing for Estimating the State Variables of Power System
Published 2008“…Samples of the local utility network for 103-bus parameter are collected and simulated using Burg and Modified Covariance algorithm to estimate the state variables. Simulation results to support the proposed method are also presented and compared with WLS method.…”
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Analysis and Optimization of Ultrasound-Assisted Alkaline Palm Oil Transesterification by RSM and ANN-GA
Published 2017“…Besides, the numerical optimization technique was employed to optimize process variables in order to obtain the maximum FAME content (reaction yield) along with the best properties using both RSM and ANN-GA techniques. …”
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Towards enhanced remaining useful life prediction of lithium-ion batteries with uncertainty using optimized deep learning algorithm
Published 2025Subjects:Article -
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Hybrid modelling and kinetic estimation for polystyrene batch reactor using Artificial Neutral Network (ANN) approach
Published 2011“…In this work, the kinetic parameters were estimated for a styrene-free radical polymerization conducted in an experimental batch reactor system using a nonlinear least squares optimization algorithm. …”
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Hydroclimatic data prediction using a new ensemble group method of data handling coupled with artificial bee colony algorithm
Published 2022“…Therefore, in this paper, we enhance the GMDH model by implementing the ABC algorithm to optimize the parameter of partial description GMDH model with some transfer functions, namely polynomial, radial basis, sigmoid and hyperbolic tangent function. …”
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10
Rank regression for modeling bus dwell time in the presence of censored observations
Published 2019“…An iterative algorithm is introduced that involves a monotone estimating function of the model parameter, and its minimization is a computationally simple optimization problem. …”
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11
Determination of tree stem volume : A case study of Cinnamomum
Published 2013“…Illustrations and algorithms are incorporated into the procedures. Non-normal and nonlinear data variables are addressed, hence data characterization is presented. …”
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Conceptual Design And Dynamical Analysis Of Aerostat System
Published 2020“…The baseline configuration for the desired mission has been obtained using a design algorithm. The statistical values of the selected design variables that include hull fineness ratio, fin area and fin position of the existing aerostat are used to obtain the baseline configuration. …”
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14
Groundwater quality assessment and optimization of monitored wells using multivariate geostatistical techniques in Amol-Babol Plain, Iran
Published 2015“…A new optimization approach was proposed for redesign monitoring network wells using optimization algorithm based on the vulnerability of aquifer to contaminations, estimation error of sampling wells, nearest distance between wells, and source of contamination in the study area. …”
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15
Performance Modeling And Size Optimization Of A Standalone Photovoltaic System
Published 2013“…Furthermore, SAPV components sizing method was formulated with a nonlinear unconstrained optimization technique by using first derivative method. …”
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16
Modeling of cupping suction system based on system identification method
Published 2022“…By minimizing integral square errors, fractional order model parameters were optimized (ISE). The results reveal that the better the precision of the modelling cupping system parameter, the lower the error. …”
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Undergraduates Project Papers -
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Analysis of daytime and nighttime ground level ozone concentrations using boosted regression tree technique
Published 2017“…A BRT model was developed using hourly ozone data as a response variable and nitric oxide (NO), Nitrogen Dioxide (NO2) and Nitrogen Dioxide (NOx) and meteorological parameters as explanatory variables. The ozone BRT algorithm model was constructed from multiple regression models, and the ‘best iteration’ of BRT model was performed by optimizing prediction performance. …”
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Variable block based motion estimation using hexagon diamond full search algorithm (HDFSA) via block subtraction technique
Published 2015“…Motion estimation is a technique to reduce high information redundancy which exists between successive frames in a video sequences. …”
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Power prediction using the wind turbine power curve and data-driven approaches / Ehsan Taslimi Renani
Published 2018“…To obtain the unknown vector of parameters of the MHTan, three heuristic optimization algorithms are employed to minimize the sum of squared residuals. …”
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20
Multi-objective optimization of process variables for MWCNT-added electro-discharge machining of 316L steel
Published 2021“…The best 21 solution sets predicted through the multi-objective optimization tool called non-dominated sorting genetic algorithm-II (NSGA-II) obeying the set objective functions are proposed which are obtained from the Pareto optimal frontiers. …”
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