Search Results - (( model evaluation metric algorithm ) OR ( parameters estimation based algorithm ))
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1
Using the evolutionary mating algorithm for optimizing deep learning parameters for battery state of charge estimation of electric vehicle
Published 2023“…According to the simulation results, the proposed EMA-DL algorithm was found to outperform all the other compared algorithms based on the evaluated metrics. …”
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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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The impact of executive function and aerobic exercise recognition in obese children under deep learning
Published 2025“…Initially, a motion recognition model based on STN and Lucas–Kanade optical flow algorithm optimization was constructed. …”
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4
Restoration of blurred images using geometric and chebichef moments / Ahlad Kumar
Published 2016“…In the third method, Tchebichef moments (TM) of low order are selected as features used as inputs to ELM to estimate the Gaussian blur parameters. Once the blur parameters are estimated, image restoration of the proposed method is carried out using split Bregman algorithm. …”
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5
Modelling monthly pan evaporation utilising Random Forest and deep learning algorithms
Published 2023Article -
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Battery remaining useful life estimation based on particle swarm optimization-neural network
Published 2024“…In conducting an analysis, the performance of the PSO NN model is compared with hybrid NN with Cultural Algorithm (CA-NN) and Harmony Search Algorithm (HSA-NN), as well as the standalone Autoregressive Integrated Moving Average (ARIMA). …”
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Model-based hybrid variational level set method applied to object detection in grey scale images
Published 2024“…To tackle the persistent challenge of segmenting grayscale images with both uneven characteristics and high noise levels, a hybrid level-set algorithm based on kernel metrics is introduced. This algorithm leverages an improved multi-scale mean filter to mitigate grayscale inhomogeneity while reducing the impact of scale parameter selection. …”
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8
Application of Machine Learning and Deep Learning Algorithms for Landslide Susceptibility Assessment in Landslide Prone Himalayan Region
Published 2025“…We carefully selected relevant metrics based on existing research and conducted a multicollinearity analysis on each parameter to ensure the model?…”
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Enhancing riverine load prediction of anthropogenic pollutants: Harnessing the potential of feed-forward backpropagation (FFBP) artificial neural network (ANN) models
Published 2025“…This study compares numerous mathematical modelling strategies for estimating riverine loads based on the chosen water quality parameters: Biochemical Oxygen Demand (BOD), Chemical Oxygen Demand (COD), Suspended Solids (SS), and Ammoniacal Nitrogen (NH3?…”
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Enhancing riverine load prediction of anthropogenic pollutants: harnessing the potential of feed-forward backpropagation (FFBP) artificial neural network (ANN) models
Published 2024“…This study compares numerous mathematical modelling strategies for estimating riverine loads based on the chosen water quality parameters: Biochemical Oxygen Demand (BOD), Chemical Oxygen Demand (COD), Suspended Solids (SS), and Ammoniacal Nitrogen (NH3–N). …”
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Software metrics selection model for predicting maintainability of object-oriented software using genetic algorithms
Published 2016“…The latest effort to solve this selection problem is the development of the metrics selection model that uses genetic algorithm (GA). …”
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12
Improving Accuracy Metric with Precision and Recall Metrics for Optimizing Stochastic Classifier
Published 2011“…In this study, we propose a new evaluation metric that combines accuracy metric with the extended precision and recall metrics to negate these detrimental effects. …”
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Improving accuracy metric with precision and recall metrics for optimizing stochastic classifier
Published 2011“…In this study, we propose a new evaluation metric that combines accuracy metric with the extended precision and recall metrics to negate these detrimental effects. …”
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14
Improving accuracy metric with precision and recall metrics for optimizing stochastic classifier
Published 2011“…In this study, we propose a new evaluation metric that combines accuracy metric with the extended precision and recall metrics to negate these detrimental effects.We refer the new evaluation metric as optimized accuracy with recall-precision (OARP). …”
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15
Semiparametric inference procedure for the accelarated failure time model with interval-censored data
Published 2019“…A computationally simple two-step iterative algorithm, called estimationapproximation algorithm, is introduced for estimating the parameters of the model on the basis of the rank estimators. …”
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16
A Systematic Literature Review of Machine Learning Methods for Short-term Electricity Forecasting
Published 2023Conference Paper -
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Role Minimization As An Optimization Metric In Role Mining Algorithms : A Literature Review
Published 2018“…A recent access control model that could accommodate a dynamic structure such as cloud computing can be recognized as role based access control and the role management process of this access control can be identified as role mining.The current trend in role based access control is the role mining problem that can be described as the difficulty to uncover an optimum set of roles from the userpermission assignment.To solve this problem,the researchers have proposed role mining algorithms to produce role set and among the existing algorithms there is an intrinsic topic of the common perception to evaluate the goodness of the generated role set.Eventually,the value of the identified roles could be measured by the preferred metric of optimality namely the number of roles,sizes of userassignment and permission-assignment and Weighted Structural Complexity.Until now, there is some disagreement on the optimization metric but notably many researchers have agreed on the minimization of the number of roles as a solid metric.This paper discusses an overview of the current state-of-the-art on the recent role mining algorithms that focus on role minimization as an optimization metric to evaluate the goodness of the identified roles. …”
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Efficient region of interest based metric learning for effective open world deep face
Published 2022“…To establish the effectiveness, we investigated various threshold finding strategies for five state-of-the-art face recognition algorithms for open world adaptation on different datasets.We also proposed a novel performance evaluation metric for FR algorithms on imbalanced datasets. …”
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Finite impulse response optimizers for solving optimization problems
Published 2019“…In this work, three new estimation-based metaheuristic algorithms are introduced. …”
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20
An improved scatter search algorithm for parameter estimation in large-scale kinetic models of biochemical systems
Published 2019“…Methods: This paper proposes an improved scatter search algorithm to address the challenging parameter estimation problem. …”
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