Search Results - weight estimation ((methods algorithm) OR (based algorithm))
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1
Indoor positioning using weighted magnetic field signal distance similarity measure and fuzzy based algorithms
Published 2021“…The lowest average Euclidean distance is chosen, and the average estimated location of the RPs is calculated. Lastly, for the fuzzy algorithm, a rule-based decision is applied to select whether the triangle area or average Euclidean algorithm is used to find the final estimated position. …”
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2
State estimation of the power system using robust estimator
Published 2016“…In this study, a new robust algorithm based on the quasi weighted least squares (QWLS) estimator is presented. …”
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3
Robust diagnostics and variable selection procedure based on modified reweighted fast consistent and high breakdown estimator for high dimensional data
Published 2022“…Therefore, a robust sure independence screening procedure based on the weighted correlation algorithm of MRFCH for high dimensional data is developed to address this problem. …”
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4
Adaptive beamforming algorithm based on Simulated Kalman Filter
Published 2017“…There are many methods to perform adaptive beamforming and one of the method is to use metaheuristic algorithm, to estimate the weights for individual elements in an array. …”
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5
APPLICATION OF BURG’S ALGORITHM IN STATE ESTIMATION
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Development Of Stereo-Matching Algorithm Based On Adaptive Weighted Prediction
Published 2019“…The experimental result on the proposed algorithm is able to reduce 17.4% of weighted average error for all and 9.62% of weighted average error for nonocc (nonoccluded) compared to others Stereo Matching Algorithm without the proposed framework. …”
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7
Power System State Estimation In Large-Scale Networks
Published 2010“…This thesis describes a pre-screening process to identify the bad measurements and the measurement weights before performing the WLS estimation technique employed in SE. …”
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8
LEMABE: a novel framework to Improve analogy-based software cost estimation using learnable evolution model
Published 2021“…To improve software development cost estimation, the current study has investigated the effect of the LEM algorithm on optimization of features weighting and proposed a new method as well. …”
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9
Local Stereo Matching Algorithm Using Small-Color Census Spared Adaptive Support Weight
Published 2011“…This paper proposed an effective disparity estimation algorithm based on census transform with geodesic support weight, called small-color census spared adaptive support weight (SCCADSW). …”
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10
Estimating the un-sampled ph value via neighbouring points using multi-layer neural network - genetic algorithm
Published 2023“…In investigating this method, three algorithms are used: Neural Network-Genetic Algorithm (MLNN-GA), MLNN with backpropagation (MLNN-BP), and averaging method. …”
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11
Modified least trimmed squares method for face recognition / Nur Azimah Abdul Rahim
Published 2018“…In the proposed algorithm, the contaminated observations are distinguished in C-steps as every observation will be assigned a weight based on a cutoff value which will give a zero weight for any observations with residual error greater than the cutoff value and a weight "one" (1) otherwise. …”
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12
An enhanced distance vector-hop algorithm using new weighted location method for wireless sensor networks
Published 2020“…Aimed at addressing problems mentioned above, an enhanced DV-Hop algorithm based on weighted factor, along with new weighted least squares location technique, is proposed in this paper, and it is called WND-DV-Hop. …”
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13
GMSD-based perceptually motivated non-local means filter for image denoising
Published 2019“…Further, the proposed methodology also helps in mitigating the patch jittering blur effect (PJBE) and over smoothing of denoised images as observed with conventional NLM algorithm. Experimental evaluations based on visual-quality assessment and least-square based metrics have shown that the proposed algorithm yields better denoised image estimates than the conventional NLM algorithm. …”
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14
Statistical data preprocessing methods in distance functions to enhance k-means clustering algorithm
Published 2018“…The suggested approaches are called new approach to min-max (NAMM) and decimal scaling (NADS). The Hybrid mean algorithms which are based on spherical clusters is also proposed to remedy the most significant limitation of the K-Means and K-Midranges algorithms. …”
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15
Use of AR Block Processing for Estimating the State Variables of Power System
Published 2008“…This paper describes an approach to identify and change the measurement weights used in Weight Least Square (WLS) estimation method employed in State Estimation (SE). …”
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16
Modeling of cardiovascular diseases (CVDs) and development of predictive heart risk score
Published 2021“…A novel methodology was used to compute simple heart risk scores called non-laboratory based heart risk score (NLHRS). The methodology is proposed as stacking ensemble ML and the best ML algorithms are used as a base learner to compute relative feature weights. …”
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17
System identification of hammerstein model a quarter car passive suspension systems using Multilayer Perceptron Neural Networks (MPNN)
Published 2005“…Unitwise, Fisher’s Scoring Method Reduces To The Algorithm In Which Each Unit Estimates Its Own Weights By A Weighted Least Square Method. …”
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Performance Analysis of ARMA based Magnetic Resonance Imaging (MRI) Reconstruction Algorithm
Published 2012“…Despite this success, two problems lessen the use of this technique, these are: non availability of optimal method of estimating model order and the model coefficients determination. …”
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Long-term electrical energy consumption: Formulating and forecasting via optimized gene expression programming / Seyed Hamidreza Aghay Kaboli
Published 2018“…To assess the applicability and accuracy of the proposed method for long-term electrical energy consumption, its estimates are compared with those obtained from artificial neural network (ANN), support vector regression (SVR), adaptive neuro-fuzzy inference system (ANFIS), rule-based data mining algorithm, GEP, linear, quadratic and exponential models optimized by particle swarm optimization (PSO), cuckoo search algorithm (CSA), artificial cooperative search (ACS) algorithm and backtracking search algorithm (BSA). …”
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20
Performance comparison of feedforward neural network training algorithms in modeling for synthesis of polycaprolactone via biopolymerization
Published 2018“…This paper aims to identify the most effective training method for biopolymerization. Results show that the quasi-Newton-based and Levenberg–Marquardt algorithms have the best performance with MAPE values of 4.512, 5.31, and 3.21% for the number of average molecular weight, weight average molecular weight, and polydispersity index, respectively.…”
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