Search Results - (( data estimation clustering algorithm ) OR ( parameter estimation method algorithm ))
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1
Parameter Estimation of Lorenz Attractor: A Combined Deep Neural Network and K-Means Clustering Approach
Published 2022“…DNN techniques is suitable in solving nonlinear and complex problem. The most popular method to solve parameter estimation problem is using optimization algorithm that easily trap to local minima and poor in exploitation to find the good solutions. …”
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2
A new hybrid deep neural networks (DNN) algorithm for Lorenz chaotic system parameter estimation in image encryption
Published 2023“…The research starts with developing the hybrid deep learning model consisting of DNN and a K-Means Clustering Algorithm. Then, the developed algorithm is implemented to estimate the parameters of the Lorenz system. …”
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3
Parameter estimation and outlier detection for some types of circular model / Siti Zanariah binti Satari
Published 2015“…We derive the maximum likelihood estimation of parameters as well as the variance-covariance of parameters. …”
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4
Parameter estimation of K-distributed sea clutter based on fuzzy inference and Gustafson-Kessel clustering
Published 2011“…The main contribution of the proposed method is the ability to estimate the parameters, given a small number of data which will usually be the case in practical applications. …”
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5
Semiparametric binary model for clustered survival data
Published 2014“…We investigated the effects of the strength of cluster correlation and censoring rates on properties of the parameters estimate. …”
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6
The multiple outliers detection for circular univariate data using different agglomerative clustering algorithms
Published 2024“…Then, the results performance of the agglomerative clustering algorithms were compared and the best method for certain data conditions is chosen. …”
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7
Optimization of ANFIS with GA and PSO estimating α ratio in driven piles
Published 2020“…The system was optimized by changing the number of clusters in the FIS and then the output was used for the GA and PSO optimization algorithm. …”
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8
Predicting the popularity of tweets using the theory of point processes.
Published 2019“…We further propose an inhomogeneous Poisson process model and an estimation method which utilizes internal and external knowledge, based on the times of historical retweets up to the censoring time, and the complete retweet sequences in the training data set respectively. …”
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9
EZ-SEP: extended Z-SEP routing protocol with hierarchical clustering approach for wireless heterogeneous sensor network
Published 2021“…In addition, EZ-SEP is weighted up using various estimation schemes such as base station repositioning, altering the field density, and variable nodes energy for comparison with the previous parent algorithm. …”
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10
Detection And Identification Of Stiction In Control Valves Based On Fuzzy Clustering Method
Published 2016“…In this study, in order to improve covariance estimation of fuzzy clustering, linearly correlation of data is detected. …”
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11
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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12
Operational structural damage identification using de-noised modal feature in machine learning / Chen Shilei
Published 2021“…For the unsupervised learning method, the hierarchical cluster analysis can correctly cluster the samples in terms of their damage states. …”
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13
Indoor positioning using weighted magnetic field signal distance similarity measure and fuzzy based algorithms
Published 2021“…Therefore, for the second objective, another algorithm named the fuzzy algorithm is designed which combines the clustering algorithm, matching algorithm, triangle area algorithm and average Euclidean algorithm used to estimate location. …”
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14
Fuzzy rank cluster top k Euclidean distance and triangle based algorithm for magnetic field indoor positioning system
Published 2021“…Then, we create a rank cluster algorithm where we match the top 10 ranks RPs with the nearest Euclidean distance to the TP with the RPs cluster. …”
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15
Balancing Exploitation And Exploration Search Behavior On Nature-Inspired Clustering Algorithms
Published 2018“…As a conclusion, balancing the search behavior notably enhanced the overall performance of the three proposed frameworks and made each of them an excellent tool for data clustering.…”
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16
Statistical data preprocessing methods in distance functions to enhance k-means clustering algorithm
Published 2018“…The K-Means algorithm is the commonest and fast technique in partitional cluster algorithms, although with unnormalized datasets it can achieve local optimal. …”
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17
Datasets Size: Effect on Clustering Results
Published 2013“…In this paper, we proposed a research technique that implements descriptive algorithms on numeric datasets of varied sizes. We modeled each subset of our data using EM clustering algorithm; two different numbers of partitions (k) were estimated and used for each experiment. …”
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18
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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19
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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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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