Search Results - (( time estimation clustering algorithm ) OR ( weight distribution process algorithm ))*
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1
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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2
Kernel and multi-class classifiers for multi-floor wlan localisation
Published 2016“…The multi-class classification strategy is used to ensure quick estimation of the multi-class NN algorithms. All of the algorithms are later combined to provide device location estimation for multi-floor environment. …”
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3
Segmentation of MRI brain images using statistical approaches
Published 2011“…The Gaussian Mixture Model (GMM) is a clustering algorithm that is commonly used for brain MRI segmentation. …”
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4
Efficient tag grouping RFID anti-collision algorithm for internet of things applications based on improved k-means clustering
Published 2023“…In the initialization stage, the reader uses improved K-means clustering running concurrently with a tag counter algorithm to cluster tags into K groups using tags RN16 while the counter returns an accurate tag number estimate. …”
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A new hybrid deep neural networks (DNN) algorithm for Lorenz chaotic system parameter estimation in image encryption
Published 2023“…The first research objective is to develop a new deep learning algorithm by a hybrid of DNN and K-Means Clustering algorithms for estimating the Lorenz chaotic system. …”
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6
Firefly analytical hierarchy algorithm for optimal allocation and sizing of distributed generation in radial distribution network
Published 2022“…Moreover, the empirical results obtained showed that incorporating the AHP into Firefly Algorithm improved the accuracy of weight calculations in the multi-objective formulation of the optimisation process. …”
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7
Identifying homogeneous rainfall catchments for non-stationary time series using TOPSIS algorithm and bootstrap K-sample Anderson-Darling test
Published 2018“…The purpose of this study is to introduce a new regionalization algorithm to identify the most suitable agglomerative hierarchical clustering (AHC) algorithm and the optimum number of homogeneous rainfall catchments for non-stationary rainfall time series. …”
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8
Density based subspace clustering: a case study on perception of the required skill
Published 2014“…In the early stage, the present research estimates density dimensions and the results are used as input data to determine the initial cluster based on density connection, using DBSCAN algorithm. …”
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9
Density subspace clustering: a case study on perception of the required skill
Published 2014“…In the early stage, the present research estimates density dimensions and the results are used as input data to determine the initial cluster based on density connection, using DBSCAN algorithm. …”
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10
Improvement of routing protocol in wireless sensor network for energy consumption to maximize network lifetime
Published 2013“…We show that existing energy models over-estimate life expectancy of a sensor node by 30–58% and also yield an “optimised” number of clusters which is too large. …”
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11
Peak pressure analysis of foot plantar distribution based on image processing algorithm
Published 2018“…The other main goal of this work is to create an algorithm which has the ability to formulate accurately and reliably the distribution of pressure over the foot plantar. …”
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12
An improved machine learning model of massive Floating Car Data (FCD) based on Fuzzy-MDL and LSTM-C for traffic speed estimation and prediction
Published 2023“…In the second method, a new traffic estimation method is proposed using Fuzzy C-Mean (FCM) clustering and Minimum Description Length (MDL). …”
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13
Averaged kernel floor localization algorithm for multi-floor WLAN positioning
Published 2017“…Additionally, the proposed algorithm has very low processing time of about 29 times lower compared to previous floor localization algorithms.…”
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14
Optimization of PID parameters for hydraulic positioning system utilizing variable weight Grey-Taguchi and particle swarm optimization
Published 2014“…Previously, researchers had integrated PSO algorithms in the PID parameter tuning process. This research aims to improve the PSO-PID tuning algorithms by integrating the tuning process with the Variable Weight Grey-Taguchi Design of Experiment (DOE) method. …”
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RWP-NSGA II: reinforcement weighted probabilistic NSGA II for workload allocation in fog and internet of things environment
Published 2024“…This paper proposes an improved version of NSGA II, namely, reinforcement weighted probabilistic NSGA II, which uses weighted probabilistic mutation. …”
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17
Optimization of PID Parameters Utilizing Variable Weight Grey-Taguchi Method and Particle Swarm Optimization
Published 2017“…Previously, researchers had integrated PSO algorithms in the PID parameter tuning process. This research aims to improve the PSO-PID tuning algorithms by integrating the tuning process with the Variable Weight Grey-Taguchi Design of Experiment (DOE) method. …”
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18
Implementasi Algoritma Cheapest Insertion Heuristic (CIH) dalam Penyelesaian Travelling Salesman Problem (TSP)
Published 2018“…The purpose of TSP is to find the route of all cities with minimum total weight.Many algorithms have been found to solve the TSP, one of which is the Cheapest Insertion Heuristic (CIH) algorithm in the process of inserting weighted steps obtained from the equation c (i, k, j) = d (i, k) + d (k, j) - d (i, j). …”
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Poisson Transmuted Exponential Distribution For Count Data With Skewed, Dispersed And Excess Zero
Published 2024“…Three Transmutation Maps Are Used To Extend The Exponential Distributions, The Weighted Exponential Distribution, And The New Weighted Exponential Distribution. …”
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20
ETERS: A comprehensive energy aware trust-based efficient routing scheme for adversarial WSNs
Published 2021“…A novel and efficient cluster head selection algorithm (ECHSA) is employed to improve the performance of the cluster head (CH) selection process in clustered WSN. …”
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