Search Results - (( a distribution means algorithm ) OR ( parameters variation new algorithm ))
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1
Development an accurate and stable range-free localization scheme for anisotropic wireless sensor networks
Published 2022“…Accordingly, this study aspires to bridge the research gap by exploring a new DV-Hop algorithm to build a fast, costefficient, strong range-free localization scheme. …”
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2
Channel Modelling and Estimation in Multiple-Input Multiple-Output Orthogonal Frequency Division Multiplexing Wireless Communication Systems
Published 2008“…The second issue addressed in this thesis is the channel estimation in MIMO OFDM systems. New time-domain (TD) adaptive estimation methods based on recursive least squares (RLS) and normalized least-mean squares (NLMS) algorithms are proposed. …”
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3
Design of low order quantitative feedback theory and H-infinity-based controllers using particle swarm optimisation for a pneumatic actuator system
Published 2010“…These algorithms are designed to achieve the robustness over a wide range of system parameters change and disturbances. …”
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4
Three phase induction motor coupled to DC motor in hybrid electric vehicle application
Published 2011“…Software in the-loop (SIL) and hardware-in-the-loop (HIL) simulations have been performed for induction motor with electric vehicle load to verify the performance of the new algorithm as well as to tune the control parameters. …”
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5
A new method for decreasing cell-load variation in dynamic cellular manufacturing systems
Published 2016“…Cell load variation is considered a significant shortcoming in scheduling of cellular manufacturing systems. …”
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6
Identifying and estimating solar cell parameters using an enhanced slime mould algorithm
Published 2024“…This study proposed an enhanced slime mould algorithm (ESMA) for identifying the solar cells’ parameters for five photovoltaic (PV) models, making two modifications to the original slime mould algorithm (SMA). …”
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7
Model-based hybrid variational level set method applied to lung cancer detection
Published 2024“…This algorithm simplifies the (Local Intensity Clustering) LIC model and devises a new energy functional based on the region-based pressure function. …”
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8
Backstepping Integral Super Twisting Sliding Mode Control Algorithm For Autonomous Underwater Glider
Published 2019“…The BISTSMC was tested for external disturbance and parameter variations. The BISTSMC has been benchmarked its performances with other sliding mode control (SMC) strategies to evaluate the chattering suppression of the controllers. …”
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9
Beta Distribution Weighted Fuzzy C-Ordered-Means Clustering
Published 2024“…The fuzzy C-ordered-means clustering (FCOM) is a fuzzy clustering algorithm that enhances robustness and clustering accuracy through the ordered mechanism based on fuzzy C-means (FCM). …”
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10
Modified K-Nearest Neighborhood Algorithm For Optimal Selection Of Distribution Centre In The Disaster Relief Operation
Published 2024thesis::master thesis -
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A multi-period scheduling of dynamic cellular manufacturing systems in the presence of cost uncertainty
Published 2016“…To measure the level of cell-load variation a new mathematical index is developed. Then, a new method is proposed for minimizing cell-load variation in the mentioned condition by using control lines. …”
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13
The effect of adaptive parameters on the performance of back propagation
Published 2012“…The Back Propagation algorithm or its variation on Multilayered Feedforward Networks is widely used in many applications. …”
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14
Parallel power load abnormalities detection using fast density peak clustering with a hybrid canopy-K-means algorithm
Published 2025“…Parallel power loads anomalies are processed by a fast-density peak clustering technique that capitalizes on the hybrid strengths of Canopy and K-means algorithms all within Apache Mahout's distributed machine-learning environment. …”
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15
New global maximum power point tracking and modular voltage equalizer topology for partially shaded photovoltaic system / Immad Shams
Published 2022“…Only one dynamic variable is used as a tuning parameter reducing the complexity of the algorithm. …”
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16
An observation of different clustering algorithms and clustering evaluation criteria for a feature selection based on linear discriminant analysis
Published 2022“…The k-means and the Gaussian mixture distribution were adopted as the clustering algorithms and each algorithm was tested on four datasets with four distinct clustering evaluation criteria: Calinski-Harabasz, Davies-Bouldin, Gap and Silhouette. …”
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Slice sampler algorithm for generalized pareto distribution
Published 2018“…In this paper, we developed the slice sampler algorithm for the generalized Pareto distribution (GPD) model. …”
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18
To develop an efficient variable speed compressor motor system
Published 2007“…To achieve a robust controller from variation of motor parameters, a real-time or on-line learning algorithm based on a second order optimization Levenberg-Marquardt is employed. …”
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Implementation of Parallel K-Means Algorithm to Estimate Adhesion Failure in Warm Mix Asphalt
Published 2020“…The results showed that the PKIP algorithm decreases the execution time up to 30 to 46 if compared with the sequential k means algorithm when implemented using multiprocessing and distributed computing. …”
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Identification of continuous-time model of hammerstein system using modified multi-verse optimizer
Published 2021“…The essential feature of the average design parameter updating mechanism is that it helps any trapped design parameter jump out from the local optima region and continue a new search track. …”
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