Search Results - (( regional distribution means algorithm ) OR ( parameters variation case algorithm ))
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1
Improving the synthetic coefficient of variation chart by incorporating side sensitivity
Published 2024“…Algorithms to obtain optimal chart parameters are also formulated. …”
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2
A comparative effectiveness of hierarchical and non-hierarchical regionalisation algorithms in regionalising the homogeneous rainfall regions
Published 2022“…The results of the analysis show that Forgy K-means non-hierarchical (FKNH), Hartigan- Wong K-means non-hierarchical (HKNH), and Lloyd K-means non-hierarchical (LKNH) regionalisation algorithms are superior to other automated agglomerative hierarchical and non-hierarchical regionalisation algorithms. …”
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A comparative effectiveness of hierarchical and nonhierarchical regionalisation algorithms in regionalising the homogeneous rainfall regions
Published 2022“…The results of the analysis show that Forgy K-means non-hierarchical (FKNH), HartiganWong K-means non-hierarchical (HKNH), and Lloyd K-means non-hierarchical (LKNH) regionalisation algorithms are superior to other automated agglomerative hierarchical and non-hierarchical regionalisation algorithms. …”
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4
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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5
A comparative effectiveness of hierarchical and nonhierarchical regionalisation algorithms in regionalising the homogeneous rainfall regions
Published 2022“…The results of the analysis show that Forgy K-means non-hierarchical (FKNH), HartiganWong K-means non-hierarchical (HKNH), and Lloyd K-means non-hierarchical (LKNH) regionalisation algorithms are superior to other automated agglomerative hierarchical and non-hierarchical regionalisation algorithms. …”
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6
The effect of key parameters on the design of an optimized CAES power plant
Published 2017“…In order to obtain a more tangible realization, it is necessary to verify the results against the variation of key parameters. In this study, the sensitivity analysis is performed based on main parameters including plant loading and ambient condition and the resultant trends of each case are presented. …”
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A method for computation of surface roughness of digital elevation model terrains via multiscale analysis
Published 2010“…Granulometric analysis is employed to compute the average area of curvature regions in the terrain, and the average roughness of the terrain due the distribution of curvature regions. …”
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A method for computation of surface roughness of digital elevation model terrains via multiscale analysis
Published 2010“…Granulometric analysis is employed to compute the average area of curvature regions in the terrain, and the average roughness of the terrain due the distribution of curvature regions. …”
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Novel wide-area fault location and predictive maintenance technique for distribution system
Published 2023“…The algorithm is able to identify the faulted branches in a radial distribution system with high accuracy. …”
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Comparison between clustering algorithm for rainfall analysis in Kelantan / Wan Nurshazelin Wan Shahidan and Siti Nurasikin Abdullah
Published 2017“…So, in this study clustering algorithm on rainfall distribution dataset is done using WEKA 3.8 software. …”
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Development of controller for an underactuated autonomous underwater vehicle (AUV)
Published 2019“…The simulation results have shown that the proposed controller provides the smallest chattering about more than 1000 times smaller than STSMC, more than 100 times smaller than back-stepping SMC in nominal, disturbance and parameter variation cases respectively. The steady error of the proposed controller also gives the smallest steady state error of four times smaller than STSMC and back-stepping SMC in all cases for pitching angle and 100 times smaller than STSMC and back-stepping for excess mass. …”
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Research Report -
12
Enhancing clustering algorithm with initial centroids in tool wear region recognition
Published 2020“…Regular unsupervised K-means is refocused as semi-supervised Fixum K-means. …”
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Scheduling dynamic cellular manufacturing systems in the presence of cost uncertainty using heuristic method
Published 2016“…It is observed that in 67% of studied cases, inflation rate can strengthen cell load variation. …”
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Development of lung cancer prediction system using meta-heuristic optimized deep learning model
Published 2023“…After that cancer-affected region in the lung is segmented with the help of the proposed Butterfly Optimization Algorithm-based K-Means Clustering (BOAKMC) algorithm. …”
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15
TRMM Satellite Algorithm Estimates to Represent the Spatial Distribution of Rainstorms
Published 2016“…These findings suggest that satellite algorithm estimations from TRMM are suitable to represent the spatial distribution of extreme rainfall.…”
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Variational Bayesian inference for exponentiated Weibull right censored survival data
Published 2023“…The results from the experiments reveal that the Variational Bayesian (VB) approach is better than the competing Metropolis-Hasting Algorithm and the reference maximum likelihood estimates.…”
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An attack proof intelligent digital watermarking based on safe region of fast fourier transform
Published 2010“…Keywords: (Artificial Neural Network, Back Propagation algorithm, Fast Fourier Transform, FFT, Image watermarking, Safe Region,) …”
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Proceeding Paper -
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Optimisation of fed-batch fermentation process using deep reinforcement learning
Published 2023“…When dealing with model mismatch (±15% parameter variation in critical growth and maximum glucose uptake rate) and process disturbance (±20% deviation in substrate feeding concentration), the proposed algorithm was able to handle the changes with a minor effect on the yeast yield up to 13.78% and 2.52%, respectively, across all different initial condition cases. …”
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20
Computation of scale-independent surface roughness via the generation of multiscale digital elevation models
Published 2008“…Using the mask of pixels modified at each scale, granulometric analysis is employed to compute the average size of convex and concave regions in the DEM, and the scale-independent average roughness of the terrain of the DEM due the distribution of convex and concave regions in the terrain. …”
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