Search Results - (( java simulation optimization algorithm ) OR ( _ interpolating data algorithm ))
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1
Numerical Integration And Data Reduction For Application In Photometry
Published 2003“…In this thesis, an algorithm based on a local interpolation scheme called the Average Angle Method was developed for numerical integration and data reduction of photometric data, and in general, for any data set sharing similar characteristics as the luminous intensity data The new interpolation scheme interpolates discrete data with piecewise cubic polynomials having a CI continuity in the interior. knots. …”
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2
Optimal search algorithm in a big database using interpolation–extrapolation method
Published 2019“…Search using traditional binary-search algorithm can be accelerated by employing an interpolation search technique when the data is regularly distributed. …”
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3
Attribute reduction based scheduling algorithm with enhanced hybrid genetic algorithm and particle swarm optimization for optimal device selection
Published 2022“…The simulation is implemented with iFogSim and java programming language. …”
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4
Enhancement of Ant Colony Optimization for Grid Job Scheduling and Load Balancing
Published 2011“…Global pheromone update is performed after the completion of processing the jobs in order to reduce the pheromone value of resources. A simulation environment was developed using Java programming to test the performance of the proposed EACO algorithm against existing grid resource management algorithms such as Antz algorithm, Particle Swarm Optimization algorithm, Space Shared algorithm and Time Shared algorithm, in terms of processing time and resource utilization. …”
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5
Ant colony optimization algorithm for load balancing in grid computing
Published 2012“…The proposed algorithm is known as the enhance ant colony optimization (EACO). …”
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Monograph -
6
Development of android application for peninsular Malaysia GEOID height calculator / Mohamad Nazir Md Nazri
Published 2021“…Verification of algorithm of interpolation method had verified that only two interpolation methods are useable for producing results which are Bilinear Interpolation and Inverse Distance Weighted. …”
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7
Analysis of multiexponential transient signals using interpolation-based deconvolution and parametric modeling techniques
Published 2003“…One method of overcoming this d1ficulty is by incorporating the spline interpolation algorithm into the nonlinear preprocessing procedure. …”
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Proceeding Paper -
8
Exponential Parameterized Cubic B-Spline Curves And Surfaces
Published 2020“…In developing B-spline curve interpolation method, an algorithm is presented for interpolating data points. …”
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9
STEP-NC Interpolator for General 2D and 3D Parametric Curve / Dzullijah Ibrahim...[et al.]
Published 2017“…A STEP-NC interface to OAPC-NC interpolator using STEP-NC tool path data is proposed and developed. …”
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10
OPTIMIZED MIN-MIN TASK SCHEDULING ALGORITHM FOR SCIENTIFIC WORKFLOWS IN A CLOUD ENVIRONMENT
Published 2023“…To achieve this, we propose a new noble mechanism called Optimized Min-Min (OMin-Min) algorithm, inspired by the Min-Min algorithm. …”
Review -
11
Comparison of envelope interpolation techniques in Empirical Mode Decomposition (EMD) for eyeblink artifact removal from EEG
Published 2017“…However, the algorithm is relatively slow for real time processing due to the iterative nature of EMD and the fact that interpolation of large number of data points consumes a lot of computer resources. …”
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12
Embedded system for indoor guidance parking with Dijkstra’s algorithm and ant colony optimization
Published 2019“…This study proposes a car parking management system which applies Dijkstra’s algorithm, Ant Colony Optimization (ACO) and Binary Search Tree (BST) in structuring a guidance system for indoor parking. …”
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13
Features selection for intrusion detection system using hybridize PSO-SVM
Published 2016“…Hybridize Particle Swarm Optimization (PSO) as a searching algorithm and support vector machine (SVM) as a classifier had been implemented to cope with this problem. …”
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14
Interpolation and extrapolation techniques based Neural Network in estimating the missing ionospheric TEC data
Published 2024“…Normalized RMSE, RMSE and relative correction are computed for both methods to evaluate the capability of NN to interpolate and extrapolate the missing data. The results show that NN is able to interpolate the missing TEC data within the input range better than extrapolating the missing data outside the input range. …”
Conference Paper -
15
An efficient method of biometric matching using interpolated ECG data
Published 2010“…Results of experiments confirmed that the template matching using interpolation method achieved better accuracy (up to 4.46%) than the existing method without interpolation when using ECG data with lower sampling rate.…”
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Proceeding Paper -
16
Resource management in grid computing using ant colony optimization
Published 2011“…Resources with high pheromone value are selected to process the submitted jobs.Global pheromone update is performed after completion processing the jobs in order to reduce the pheromone value of resources.A simulation environment was developed using Java programming to test the performance of the proposed EACO algorithm against other ant based algorithm, in terms of resource utilization.Experimental results show that EACO produced better grid resource management solution.…”
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Monograph -
17
THE DEVELOPMENT OF C1 CUBIC TIMMER TRIANGULAR PATCHES FOR SCATTERED DATA INTERPOLATION
Published 2020“…Finally, the cubic Timmer triangular patch is used to reconstruct a surface from non-uniform and uniform scattered data. To do this, we employ three stages algorithm…”
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18
Interpolation and Extrapolation Techniques Based Neural Network in Estimating the Missing Ionospheric TEC Data
Published 2024Proceedings Paper -
19
Implementation of locust inspired scheduling algorithm with huge number of servers for energy efficiency in a cloud datacenter
Published 2019“…Cloudsim is used as Discrete Event Simulation tool and Java as coding language to evaluate LACE algorithm. …”
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20
Trigonometric-Euclidean-Smoother Interpolator (TESI) for continuous time-series and non-time-series data augmentation for deep neural network applications in agriculture
Published 2023“…Deep neural networks (DNNs) can predict such crop variables. However, DNNs are data greedy algorithms that overfit/underfit on small-size datasets. …”
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