Search Results - (( simulation optimization based algorithm ) OR ( data application testing algorithm ))
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1
Multi-Objective Hybrid Algorithm For The Classification Of Imbalanced Datasets
Published 2019“…A new self-adaptive hybrid algorithm (CSCMAES) is introduced for optimization. …”
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Thesis -
2
An exponential based simulated kalman filter algorithm for data-driven PID tuning in liquid slosh controller
Published 2018“…This paper presents an Exponent-based Simulated Kalman Filter (EbSKF) algorithm. …”
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3
An experimental study of neighbourhood based metaheuristic algorithms for test case generation satisfying the modified condition / decision coverage criterion
Published 2018“…To generate test cases that satisfy MC/DC criterion, many researchers adopt neighborhood based meta-heuristics algorithms (including that of Simulated Annealing and Hill Climbing) as the problem itself is neighborhood based. …”
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4
Optimisation model for scheduling MapReduce jobs in big data processing / Ibrahim Abaker Targio Hashem
Published 2017“…In this study, we aim to optimize task scheduling and resource utilization using an evolutionary algorithm based on the proposed completion time and monetary cost of cloud service models. …”
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5
Simulated kalman filter (SKF) based image template matching for distance measurement by using stereo vision system
Published 2018“…In addition, it is expected that it can be applied in real-time application. In this study, Simulated Kalman Filter (SKF) is applied to image template matching application as the optimization algorithm. …”
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6
Application of Evolutionary Algorithm for Assisted History Matching
Published 2014“…While the automatic method focus on optimization which is normally computer based. In this project, we will define and discuss the application of evolutionary algorithm in assisted history matching. …”
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Final Year Project -
7
New random approaches of modified adaptive bats sonar algorithm for reservoir operation optimization problems
Published 2024“…In the fourth phase, the newly developed algorithm undergoes testing on the formulated ROOPs and compared to several contemporary optimizer algorithms. …”
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8
Taguchi's method for optimized neural network based autoreclosure in extra high voltage lines
Published 2008“…The fault identification prior to reclosing is based on optimized artificial neural network associated with Levenberg Marquardt algorithm to train the ANN and Taguchi's Method to find optimal parameters of the algorithm and number of hidden neurons. …”
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9
Comparative Analysis of Neighborhood based Meta-heuristic Algorithms for MC/DC Test Data Generation
Published 2016“…Most implementations have been focused on neighborhood-based meta-heuristics. In order to help test engineers to make informed decision on the best neighborhood based implementations, this paper investigates the size and time performance of two MC/DC test strategies re-implementation based on Simulated Annealing against two newly developed strategies based on Great Deluge and Late Acceptance Hill Climbing algorithms respectively. …”
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10
An improved data classification framework based on fractional particle swarm optimization
Published 2019“…The proposed algorithm is tested and verified for optimization performance comparison on ten benchmark functions against six existing established algorithms in terms of Mean of Error and Standard Deviation values. …”
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11
Iterative And Single-Step Solutions Of Two Dimensional Time-Domain Inverse Scattering Problem Featuring Ultra Wide Band Sensors
Published 2010“…Finally, the algorithms‘ robustness against the noisy data was evaluated using two simulated experiments with signal-to-noise ratios of 6 and 8 dB respectively.…”
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12
Autoreclosure in Extra High Voltage Lines using Taguchi’s Method and Optimized Neural Networks
Published 2008“…The fault identification prior to reclosing is based on optimized artificial neural network associated with standard Error Back-Propagation, Levenberg Marquardt Algorithm and Resilient Back-Propagation training algorithms together with Taguchi’s Method. …”
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13
Autoreclosure in Extra High Voltage Lines using Taguchi's Method and Optimized Neural Networks
Published 2009“…The fault identification prior to reclosing is based on optimized artificial neural network associated with standard Error Back-Propagation, Levenberg Marquardt Algorithm and Resilient Back-Propagation training algorithms together with Taguchi’s Method. …”
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14
Using the evolutionary mating algorithm for optimizing deep learning parameters for battery state of charge estimation of electric vehicle
Published 2023“…According to the simulation results, the proposed EMA-DL algorithm was found to outperform all the other compared algorithms based on the evaluated metrics. …”
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Article -
15
Modeling And Control Of V-Groove Rotary Impact Driver
Published 2020“…Finally, prototype was built based on the software simulation model for actual human test and validation. …”
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16
Battery energy storage system sizing using PSO algorithm in DIgSILENT powerfactory
Published 2022“…The IEEE 9-bus system is the test case used to demonstrate and discuss the application of algorithms in DPL script. …”
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17
A class skew-insensitive ACO-based decision tree algorithm for imbalanced data sets
Published 2021“…The proposed algorithm was compared to the existing algorithm, ATM in nine (9) publicly available imbalanced data sets. …”
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Article -
18
A Single Objective Flower Pollination Algorithm for Modeling the Horizontal Flexible Plate System
Published 2020“…The collected of real vibration data through experimental study was then utilized to develop the dynamic system model based on linear autoregressive with exogenous (ARX) model structure and optimized by flower pollination algorithm (FPA). …”
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Proceeding -
19
Voting algorithms for large scale fault-tolerant systems
Published 2011“…To solve this problem and gain benefits of this algorithm, we employed parallel algorithm technique and by using optimal number of processors, we could propose optimal algorithms known as Parallel Average Voting and Parallel Weighted Average Voting which both have optimal time complexity and less calculation cost. …”
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20
Autoreclosure in extra high voltage lines using taguchi's method and optimized neural networks
Published 2008“…The fault identification prior to reclosing is based on optimized artificial neural network associated with standard Error Back-Propagation, Levenberg Marquardt Algorithm and Resilient Back-Propagation training algorithms together with Taguchi's Method. …”
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