Search Results - (( data optimization based algorithm ) OR ( software validation using algorithm ))
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1
Autoreclosure in Extra High Voltage Lines using Taguchi’s Method and Optimized Neural Networks
Published 2008“…The algorithms are developed using MATLABTM software. A range of faults are simulated on EHV modeled transmission line using SimPowerSytemsTM, and the spectra of the fault data are analyzed using fast Fourier transform which facilitates extraction of distinct features of each type of fault. …”
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2
Autoreclosure in Extra High Voltage Lines using Taguchi's Method and Optimized Neural Networks
Published 2009“…The algorithms are developed using MATLAB software. A range of faults are simulated on EHV modeled transmission line using SimPowerSytems, and the spectra of the fault data are analyzed using fast Fourier transform to extract features of each type of fault. …”
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3
Development of classification model between clean water and polluted water based on capacitance properties using Levenberg Marquardt (LM) algorithm of artificial neural network / M...
Published 2020“…These measurement inputs were then going through the process of classification in ANN to generate the optimized models by using LM algorithm. The model is being trained, tested, and validated to differentiate between clean water and polluted water. …”
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Student Project -
4
Autoreclosure in extra high voltage lines using taguchi's method and optimized neural networks
Published 2008“…The algorithms are developed using MATLABâ„¢ software. A range of faults are simulated on EHV modeled transmission line using SimPowerSytemsâ„¢, and the spectra of the fault data are analyzed using fast Fourier transform which facilitates extraction of distinct features of each type of fault. …”
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5
Mathematical models and optimization algorithms for low-carbon Location-Inventory-Routing Problem with uncertainty
Published 2024“…When compared to the Supply Chain Guru X (SCGX) software, the proposed algorithms offer higher practical applicability.…”
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6
Development of efficient t-way test data generation algorithm and execution strategies
Published 2012“…This strategy is able to reduce the number of test data, but the execution time is not optimized. (II) EasyA (Easy Algorithm for 2-way Test Data Generation) is developed based on matrix based calculation to overcome the time constrains by keeping the number of test data in an acceptable range. …”
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7
Controller placement problem in the optimization of 5G based SDN and NFV architecture
Published 2021“…In addition, energy savings of up to 70% are achieved compared to the proposed Dijkstra-based energy-aware algorithms.…”
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8
Variable Neighborhood Descent and Whale Optimization Algorithm for Examination Timetabling Problems at Universiti Malaysia Sarawak
Published 2025“…A constructive algorithm was developed to generate an initial feasible solution, which was subsequently refined using two primary approaches to evaluate their efficiency: Iterative Threshold Pipe Variable Neighborhood Descent (IT-PVND), and a modified Whale Optimization Algorithm (WOA). …”
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9
Graph theory approach for managing lecturers’ schedule using graph colouring method / Siti Nor Ba Basri, Nur Su’aidah Khozaid and Farhana Hazwani Ismail
Published 2023“…By using graph theory, graph colouring techniques, and ILP validation, this work optimizes lecturers' timetable scheduling, resolving conflicts, omissions, limitations, and preferences for optimal educational scheduling and resource allocation. …”
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Student Project -
10
Modeling And Control Of V-Groove Rotary Impact Driver
Published 2020“…The speed is optimized by using state-flow algorithm with fixed-point data types, thus reduced hardware computational requirement with acceptable accuracy. …”
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11
Development of optimized damage prediction method for health monitoring of ultra high performance fiber-reinforced concrete communication tower
Published 2018“…Therefore, this study aims to develop a new health monitoring system for communication towers based on AdaBoost, Bagging, and RUSBoost algorithms as hybrid algorithm, which can predict the damage by using noisy, random, unstable, and skewed frequency data with high accuracy. …”
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12
Production quantity estimation using an improved artificial neural network
Published 2015“…In order to increase the performance of NNBP, optimization techniques such as Genetic Algorithm (GA) and Particle Swarm Optimization (PSO) are being hybrid with the ANN model to become Hybrid Neural Network Genetic Algorithm (HNNGA) model and Hybrid Neural Network Particle Swarm Optimization (HNNPSO) model respectively. …”
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13
Modeling flood occurences using soft computing technique in southern strip of Caspian Sea Watershed
Published 2012“…This approach was based on fuzzy expert system (FES) using Fuzzy Toolbox of MATLAB software. …”
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14
Feature fusion using a modified genetic algorithm for face and signature recognition system
Published 2015“…Results show that the proposed method yield optimal recognition with the highest accuracy of 97.50%. …”
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15
Multifunctional optimized group method data handling for software effort estimation
Published 2022“…Nevertheless, finding the best effort estimation model with good accuracy is hard to serve this purpose. Group Method of Data Handling (GMDH) algorithms have been widely used for modelling and identifying complex systems and potentially applied in software effort estimation. …”
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16
Multi-perspective usability evaluation with multi-criteria decision analysis for optimal selection of open-source software
Published 2021“…A well-organised algorithmic procedure is presented in detail, and a case study was examined to illustrate the validity and feasibility of the proposed methodology. …”
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17
Metaheuristic research: a comprehensive survey
Published 2018“…Moreover, the performance tests are often performed on specific benchmark functions - few studies are those which involve data from real-life scientific or engineering optimization problems. …”
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18
Edge assisted crime prediction and evaluation framework for machine learning algorithms
Published 2022“…To anticipate occurrences, ML methods such as Decision Trees, Neural Networks, K-Nearest Neighbors, and Impact Learning are being utilized, and their performance is compared based on the data processing and modification used. …”
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19
Frit-based controller tuning of a dc-dc boost converter
Published 2022“…Furthermore, we formulate the algorithm for determining the optimal controller parameters based on the Model-Free approach. …”
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Undergraduates Project Papers -
20
Defect recognition method for magnetic leakage detection in oil and gas steel pipes based on improved neural networks / Wang Jie ... [et al.]
Published 2024“…Simulated data are generated using ANSYS software by using models of semi-circular defects in steel pipes, producing magnetic leakage signals of varying intensities. …”
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