Search Results - (( (quantile OR quantify) selection using algorithm ) OR ( java implementation path algorithm ))
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Heavy Transportation Shortest Route using Dijkstra’s algorithm (HETRO) / Nurul Aqilah Ahmad Nezer
Published 2017“…The development tools used in developing this project is NetBeans by using Java for the implementation of the coding. The methodology that used for developing this system is the Dijkstra’s algorithm. …”
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2
Elastic net penalized Quantile Regression Model and Empirical Mode Decomposition for Improving the Accuracy of the Model Selection
Published 2023“…Such methods are ridge penalized quantile regression, lasso penalized quantile regression, and elastic net penalized quantile regression which are used for variable selection and regularization and deals with the multicollinearity problem when it exists between the predictor variables. …”
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Embedded system for indoor guidance parking with Dijkstra’s algorithm and ant colony optimization
Published 2019“…BST inserts the nodes in the way that the Dijkstra’s can find the empty parking in fastest way. Dijkstra’s algorithm initials the paths to finding the shortest path while ACO optimizes the paths. …”
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Path planning for unmanned aerial vehicle (UAV) using rotated accelerated method in static outdoor environment
Published 2021“…In this study, a fast iterative method known as Rotated Successive Over-Relaxation (RSOR) is introduced. The algorithm is implemented in a self-developed 2D Java tool, UAV Planner. …”
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Penalized Quantile Regression Methods And Empirical Mode Decomposition For Improving The Accuracy Of The Model Selection
Published 2024“…Therefore, three methods based on a combination of the empirical mode decomposition (EMD) algorithm and penalized quantile regression have been proposed in this study. …”
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Smart appointment organizer for mobile application / Mohd Syafiq Adam
Published 2009“…The main component of this prototype is the use of Dijkstra algorithm to compute the shortest path from source of appointment to the 6 points of destinations within UiTM Shah Alam. …”
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VLSI floor planning optimization using genetic algorithm and cross entropy method / Angeline Teoh Szu Fern
Published 2012“…CE is a new algorithm that was recently developed using probability. …”
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Development of saliency metric for autonomous landmark selection in cognitive robot navigation / Gao Hanyang
Published 2022“…This dissertation proposes an algorithm to quantify urban landmarks based on visual salience indicators for cognitive robot navigation. …”
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9
Implementation of Color Filtering on FPGA
Published 2007“…The second is the double band-pass-filter algorithm. Work is currently conducted to quantify the effectiveness of the band-pass filtering algorithm on FPGA before proceeding to test and implement the triple and quadruple band-pass filtering methods.…”
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10
Leveraging mechanomyography signal for quantitative muscle spasticity assessment of upper limb in neurological disorders using machine learning
Published 2024“…The test results determined the selection of twenty-five features from a total of forty-eight which be used to train an optimum classifier algorithm for the purpose of quantifying the level of muscle spasticity. …”
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Prediction of photovoltaic system output using hybrid Cuckoo Search Least Square Support Vector Machine / Muhammad Aidil Adha Aziz
Published 2019“…In this thesis, Mean Absolute Percentage Error (MAPE) is used to quantify the performance of the prediction. …”
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12
Implementation of color filtering on FPGA
Published 2007“…The second is the double band-pass-filter algorithm. Work is currently conducted to quantify the effectiveness of the band-pass filtering algorithm on FPGA before proceeding to test and implement the triple and quadruple band-pass filtering methods. …”
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13
Load shedding scheme for islanded distribution network with flexible load selection and power changes / Ja’far Saifeddin Abdelhafiz Jallad
Published 2018“…A metaheuristic algorithm in the UFLS scheme can be used to select the best load combination in real time. …”
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14
Leveraging mechanomyography signal for quantitative muscle spasticity assessment of upper limb in neurological disorders using machine learning
Published 2024“…The test results determined the selection of twenty-five features from a total of forty-eight which be used to train an optimum classifier algorithm for the purpose of quantifying the level of muscle spasticity. …”
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15
Monitoring the drying process of glutinous rice using hyperspectral imaging coupled with multivariate analysis
Published 2024“…The model prediction performance shows an accuracy (R²P) of 0.9206 with RMSEP of 1.1410. Using CARS algorithm resulted in the selection of 21 optimal wavelengths that are highly associated with the moisture content of glutinous rice during the drying process and the developed PLS model based on the selected wavelength gave an increased model accuracy with R2CV and RMSECV of 0.9176 and 1.0986 respectively. …”
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Objective quantification of selective attention in schizophrenia a hybrid TMS – EEG approach
Published 2017“…The aim of the study is to quantify objectively the neural correlate of selective attention that reflected in auditory late responses (ALRs) using signal processing techniques. …”
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Evolutionary cost-cognizant regression test case prioritization for object-oriented programs
Published 2019“…Therefore, this study proposed a cost-cognizant TCP approach for object-oriented software that uses path-based integration testing to identify the possible execution path extracted from the Java System Dependence Graph (JSDG) model of the source code using forward slicing technique. …”
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18
Wavelet-based compression of medical images: Filter-bank selection and evaluation
Published 2003“…The statistical indices such as mean square error (MSB), maximum absolute error (MAE) and peak signal-to-noise ratio (PSNR) were used to quantify the effect of wavelet compression of selected images. …”
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Tracking using normalized cross correlation and color space
Published 2007“…In addition to the TDR being used as a metric to determine the accuracy of a tracking method, another metric was formulated to quantify the accuracy of a tracking algorithm. …”
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