Search Results - (( developing variables classification algorithm ) OR ( java visualization using algorithmic ))
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1
A performance analysis of association rule mining algorithms
Published 2016“…In this paper, we evaluate the performance of association rule mining algorithms in-terms of execution times and memory usage using the CPU profiler of Java VisualVM. …”
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Conference or Workshop Item -
2
Performance evaluation of real-time multiprocessor scheduling algorithms
Published 2016“…We hyave used the CPU profiler of Oracle JavaTM VisualVM to monitor the execution of LRE-TL as well as USG algorithms. …”
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3
Classification of tropical rainforest using different classification algorithm based on remote sensing imagery: A study of Gunung Basor
Published 2019“…Remote sensing technologies are used globally to derive some of crucial spatial variable parameter such as vegetation cover. Three different classification algorithm, minimum distance classifier, Mahalanobis distance classifier and maximum likelihood algorithm was applied to classify the forest area in Gunung Basor. …”
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Undergraduate Final Project Report -
4
Visdom: Smart guide robot for visually impaired people
Published 2025“…An Android mobile application, developed using Java and the java.net.Socket library, provides an intuitive and accessible user interface for seamless interaction with the robot. …”
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Final Year Project / Dissertation / Thesis -
5
Gas Identi cation by Using a Cluster-k-Nearest-Neighbor
Published 2009“…Therefore for that reason we develop another algorithm for clustering space which contributes a higher accuracy compares to K-means cluster with less subclass number, higher stability and bounded time of classification with respect to the variable data size. …”
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6
Using fuzzy association rule mining in cancer classification
Published 2011“…A new algorithm has been developed to identify the fuzzy rules and significant genes based on fuzzy association rule mining. …”
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7
Development of a syncope classification algorithm from physiological signals acquired in tilt-table test
Published 2023“…Features that selected for the classification is mean of systolic and diastolic blood pressure, standard deviation of real variability of diastolic blood pressure, and the mean of systolic blood pressure in low and high frequency ratio. …”
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Final Year Project / Dissertation / Thesis -
8
Web-based RIG performance reporting system using interactive visualization techniques / Amir Hambaly Nasaruddin
Published 2019“…D3.js is used as a technology to visualize the result in interactive form or dynamic visualization which is a JavaScript library and Python is a language to program the system. …”
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Thesis -
9
Gene Selection For Cancer Classification Based On Xgboost Classifier
Published 2022“…Due to this situation, development of the gene selection method has become more important in obtain useful information for cancer classification, and diagnoses for other diseases. …”
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Undergraduates Project Papers -
10
A New Quadratic Binary Harris Hawk Optimization For Feature Selection
Published 2019“…However, the original HHO is developed to solve the continuous optimization problems, but not to the problems with binary variables. …”
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11
Enhanced bibliographic data retrieval and visualization using query optimization and spectral centrality measure
Published 2019“…This study proposing an enhance bibliographic data retrieval and visualization using hybrid clustering method consists of K-harmonic mean (KHM) and Spectral Algorithm and eigenvector centrality measure. …”
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12
Design Of Robot Motion Planning Algorithm For Wall Following Robot
Published 2006“…Algorithms are developed for a simulated mobile robot that uses an array of range finders for navigation. …”
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Monograph -
13
Evaluation and Comparative Analysis of Feature Extraction Methods on Image Data to increase the Accuracy of Classification Algorithms
Published 2024“…The classification algorithm used in this research is the Convolutional Neural Network (CNN) algorithm. …”
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14
Optimal Weighted Learning of PCA and PLS for Multicollinearity Discriminators and Imbalanced Groups in Big Data (S/O: 13224)
“…This study developed an algorithm for statistical classification that enable ones to classify a future data to one of predetermined groups based on the measured data which facing two major threats; (i) multicollinearity among the measured variables and (ii) imbalanced groups. …”
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Monograph -
15
Mathematical simulation for 3-dimensional temperature visualization on open source-based grid computing platform
Published 2009“…The development of this architecture is based on several programming language as it involves algorithm implementation on C, parallelization using Parallel Virtual Machine (PVM) and Java for web services development. …”
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Conference or Workshop Item -
16
Improvement of land cover mapping using Sentinel 2 and Landsat 8 imageries via non-parametric classification
Published 2020“…The last phase involves developing a new fusion algorithm using SVM and Fuzzy K-Means Clustering (FKM) algorithms for Sentinel 2 data to enhance LCM accuracy. …”
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Thesis -
17
A comparison of support vector machine and decision tree classifications using satellite data of Langkawi Island
Published 2009“…The study indicates that the classification accuracy of SVM algorithm was better than DT algorithm. …”
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18
Finding an effective classification technique to develop a software team composition model
Published 2017“…Ineffective software team composition has become recognized as a prominent aspect of software project failures.Reports from results extracted from different theoretical personality models have produced contradicting fits, validity challenges, and missing guidance during software development personnel selection.It is also believed that the technique/s used while developing a model can impact the overall results.Thus, this study aims to: 1) discover an effective classification technique to solve the problem, and 2) develop a model for composition of the software development team.The model developed was composed of three predictors: team role, personality types, and gender variables; it also contained one outcome: team performance variable.The techniques used for model development were logistic regression, decision tree, and Rough Sets Theory (RST).Higher prediction accuracy and reduced patte rn complexity were the two parameters forselecting the effective technique.Based on the results, the Johnson Algorithm (JA) of RST appeared to be an effective technique for a team composition model.The study has proposed a set of 24 decision rules for finding effective team members.These rules involve gender classification to highlight the appropriate personality profile for software developers.In the end, this study concludes that selecting an appropriate classification technique is one of the most important factors in developing effective models.…”
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19
Finding an effective classification technique to develop a software team composition model
Published 2018“…The model developed was composed of 3 predictors: team role, personality types, and gender variables; it also contained 1 outcome: team performance variable. …”
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20
Finding an effective classification technique to develop a software team composition model
Published 2018“…The model developed was composed of 3 predictors: team role, personality types, and gender variables; it also contained 1 outcome: team performance variable. …”
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