Search Results - (( developing data normalization algorithm ) OR ( java evaluation learning algorithm ))
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A Feature Ranking Algorithm in Pragmatic Quality Factor Model for Software Quality Assessment
Published 2013“…The assessment of quality attributes has been improved using FRA algorithm enriched with a formula to calculate the priority of attributes and followed by learning adaptation through Java Library for Multi Label Learning (MULAN) application. …”
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Adoption of machine learning algorithm for analysing supporters and non supporters feedback on political posts / Ogunfolajin Maruff Tunde
Published 2022“…The method was implemented using Java and the results of the simulation were evaluated using five standard performance metrics: accuracy, AUC, precision, recall, and f-Measure. …”
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An ensemble learning method for spam email detection system based on metaheuristic algorithms
Published 2015“…In the second phase, a classifier ensemble learning model is proposed consisting of separate outputs: (i) To select a relevant subset of original features based on Binary Quantum Gravitational Search Algorithm (QBGSA), (ii) To mine data streams using various data chunks and overcome a failure of single classifiers based on SVM, MLP and K-NN algorithms. …”
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Web-based clustering tool using fuzzy k-mean algorithm / Ahmad Zuladzlan Zulkifly
Published 2019“…Even a normal people using clustering to grouping their data. …”
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Algorithm for calculation of cephalometric soft tissue facial traits
Published 2007“…This paper presents development of a new soft tissue analysis algorithm, which will be used as an analysis tool in Computer Assisted Craniofacial Surgery Planner – a surgery planning system under development. …”
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Landslide Susceptibility Mapping with Stacking Ensemble Machine Learning
Published 2024“…In this paper, the stacking ensemble method is used to increase the accuracy of the machine learning model for LSM where the base (first-level) learners use five ML algorithms namely decision tree (DT), k-nearest neighbor (KNN), AdaBoost, extreme gradient boosting (XGB) and random forest (RF). …”
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Smart energy meter with adaptive communication data transfer algorithm for electrical energy monitoring
Published 2021“…Thus, in this thesis, a new Smart Energy Meter (SEM) with adaptive data transfer algorithm is designed to accommodate the problem. …”
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Features selection for intrusion detection system using hybridize PSO-SVM
Published 2016“…The simulation will be carried on WEKA tool, which allows us to call some data mining methods under JAVA environment. The proposed model will be tested and evaluated on both NSL-KDD and KDD-CUP 99 using several performance metrics.…”
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Hardware Simulator for Seizure, Preseizure and Normal Mode Signal Generation in LabVIEW Environment for Research
Published 2013“…Here we develop a hardware simulator of the EEG model or to simulator any EEG data set in either .edf or .tdmsot .txtformat from any patient or database depository. …”
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Adaptive policing and shaping algorithms on inbound traffic using generalized Pareto distribution / Nor Azura Ayop
Published 2016“…Log likelihood estimation technique is used to fit the best 2-parameter CDF compared to Weibull, Normal and Rician distribution model. The percentage level 5% under original bandwidth used is developed on policing and shaping algorithms to control bandwidth used. …”
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The effect of dose calculation algorithms on the normal tissue complication probability values of thoracic cancer
Published 2015“…Purpose: To identify the effect of dose calculation algorithms on the Normal Tissue Complication Probability values of thoracic cancer. …”
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Spectral discrimination and index development of roofing materials and conditions using field spectroscopy and worldview-3 satellite image
Published 2016“…Three feature selection algorithms of Genetic Algorithm (GA), Support Vector Machine (SVM) and Random Forest (RF) were used to select the most significant wavelengths since the algorithms works well with large size of data and widely applied for feature selection of hyperspectral remote sensing data. …”
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Data normalization techniques in swarm-based forecasting models for energy commodity spot price
Published 2014“…Data mining is a fundamental technique in identifying patterns from large data sets.The extracted facts and patterns contribute in various domains such as marketing, forecasting, and medical.Prior to that, data are consolidated so that the resulting mining process may be more efficient.This study investigates the effect of different data normalization techniques.which are Min-max, Z-score and decimal scaling, on Swarm-based forecasting models.Recent swarm intelligence algorithms employed includes the Grey Wolf Optimizer (GWO) and Artificial Bee Colony (ABC).Forecasting models are later developed to predict the daily spot price of crude oil and gasoline.Results showed that GWO works better with Z-score normalization technique while ABC produces better accuracy with the Min-Max.Nevertheless, the GWO is more superior than ABC as its model generates the highest accuracy for both crude oil and gasoline price.Such a result indicates that GWO is a promising competitor in the family of swarm intelligence algorithms.…”
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Investigating the Application of Artificial Intelligence for Earthquake Prediction in Terengganu
Published 2023text::Thesis -
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The normalized random map of gradient for generating multifocus image fusion
Published 2020“…Many researchers have developed many new and sophisticated methods. They show complicated computation and algorithm. …”
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Stroke-to-stroke matching in on-line signature verification
Published 2010“…Current methods make use of the DTW algorithm and its variant to segment them before comparing each of its data dimension. …”
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An improved recommender system based on normalization of matrix factorization and collaborative filtering algorithms
Published 2015“…The hypothesis is that the tendency of normalization technique to simplify the data combined with the accuracy of the neighborhood models can improve the accuracy of the RS. …”
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Talkout : Protecting mental health application with a lightweight message encryption
Published 2022“…The investigation of lightweight message encryption algorithms is conducted with systematic quantitative literature and experiment implementation in Java and Android running environment. …”
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