Search Results - (( based deviation selection algorithm ) OR ( java implementation learning algorithm ))
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1
Plagiarism Detection System for Java Programming Assignments by Using Greedy String-Tilling Algorithm
Published 2008“…The prototype system, known as Java Plagiarism Detection System (JPDS) implements the Greedy-String-Tiling algorithm to detect similarities among tokens in a Java source code files. …”
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2
An Educational Tool Aimed at Learning Metaheuristics
Published 2020“…Implemented with Java, this tool provides a friendly GUI for setting the parameters and display the result from where the learner can see how the selected algorithm converges for a particular problem solution. …”
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3
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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4
A Feature Ranking Algorithm in Pragmatic Quality Factor Model for Software Quality Assessment
Published 2013“…The methodology used consists of theoretical study, design of formal framework on intelligent software quality, identification of Feature Ranking Technique (FRT), construction and evaluation of FRA algorithm. 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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5
Dynamic Robust Bootstrap Algorithm for Linear Model Selection Using Least Trimmed Squares
Published 2009“…To rectify this problem, we propose a Dynamic Robust Bootstrap-LTS based (DRBLTS) algorithm where the percentage of outliers in each bootstrap sample is detected. …”
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6
Feature extraction and selection algorithm based on self adaptive ant colony system for sky image classification
Published 2023“…The ant colony optimisation (ACO) algorithm have been used to select feature subset. …”
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7
Fault diagnostic algorithm for precut fractionation column
Published 2004“…The fault diagnostic algorithm is supported by the process history based method and developed by using Borland C++ Builder 6.0. …”
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8
Development of a rule-based fault diagnostic advisory system for precut fractionation column
Published 2005“…The advisory system algorithm used process history based method and presented by rule-based approach. …”
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9
Web-based clustering tool using fuzzy k-mean algorithm / Ahmad Zuladzlan Zulkifly
Published 2019“…This project will use fuzzy k-means clustering algorithm to cluster the data because it is easy to implement and have many advantages. …”
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10
Optimal input features selection of wavelet-based EEG signals using GA
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11
An Evolutionary Algorithm: An Enhancement of Binary Tournament Selection for Fish Feed Formulation
Published 2022“…*e novelty of the proposed SD tournament selection is compared with BT selection in terms of searching for an efficient but not myopic algorithm. …”
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12
Fault diagnostic advisory system using moving-range chart and hazard operability study.
Published 2007“…Moving-Range (x-MR) Chart and (HAZOP) study were used to define the causes and consequences of process deviation based on selected parameter for each study node. …”
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POTENTIAL GROUPER FEED FORMULATION BASED ON EVOLUTIONARY ALGORITHM CONCEPT WITH A UNIQUE SELECTION OPERATOR
Published 2018“…Hence, in this study, an EA-based approach with a refinement on using the standard deviation in the strategy of tournament selection has been proposed to minimize the total cost in formulating the feed of grouper fish. …”
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14
Penalized LAD-SCAD estimator based on robust wrapped correlation screening method for high dimensional models
Published 2021“…The SIS method uses the rank correlation screening (RCS) algorithm in the pre-screening step and the traditional Pathwise coordinate descent algorithm for computing the sequence of the regularization parameters in the post screening step for onward model selection. …”
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15
Efficient Time-Varying q-Parameter Design for q-Incremental Least Mean Square Algorithm with Noisy Links
Published 2022“…Motivated by this fact, a quantum calculus-based noisy links incremental least mean squares (NL-qILMS) algorithm is proposed. …”
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16
Neural Network Model and Finite Element Simulation of Spring back in Plane-Strain Metallic Beam Bending
Published 2006“…To validate the finite element model physical experiments were conducted. A neural network algorithm based on the backpropagation algorithm has been developed. …”
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17
Features selection for intrusion detection system using hybridize PSO-SVM
Published 2016“…Hybridize Particle Swarm Optimization (PSO) as a searching algorithm and support vector machine (SVM) as a classifier had been implemented to cope with this problem. …”
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18
Fault diagnostic advisory system using moving-range chart and hazard operability study
Published 2007“…Moving-Range (x-MR) Chart and HAZOP study were used to define the causes and consequences of process deviation based on selected parameter for each study node. …”
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19
Potential grouper feed formulation based on evolutionary algorithm concept with a unique selection operator
Published 2018“…However, the issue is on its cost while providing quality feed mix.That leads to the search for an approach which could provide the most suitable feed ingredients and nutrients.One potential approach is the Evolutionary Algorithm (EA) which has been used to solve the feed formulation problems in poultry, shrimp and cattle.Hence, in this study, an EA-based approach with a refinement on using the standard deviation in the strategy of tournament selection has been proposed to minimize the total cost in formulating the feed of grouper fish.Results show that the lowest cost can be accepted while satisfying the nutrient requirements of grouper fish.…”
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20
An enhancement of classification technique based on rough set theory for intrusion detection system application
Published 2019“…In order to improve classification performance problem, feature selection and discretization algorithm are crucial in selecting relevant attributes that could improve classification performance. …”
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