Search Results - (( java implementation learning algorithm ) OR ( using co optimization algorithm ))
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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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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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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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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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Modeling the impacts of constant price GDP and population on CO2 emissions using Cobb-Douglas model and ant colony optimization algorithm
Published 2019“…Modeling is done by using Cobb-Douglas model production function, where parameter estimation is done by using ant colony optimization algorithm. …”
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Resource allocation in coordinated multipoint long term evolution-advanced networks
Published 2015“…ORA is formulated based on Lagrangian method and optimized using Particle Swarm Optimization (PSO). …”
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A hybrid numerical approach for multi-responses optimization of process parameters and catalyst compositions in CO2 OCM process over CaO-MnO/CeO2 catalyst
Published 2005“…A new hybrid numerical approach, using Weighted Sum of Squared Objective Functions (WSSOF) algorithm, was developed for multi-responses optimization of carbon dioxide oxidative coupling of methane (CO2 OCM). …”
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A Preliminary Study of Wood Species Classifacation System Based on Wood Knot Texture Using K-Nearest Neighbour With Optimized Features From Binary Magnetic Optimization Algorithm S...
Published 2013“…The features of the wood knot images are extracted using Gray Level Co-Occurrence Matrix. Binary Magnetic Optimization Algorithm is use to optimize the feature selection process. …”
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Optimization of Prediction Error in CO2 Laser Cutting process by Taguchi Artificial Neural Network Hybrid with Genetic algorithm
Published 2013“…The potential of genetic algorithm in optimization was utilized in the proposed hybrid model to minimize the error prediction for regions of cutting conditions away from the Taguchi based factor level points. …”
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A Hybrid Neural Network-Based Improved PSO Algorithm for Gas Turbine Emissions Prediction
Published 2025“…The model achieves the lowest MSE, MAE, and RMSE values for CO and NOx emissions. Overall, the hybrid model achieves high prediction accuracy, particularly with optimized PSO parameter selection using seed random generators. ? …”
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Forecasting of energy-related carbon dioxide emission using ANN combined with hybrid metaheuristic optimization algorithms
Published 2025“…Multilayer perceptrons (MLP) are combined with various nature-inspired optimization algorithms, such as Heap-Based Optimizer (HBO), Teaching-Learning-Based Optimization (TLBO), Whale Optimization Algorithm (WOA), Vortex Search algorithm (VS), and Earthworm Optimization Algorithm (EWA), to create a dependable predictive network that takes the complexity of the problem into account. …”
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Enhancing CI engine performance and emission control using a hybrid RSM–Rao algorithm for ZnO-doped castor–neem biodiesel blends
Published 2025“…RSM was used to plan the design of the experiment and detect the optimal engine conditions for enhancing PI and reducing EAs while 3 algorithms were used to solve a multi-objective function. …”
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Optimization of food waste to sewage sludge ratio for anaerobic co-digestion process using Artificial Neural Network (ANN) and Genetic Algorithm (GA)
Published 2021“…This is because of the abundance of food waste in landfills has contributed to the emission of greenhouse gas (GHG). Therefore, by using anaerobic co-digestion technology, food waste (FW) can be used as a substrate with sewage sludge (SS) to produce a valuable product such as methane gas. …”
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Multi-objective optimization of stand-alone hybrid renewable energy system by genetic algorithm
Published 2013“…HOGA, as a new effective tool for multi-objective optimization by evolutionary algorithm is used in this research. …”
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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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Prediction of CO2 emission for the central European countries through five metaheuristic optimization techniques helping multilayer perceptron
Published 2025“…The GDP of the Central European countries (from 1990 to 2016) based on several energy sources, such as coal, oil, natural gas, and renewable energy, are used as inputs in this study. To develop a reliable predictive network considering the problem complexity, multilayer perceptron (MLP) is combined with several nature-inspired optimization algorithms, namely, black hole algorithm (BHA), future search algorithm (FSA), backtracking search algorithm (BSA), biogeography-based optimization (BBO), and shuffled complex evolution (SCE). …”
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Compressed Sensing Implementations For Sparse Channel Estimation In OFDM Systems
Published 2018“…By using the restricted isometry property, the theoretical analysis of both CoFA and SdMP algorithms and the sufficient conditions for realizing an improved reconstruction performance were presented. …”
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