Search Results - (( developing net selection algorithm ) OR ( java application clustering algorithm ))
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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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Thesis -
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A Toolkit for Simulation of Desktop Grid Environment
Published 2014“…The prototypes will be developed using JAVA language united with a MySQL database. Core functionality of the simulator are job generation, volunteer generation, simulating algorithms, generating graphical charts and generating reports. …”
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Final Year Project -
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Robust variable selection methods for large- scale data in the presence of multicollinearity, autocorrelated errors and outliers
Published 2016“…We develop Robust Forward Selection algorithm based on RFCH correlation coefficient (RFS.RFCH) because FS.Winso is not robust to multivariate outliers. …”
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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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A web-based implementation of k-means algorithms
Published 2022“…Firstly, k-luster could incorporate additional clustering algorithms, or even classification algorithms in the future. …”
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Final Year Project / Dissertation / Thesis -
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Comparative analysis of Selective Clonal Mutation with conventional GA operators in solar tracking environment
Published 2023Conference Paper -
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Assessing the simulation performances of multiple model selection algorithm
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Algorithmic approaches in model selection of the air passengers flows data
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Sizing optimization of large-scale grid connected photovoltaic system using dolphin echolocation algorithm / Muhammad Zakyizzuddin Rosselan
Published 2018“…Apart from that, sizing algorithm with DEA was also discovered to outperform sizing algorithms with selected computational intelligence, i.e. …”
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Lexicon-based and immune system based learning methods in Twitter sentiment analysis
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Academic leadership bio-inspired classification model using negative selection algorithm
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Comparative Performance Analysis of Bat Algorithm and Bacterial Foraging Optimization Algorithm using Standard Benchmark Functions
Published 2014“…Over the last 30 years, many meta-heuristic algorithms have been developed in the literature including that of Simulated Annealing (SA), Genetic Algorithm (GA), Ant Colony Optimization (ACO), Particle Swarm Optimization (PSO), Harmony Search Algorithm (HS) to name a few. …”
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Development of intelligent evaluation system for product end-of-life selection strategy
Published 2011“…This problem can be best resolved by promoting end-of-life (EOL) selection strategies. The main objective of this research is to develop an evaluation system for selecting EOL strategy specifically for remanufacturing. …”
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Deep learning-based breast cancer detection and classification using histopathology images / Ghulam Murtaza
Published 2021“…For BrC detection, an efficient and reliable model namely Ensemble BrC Detection Network (EBrC-Net) and three misclassification reduction (McR) algorithms are developed. …”
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Techno-economic optimization and modelling of grid-connected photovoltaic and battery energy storage system
Published 2023“…Apart from that, the maximum demand supervisory control algorithm is developed via MATLAB Stateflow® for the battery management system (BMS) to monitor and regulate the load to maintain the net load consumption below MD limit with or without solar PV generation. …”
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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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