Search Results - (( variable implementation tree 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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A comparison of support vector machine and decision tree classifications using satellite data of Langkawi Island
Published 2009“…Two classifiers were used to classify SPOT 5 satellite image; Decision Tree (DT) and Support Vector Machine (SVM). The Decision Tree rules were developed manually based on Normalized Difference Vegetation Index (NDVI) and Brightness Value (BV) variables. …”
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Determination of tree stem volume : A case study of Cinnamomum
Published 2013“…Illustrations and algorithms are incorporated into the procedures. Non-normal and nonlinear data variables are addressed, hence data characterization is presented. …”
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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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Conference or Workshop Item -
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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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Lightning fault classification for transmission line using support vector machine
Published 2023“…The most prevalent cause of faults in the power system is lightning strikes, while other causes may include insulator failure, tree or crane encroachment. In this study, two machine learning algorithms, Support Vector Machine (SVM) and k-Nearest Neighbor (kNN), were used and compared to classify faults due to lightning strikes, insulator failure, tree and crane encroachment. …”
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Conference or Workshop Item -
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Lightning Fault Classification for Transmission Line Using Support Vector Machine
Published 2024“…The most prevalent cause of faults in the power system is lightning strikes, while other causes may include insulator failure, tree or crane encroachment. In this study, two machine learning algorithms, Support Vector Machine (SVM) and k-Nearest Neighbor (kNN), were used and compared to classify faults due to lightning strikes, insulator failure, tree and crane encroachment. …”
Conference Paper -
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Green building valuation based on machine learning algorithms / Thuraiya Mohd ... [et al.]
Published 2021“…This experiment used five common machine learning algorithms namely 1) Linear Regressor, 2) Decision Tree Regressor, 3) Random Forest Regressor, 4) Ridge Regressor and 5) Lasso Regressor tested on a real estate data-set of covering Kuala Lumpur District, Malaysia. 3 set of experiments was conducted based on the different feature selections and purposes The results show that the implementation of 16 variables based on Experiment 2 has given a promising effect on the model compare the other experiment, and the Random Forest Regressor by using the Split approach for training and validating data-set outperformed other algorithms compared to Cross-Validation approach. …”
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Improved random forest for feature selection in writer identification
Published 2015“…It involved Classification and Regression Tree (CART) during the development of tree. Important features are measured by using Variable Importance (VI). …”
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Thesis -
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Recommendation System Model For Decision Making in the E-Commerce Application
Published 2024thesis::doctoral thesis -
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Gene Selection For Cancer Classification Based On Xgboost Classifier
Published 2022“…XGBoost Classifier is applied in this research, which it is an efficient open-source implementation of the gradient boosted trees algorithm. …”
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Undergraduates Project Papers -
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Detection of phishing websites using machine learning approaches
Published 2021“…The dataset consists of 11,055 observations and 32 variables. Three supervised learning models are implemented in this study: Decision Tree, K-Nearest Neighbour (KNN), and Random Forest. …”
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Proceedings -
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Classification of water quality using artificial neural network
Published 2020“…In addition, it is more flexible than existing approaches and can be implemented easily and quickly.…”
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Predictive Modelling of Stroke Occurrence among Patients using Machine Learning
Published 2023“…Advanced machine learning algorithms, including logistic regression, decision trees, random forests, and support vector machines, were utilized to analyses the dataset and develop a predictive model. …”
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Article -
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Applying machine learning and particle swarm optimization for predictive modeling and cost optimization in construction project management
Published 2024“…The Voting regression, which leverages the collective predictive power of multiple models, exhibits superior performance in comparison to individual algorithms. Feature selection methods play a crucial role in identifying the variables that have a significant impact on project costs. …”
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The future of social entrepreneurship: modelling and predicting social impact
Published 2021“…Design/methodology/approach: This study implemented an experimental method using three different algorithms: naive Bayes, k-nearest neighbor and J48 decision tree algorithms to develop and test the social impact prediction model. …”
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