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Study and Implementation of Data Mining in Urban Gardening
Published 2019“…The system is essentially a three-part development, utilising Android, Java Servlets, and Arduino platforms to create an optimised and automated urban-gardening system. …”
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Improvement of land cover mapping using Sentinel 2 and Landsat 8 imageries via non-parametric classification
Published 2020“…The last phase involves developing a new fusion algorithm using SVM and Fuzzy K-Means Clustering (FKM) algorithms for Sentinel 2 data to enhance LCM accuracy. …”
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Autism Spectrum Disorder Classification Using Deep Learning
Published 2021“…The CNN algorithm produces better results with an accuracy of 97.07%, compared with the SVM algorithm. …”
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Comparative Analysis of Cervical Cell Classification Using Machine Learning Algorithms
Published 2026journal::journal article -
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Pathway-based analysis with Support Vector Machine (SVM-LASSO) for gene selection and classification
Published 2017“…Secondly, Support Vector Machine with Least Absolute Shrinkage and Selection Operator algorithm (SVM-LASSO) is proposed, which to find informative genes for each pathway to ensure efficient gene selection and classification in every pathway. …”
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Pathway-based analysis with support vector machine (SVM-LASSO) for gene selection and classification
Published 2017“…Secondly, Support Vector Machine with Least Absolute Shrinkage and Selection Operator algorithm (SVM-LASSO) is proposed, which to find informative genes for each pathway to ensure efficient gene selection and classification in every pathway. …”
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Web-based expert system for material selection of natural fiber- reinforced polymer composites
Published 2015“…Finally, the developed expert system was deployed over the internet with central interactive interface from the server as a web-based application. As Java is platform independent and easy to be deployed in web based application and accessible through the World Wide Web (www), this expert system can be one stop application for materials selection.…”
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Diabetic disease classifier based on three machine learning models / ‘Ayuni Zamri ... [et al.]
Published 2022“…Support Vector Machine (SVM), K-Nearest Neighbours (KNN) and Random Forest (RF) are implemented in this research. …”
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Semi-supervised learning for feature selection and classification of data / Ganesh Krishnasamy
Published 2019“…The proposed algorithm is compared with the state-of-the-art feature selection algorithms using three different datasets. …”
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Diabetes risk prediction system and data visualization / Azizah Mohamad Imran and Hawa Mohd Ekhsan
Published 2023“…To determine Diabetes, the prediction model used and compared different machine learning algorithms such as Logistic Regression (LR) and Support Vector Machine (SVM). …”
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Monitoring urban green space (UGS) changes by using high resolution aerial imagery: a case study of Kuala Lumpur, Malaysia
Published 2019“…The study had classified UGS by using the Support Vector Machine (SVM) algorithm. The training area was determined by visual interpretation and aided by a land use planning map as reference. …”
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Use of hybrid classification algorithm for land use and land cover analysis in data scarce environment
Published 2013“…In this study, vegetation indices, tasseled cap transformation, hybrid classification as a combination of k-means and support vector machine algorithms,and post-classification comparison were respectively implemented to detect and assess LULC in Halabja. …”
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Assessment of suitable hospital location using GIS and machine learning
Published 2022“…Fourth, five location-allocation models were implemented based on the calculus of coverage, mainly implemented in the search for poor coverage to propose new hospital sites in both study areas. …”
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A dataset for emotion recognition using virtual reality and EEG (DER-VREEG): Emotional state classification using low-cost wearable VR-EEG headsets
Published 2022“…This shows that using less electrode channels but with proper parameter tuning and selection features affects the performance of the classifications.…”
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