Search Results - (( using data method algorithm ) OR ( waste detection method algorithm ))
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An Embedded Machine Learning-Based Spoiled Leftover Food Detection Device for Multiclass Classification
Published 2024“…In conclusion, the work demonstrates a novel method for using machine learning algorithms to classify, identify, and predict the contamination level of leftover cooked food, contributing to reducing food waste generated primarily by Malaysians…”
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RGB and RGNIR image dataset for machine learning in plastic waste detection
Published 2025“…Machine learning has emerged as a potential solution for plastic waste due to its ability to analyse and interpret large volumes of data using algorithms. …”
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A stacked ensemble deep learning model for water quality prediction / Wong Wen Yee
Published 2023“…The proposed deep learning model renders faster without the use of SMOTE. Any resampling algorithm is not a necessity in the case of this proposed algorithm. …”
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Evaluation of diagnostic performance of rK28 ELISA using urine for diagnosis of visceral leishmaniasis
Published 2016“…Again, the overall specificity was > 96 %. Conclusions: Our data indicate the potential for using urine in the diagnosis of VL. …”
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Fault detection and diagnosis for gas density monitoring using multivariate statistical process control
Published 2011“…Therefore, an efficient fault detection and diagnosis algorithm needs to be developed to detect faults that are present in a process and pinpoint the cause of these detected faults. …”
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PCB defect detection system using run-length encoding
Published 2017“…The secondary objective is to design run-length encoding algorithm able to detect and classify the defect of printed circuit board (PCB). …”
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Snort-based smart and swift intrusion detection system
Published 2018“…Methods/Statistical Analysis: The features are extracted using back-propagation algorithm. …”
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Attribute related methods for improvement of ID3 Algorithm in classification of data: A review
Published 2020“…There are several learning algorithms to implement the decision tree but the most commonly-used is ID3 algorithm. …”
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Clustering Spatial Data Using a Kernel-Based Algorithm
Published 2005“…Therefore, this work comes up with new clustering algorithm using kernel-based methods for effective and efficient data analysis by exploring structures in the data.…”
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Improving the tool for analyzing Malaysia’s demographic change: data standardization analysis to form geo-demographics classification profiles using k-means algorithms
Published 2016“…Clustering is one of the important methods in data exploratory in this era because it is widely applied in data mining.Clustering of data is necessary to produce geo-demographic classification where k-means algorithm is used as cluster algorithm. …”
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An Enhanced Hybrid Method Using AES Algorithm And Arabic Text Steganography
Published 2024thesis::master thesis -
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Solving economic load dispatch problem using genetic algorithm method / Norliza Kamarulzaman
Published 2009“…In this study, Genetic Algorithm method is used to overcome this problem. …”
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MuDi-Stream: A multi density clustering algorithm for evolving data stream
Published 2016“…The grid-based method is used as an outlier buffer to handle both noises and multi-density data and yet is used to reduce the merging time of clustering. …”
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Case Slicing Technique for Feature Selection
Published 2004“…Since the 1960s, many algorithms for data classification have been proposed. …”
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Fuzzy clustering method and evaluation based on multi criteria decision making technique
Published 2018“…The proposed algorithm is used as a pre-processing method for data followed by Gustafson-Kessel (GK) algorithm to classify credit scoring data. …”
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An adaptive density-based method for clustering evolving data streams / Amineh Amini
Published 2014“…This study proposes a density-based algorithm for clustering evolving data streams. The proposed method, which is called MuDi-Stream (Multi Density clustering algorithm for evolving data Stream), is an online-offline algorithm with four main components. …”
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Improved clustering using robust and classical principal component
Published 2017“…We call our propose method as k-means by principal components (pc1). In this study, the kernels that are created by using the k-means method are replaced with kernels which are created by using PCA method where the PCA method reduces the dimensionality of a data. …”
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