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1
A web-based implementation of k-means algorithms
Published 2022“…The K-means algorithm has been around for over a century. …”
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Final Year Project / Dissertation / Thesis -
2
Adaptive interference canceller using analog algorithm with offset voltage
Published 2015“…They require the utilization of the adaptive algorithms. Algorithms such as Least Mean Square (LMS), Normalized Least Mean Square (NLMS) and Recursive Least Square (RLS) algorithms often have poor numerical properties due to the practical implementation complexities. …”
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Thesis -
3
Segmentation of flair magnetic resonance brain images using K-Means Clustering algorithm / Nur Nabilah Abu Mangshor
Published 2010“…This project is about segmentation of FLAIR brain Magnetic Resonance Image (MRI) using K-Means Clustering algorithm. A prototype system of brain segmentation is developed by implementing K-Means Clustering algorithm. …”
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Thesis -
4
Image segmentation based on normalised cuts with clustering algorithm
Published 2013“…Evaluation of c -means and fuzzy c-means clustering algorithm with normalised cuts image segmentation on various kinds of images has been carried out. …”
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Thesis -
5
Implementation of Parallel K-Means Algorithm to Estimate Adhesion Failure in Warm Mix Asphalt
Published 2020“…The results showed that the PKIP algorithm decreases the execution time up to 30 to 46 if compared with the sequential k means algorithm when implemented using multiprocessing and distributed computing. …”
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Article -
6
IMPLEMENTATION OF NOISE CANCELLATION WITH HARDWARE DESCRIPTION LANGUAGE
Published 2006“…The project will focus on the implementation of adaptive filter with least-meansquares (LMS) algorithm or normalized least-mean-squares (NLMS) algorithm to cancel acoustic noises. …”
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Final Year Project -
7
Implementation of perez-dumortier calibration algorithm
Published 2014“…The governing theory of the algorithm was discussed in the previous chapter. This chapter presents information on how to implement the Perez-Dumotier calibration algorithm using actual field measurement. …”
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Chapter In Book -
8
loformation Retrieval - using Porter Stemming Algorithm
Published 2006“…By implementing the algorithm, it is expected from the application to retrieve only documents that relevant to the users query.…”
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Final Year Project -
9
Real time nonlinear filtered-x lms algorithm for active noise control
Published 2012“…The performance of these algorithms is usually compared with the standard linear filtered-x least mean square (FXLMS) algorithm. …”
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Thesis -
10
Extracting feature from images by using K-Means clustering algorithm / Abdul Hakim Zainal Abidin
Published 2016“…This research scope are to develop a computer application that can extract meaningful information in images by implement KMeans clustering algorithm 10 self capture facial image will be use as the research subject to test the algorithm that will extracting meaningful information of the person. …”
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Thesis -
11
A soft hierarchical algorithm for the clustering of multiple bioactive chemical compounds
Published 2007“…The results of the algorithm show significant improvement in comparison to a similar implementation of the hard c-means algorithm.…”
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Book Section -
12
Real time monitoring and controlling using Petri net algorithm for batch process plant / Mohamad Shaiful Osman
Published 2010“…Among the major benefits expected from the use of the algorithms are increasing the production, reducing cycle times, increasing yields and improved planning. …”
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Thesis -
13
Comparison of performance and computational complexity of nonlinear active noise control algorithms
Published 2011“…Several NANCs including Volterra filtered-x least mean square (VFXLMS), bilinear filtered-x least mean square (BFXLMS), and filtered-s least mean square (FSLMS) have been utilized to overcome these nonlinearities effects. …”
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Article -
14
Modeling and Analysis of New Hybrid Clustering Technique for Vehicular Ad Hoc Network
Published 2023“…The evaluation process was implemented on RK-Means, K-Means++, and OK-Means models. …”
Article -
15
Modeling of vehicle trajectory using K-means and fuzzy C-means clustering
Published 2019“…Hence, the clustering of vehicle trajectory dataset for similar patterns identification is implemented with k-means and fuzzy c-means (FCM) clustering algorithm. …”
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Proceedings -
16
Pattern Classification of Human Epithelial Images
Published 2016“…Last but not least, from the mean of properties, it will classify into the pattern after ranging the value of mean properties of each of the pattern itself that has been done in classification stage.…”
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Final Year Project -
17
Detection of the spread of Covid-19 in Indonesia using K-Means Clustering Algorithm / Mohammad Yazdi Pusadan ... [et al.]
Published 2023“…The purpose of this study is to apply the K-Means algorithm to perform clustering on COVID-19 data to determine the high spread of the virus in regions in Indonesia based on the frequency of the data. …”
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Book Section -
18
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 -
19
Evolution Performance of Symbolic Radial Basis Function Neural Network by Using Evolutionary Algorithms
Published 2023“…Each of these methods is presented in the steps in the flowchart form which can be used for its straightforward implementation in any programming language. With the use of SRBFNN-2SAT, a training method based on these algorithms has been presented, then training has been compared among algorithms, which were applied in Microsoft Visual C++ software using multiple metrics of performance, including Mean Absolute Relative Error (MARE), Root Mean Square Error (RMSE), Mean Absolute Percentage Error (MAPE), Mean Bias Error (MBE), Systematic Error (SD), Schwarz Bayesian Criterion (SBC), and Central Process Unit time (CPU time). …”
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Article -
20
A study of fluctuations and confidence of implementation in genetic algorithm optimized network in data centre
Published 2018“…Study of fluctuation in genetic algorithm has been a sub-objective in genetic algorithm implementations. …”
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