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A Comparative Study Of Fuzzy C-Means And K-Means Clustering Techniques
Published 2014“…Clustering analysis has been considered as a useful means for identifying patterns in dataset. The aim for this paper is to propose a comparison study between two well-known clustering algorithms namely fuzzy c-means (FCM) and k-means. …”
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Conference or Workshop Item -
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Direct approach for mining association rules from structured XML data
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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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Comparing means of two non-homogeneous normal populations
Published 1986“…The statistic is a funtion of the three M.L. estimates. A simple algorithm which can be implemented on a microcomputer is proposed for calculating the required values. …”
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Widely linear dynamic quaternion valued least mean square algorithm for linear filtering
Published 2017“…The new adaptive algorithm is called dynamic quaternion least mean square algorithm (DQLMS) because of the normalization process of the filter input and the variable step-size. …”
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Thesis -
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Efficient genetic partitioning-around-medoid algorithm for clustering
Published 2019“…These algorithms mostly built upon the partitioning k-means clustering algorithm. …”
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Thesis -
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Group formation using genetic algorithm
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Monograph -
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Network game (Literati) / Chung Mei Kuen
Published 2003“…The possible applications of multimedia-networked system are endless, as the demand to support interactive communication among groups of users has increased significantly. …”
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Thesis -
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ADAPTIVE LINEAR ALGORITHMS FOR POWER SYSTEM FUNDAMENTAL AND HARMONIC ESTIMATION
Published 2015“…On the other hand, Least Mean Square (LMS) algorithm is known for its ease of structure, computation and simplicity. …”
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Thesis -
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A proposed variable parameter control chart for monitoring the multivariate coefficient of variation
Published 2019“…Formulae and algorithms to optimize the various performance measures are discussed. …”
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Attribute reduction based scheduling algorithm with enhanced hybrid genetic algorithm and particle swarm optimization for optimal device selection
Published 2022“…The simulation is implemented with iFogSim and java programming language. The proposed method can be applied in smart cities, monitoring, health delivery, augmented reality, and gaming among others.…”
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Feedforward backpropagation, genetic algorithm approaches for predicting reference evapotranspiration
Published 2015“…The performance of both simulation models were evaluated using statistical coefficients such as the root of mean squared error (RMSE), mean absolute error (MAE) and coefficient of determination (R2). …”
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Maximum 2-satisfiability in radial basis function neural network
Published 2020“…MAX2SAT is a case of MAX-kSAT and is written in Conjunctive Normal Form (CNF) with two variables in each clause. This paper presents a new paradigm in using MAX2SAT by implementing in Radial Basis Function Neural Network (RBFNN). …”
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Automated QT interval measurement using modified Pan-Tompkins algorithm with independent isoelectric line approach
Published 2020“…The algorithm was implemented in Matlab and applied to the 60 seconds duration of 27 records in the PPUKM database with a sampling frequency of 500 Hz. …”
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Applying machine learning and particle swarm optimization for predictive modeling and cost optimization in construction project management
Published 2024“…Evaluation metrics such as Mean Squared Error, Root Mean Squared Error, Mean Absolute Error, and R-squared are commonly employed in the assessment of Machine Learning models' performance. …”
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