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Detection and classification of conflict flows in SDN using machine learning algorithms
Published 2021“…Moreover, applying machine learning algorithms in the identification and classification of conflicting flows has limitations. …”
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An optimized variant of machine learning algorithm for datadriven electrical energy efficiency management (D2EEM)
Published 2024“…This study recommends a selection trade-off as the function of prediction efficiency and efficacy of the algorithm. Particularly, the proposed optimized Bagged Trees are the most effective algorithm for energy demand prediction applications, and the proposed optimized Medium Trees are the most efficient algorithm for real-time systems. …”
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Decision tree-based approach for online management of PEM fuel cells for residential application
Published 2004“…In this research, a Decision Tree (DT) algorithm is employed to obtain the optimal, or quasioptimal, settings of the fuel cell online and in a general framework. …”
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Decision tree-based approach for online management of pem fuel cells for residential application
Published 2004“…In this research, a Decision Tree (DT) algorithm was employed to obtain the optimal, or quasi-optimal, settings of the fuel cell online and in a general framework. …”
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Cyberbullying detection: a machine learning approach
Published 2022“…The machine learning algorithm, Support Vector Machine was chosen after comparing it with other algorithms such as Multinomial Naïve Bayes, Decision Tree Classifier, and Random Forest Classifier. …”
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Final Year Project / Dissertation / Thesis -
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Driver behaviour classification: a research using OBD-II data and machine learning
Published 2024“…The relationship between all features and engine speed is analysed to select the optimal features, which include engine speed, vehicle speed, throttle position, and calculated engine load. Then, the proposed model makes use of the K-Means algorithm to create driving behaviour labels whether belong to safe or aggressive - validated by the safety score criteria. …”
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Ganoderma boninense classification based on near-infrared spectral data using machine learning techniques
Published 2022“…A PLS regression is used on NIR spectra to implement the prediction of ergosterol concentration which shows good corelation of R = 0.861 between the ergosterol concentration and oil palm NIR spectra. Four different ML algorithms are tested for prediction of G. boninense infection: K-Nearest Neighbour (kNN), Naïve Bayes (NB), Support Vector Machine (SVM) and Decision Tree (DT) are tested which depicted DT algorithm achieves a satisfactory overall performance with high accuracy up to 93.1% and F1-score of 92.6% compared to other algorithms. …”
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Finding the root of nonlinear function using five bracketing method / Nur Afiqah Mohamed Azhar
Published 2019“…Therefore, numerical method in the form of bracketing method is often used to find only the approximate root of the function. …”
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Gravitational search – bat algorithm for solving single and bi-objective of non-linear functions
Published 2018“…The second technique is to solve bi-objective functions by using the BOBAT algorithm. The third technique is an integration of BOGSA with BOBAT to produce a BOGSBAT algorithm. …”
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10
Determining the preprocessing clustering algorithm in radial basis function neural network
Published 2008“…Three types of method used in this study to find the centres include random selections, K-means clustering algorithm and also K-median clustering algorithm. …”
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Genetic Algorithms In Optimizing Membership Function For Fuzzy Logic Controller
Published 2010“…Thus it is important to select the accurate membership functions but these methods possess one common weakness where conventional FLC use membership function and control rules generated by human operator. …”
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The efficiency of conjugate gradient methods with global convergence / Siti Nur Hafiza Shamsudin
Published 2019“…The global convergence result is established using exact line searches. Numerical result shows that algorithm 2 which is one of the proposed CG methods is more efficiency when compared to other algorithms.…”
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Statistical data preprocessing methods in distance functions to enhance k-means clustering algorithm
Published 2018“…It shows that the IQR-HEOM method is more efficient to rectify the problem caused by using range in HEOM. …”
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Fuzzy modeling using Bat Algorithm optimization for classification
Published 2018“…As a result, the highest average accuracy generated which is 96.91% by using WBCD dataset. The average accuracy of Bat Algorithm is comparing with other methods. …”
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Undergraduates Project Papers -
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Improved stochastic gradient descent algorithm with mean-gradient adaptive stepsize for solving large-scale optimization problems
Published 2023“…This paper proposes a new SGD algorithm with modified stepsize that employs function scaling strategy. …”
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Evolution Performance of Symbolic Radial Basis Function Neural Network by Using Evolutionary Algorithms
Published 2023“…The SRBFNN’s objective function that corresponds to Satisfiability logic programming can be minimized by different algorithms, including Genetic Algorithm (GA), Evolution Strategy Algorithm (ES), Differential Evolution Algorithm (DE), and Evolutionary Programming Algorithm (EP). …”
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The fusion of particle swarm optimization (PSO) and interior point method (IPM) as cooperative movement control algorithm in Swarm Robotics / Dada Emmanuel Gbenga
Published 2016“…Secondly, we compared the performance of our new algorithm pdAPSO with APSO, and PSO using 7 benchmark functions. …”
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Comparative study of secant, Fixed point and Sixth section methods for solving root in nonlinear equation / Nik Syahrul Naim Abdul Rahman
Published 2017“…Numerical analysis is to solve the functions for finding root by using a few numerical methods such as Secant, Fixed point and Sixth section methods to solve the functions for finding root. …”
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