Search Results - (( java data classification algorithm ) OR ( using iterative learning algorithm ))
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Fuzzy modeling using Bat Algorithm optimization for classification
Published 2018“…A Sazonov Engine which is a fuzzy java engine is use to apply Bat Algorithm in the experiment. …”
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Undergraduates Project Papers -
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Active force control with iterative learning control algorithm for a vehicle suspension
Published 2013“…The new control scheme named active force control with iterative learning control algorithm (AFCIL) is complemented by the classic proportionalintegral-derivative (PID) control incorporated and designed as the outermost control loop. …”
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Classification System for Heart Disease Using Bayesian Classifier
Published 2007“…This system was developing base on to three main part which is data processing, testing and implementation of the algorithm. …”
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Intelligent adaptive active force control of a robotic arm with embedded iterative learning algorithms
Published 2001“…Two main iterative learning algorithms are utilized in the study – the first is used to automatically tune the controller gains while the second to estimate the inertia matrix of the manipulator. …”
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Adaptive active force control of a robotic arm employing twin iterative learning algorithms / Musa Mailah and Ong Miaw Yong
Published 2004“…Two iterative learning algorithms are employed in the study - the first is used to tune automatically the controller gains while the second to estimate the inertia matrix of the robotic arm. …”
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Intelligent active force control of a rigid robot arm using embedded iterative learning algorithm
Published 2000“…The paper presents a novel approach to estimating the inertia matrix of a robot arm adaptively and on-line using an iterative learning algorithm. It is employed in conjunction with an active force control strategy which has been shown to be very effective in accommodating the disturbances. …”
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An ensemble learning method for spam email detection system based on metaheuristic algorithms
Published 2015“…Major problems in classification task are large amount of training data, large number of features and different behavior of data streams that reduce accuracy and increase computational cost in classifier training phase. …”
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Adoption of machine learning algorithm for analysing supporters and non supporters feedback on political posts / Ogunfolajin Maruff Tunde
Published 2022“…This thesis is based on the application of sentiment classification algorithm to tweet data with the goal of classifying messages based on the polarity of sentiment towards a particular topic (or subject matter). …”
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Active Suspension System for Passenger Vehicle using Active Force Control with Iterative Learning Algorithm
Published 2014“…The paper describes the practical implementation of a new hybrid control method to a vehicle suspension system using Active Force Control (AFC) with Iterative Learning (IL) and proportional-integralderivative (PID) control strategy. …”
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Optimising neural network training efficiency through spectral parameter-based multiple adaptive learning rates
Published 2024“…The process of training neural networks heavily involves solving optimization problems. Most optimization algorithms use a !xed learning rate or a simpli!ed adaptive updating scheme in every iteration. …”
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Conference or Workshop Item -
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Max-D clustering K-means algorithm for Autogeneration of Centroids and Distance of Data Points Cluster
“…K-Means is one of the unsupervised learning and partitioning clustering algorithms. It is very popular and widely used for its simplicity and fastness. …”
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Enhancement of network security by use machine learning
Published 2019“…This research is about the design and simulation on enhancement network security using machine learning. The design use MATLAB coding to show the simulation. …”
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MaxD K-Means: A clustering algorithm for auto-generation of centroids and distance of data points in clusters
Published 2012“…K-Means is one of the unsupervised learning and partitioning clustering algorithms. It is very popular and widely used for its simplicity and fastness. …”
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A web-based implementation of k-means algorithms
Published 2022“…Firstly, k-luster could incorporate additional clustering algorithms, or even classification algorithms in the future. …”
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Final Year Project / Dissertation / Thesis -
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Comparative analysis of three approaches of antecedent part generation for an IT2 TSK FLS
Published 2017“…Since extreme learning machine is a non-iterative estimation procedure, it is faster than gradient-based algorithms which are iterative. …”
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Kelantan daily water level prediction model using hybrid deep-learning algorithm for flood forecasting
Published 2021“…Therefore, this present study had imputed the missing hydrological data using five imputation methods, namely Neural Network (NN), Moving Median (MM), Iterative Algorithm (IA), Nonlinear Iterative Partial Least Square (NIPALS), and Combined Correlation with Inversed Distance (CCID) imputation methods. …”
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Thesis