Search Results - (( program implementation developing algorithm ) OR ( learning implementation colony algorithm ))
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Binary ant colony optimization algorithm in learning random satisfiability logic for discrete hopfield neural network
Published 2024“…This study introduced a novel ant colony optimization algorithm that implements the population selection strategy of the Estimation of Distribution Algorithm and a new pheromone updating formula. …”
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2
A conceptual multi-agent framework using ant colony optimization and fuzzy algorithms for learning style detection
Published 2023“…The multi-agent system applies ant colony optimization and fuzzy logic search algorithms as tools to detecting learning styles. …”
Conference Paper -
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Predicting breast cancer using ant colony optimisation / Siti Sarah Aqilah Che Ani
Published 2021“…Hence, the main purpose of this study is to develop a model of classification for breast cancer cell prediction. This study implements a machine learning algorithm called Ant Colony Optimization (ACO) algorithm to develop an accurate classification model for predicting breast cancer cells. …”
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Student Project -
4
An approach to improve functional link neural network training using modified artificial bee colony for classification task
Published 2013“…The standard method for tuning the weight in FLNN is using a Backpropagation (BP) learning algorithm. Still, BP-learning algorithm has difficulties such as trapping in local optima and slow convergence especially for solving non-linearly separable classification problems. …”
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5
An approach to improve functional link neural network training using modified artificial bee colony for classification task
Published 2012“…The standard method for tuning the weight in FLNN is using a Backpropagation (BP) learning algorithm. Still, BP-learning algorithm has difficulties such as trapping in local optima and slow convergence especially for solving non-linearly separable classification problems. …”
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6
An approach to improve functional link neural network training using modified artificial bee colony for classification task
Published 2012“…The standard method for tuning the weight in FLNN is using a Backpropagation (BP) learning algorithm. Still, BP-learning algorithm has difficulties such as trapping in local optima and slow convergence especially for solving non-linearly separable classification problems. …”
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7
Functional link neural network with modified bee-firefly learning algorithm for classification task
Published 2016“…This work proposed the implementation of modified Artificial Bee Colony with Firefly algorithm for training the FLNN network to overcome the drawback of BP-learning algorithm. …”
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Thesis -
8
Implementation of Autonomous Vehicle Navigation Algorithms Using Event-Driven Programming
Published 2012“…By using FSM to describe the behaviour of a navigating mobile robot, an equivalent algorithm can be developed. The algorithm can be relatively easy translated to a suitable program with event-driven programming technique. …”
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Conference or Workshop Item -
9
Implementation of autonomous vehicle navigation algorithms using event-driven programming
Published 2012“…By using FSM to describe the behaviour of a navigating mobile robot, an equivalent algorithm can be developed. The algorithm can be relatively easy translated to a suitable program with event-driven programming technique. …”
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10
Implementation of Color Filtering on FPGA
Published 2007“…The functionality of the algorithm is first verified in Matlab, simulating the expected output of the system before implementing it onto the FPGA development board. …”
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11
Simulation of shortest path using a-star algorithm / Nurul Hani Nortaja
Published 2004“…As for WXES3l82, the thesis cover the development of programming code, the code implementation and testing and the evaluation including discussion about the problem/constraints meed in the coding program development. …”
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Thesis -
12
Development of dynamic programming algorithm for maintenance scheduling problem
Published 2020“…Then, the data of the maintenance team from one of the utilities provider company in Malaysia was collected to be implemented in the development of a dynamic programming algorithm. …”
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13
Development of DNA fragment assembly using idury-waterman algorithm / Nurul Azyanny Mustaffa
Published 2013“…It is to shows whether the program implemented satisfied the Idury-Waterman algorithm or not. …”
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Student Project -
14
Development of a cost efficient vision system for defects detection / Muhammad Zarif Kamarudin
Published 2010“…In this project, MATLAB platform is used to program the entire algorithm furthermore implementing Graphical User Interface to communicate between the vision system and the user. …”
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Monograph -
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A new teaching learning artificial bee colony based maximum power point tracking approach for assessing various parameters of photovoltaic system under different atmospheric condit...
Published 2024“…In addition, to enhance the performance teaching learning-based artificial bee colony (TLABC) method has been used at distinct weather conditions. …”
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Thesis -
17
Evaluation of the effectiveness and efficiency of Wagner and Fischer algorithm in retrieving Hadith translated documents / Kamarul Arifin Muhamad
Published 2002“…Second experiment uses dynamic programmings apply with Wagner and Fischer algorithm.…”
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Thesis -
18
Controller And Circuitry Design And Implementation For Fire Fighting Robot For MIROC 2014 Competition
Published 2014“…This algorithm is designed using an iterative design model, whereby the program is continually tested and improved. …”
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Final Year Project -
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Implementation of color filtering on FPGA
Published 2007“…The functionality of the algorithm is first verified in Matlab, simulating the expected output of the system before implementing it onto the FPGA development board. …”
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Conference or Workshop Item -
20
An improved teaching-learning-based optimization for extreme learning machine in floating photovoltaic power forecasting
Published 2025“…The proposed method achieved superior forecasting accuracy compared to benchmark algorithms including standard teaching-learning-based optimization with extreme learning machine, manta rays foraging optimization with extreme learning machine, moth flame optimization with extreme learning machine, ant colony optimization with extreme learning machine and salp swarm algorithm with extreme learning machine. …”
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