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Study Of Modified Training Algorithm For Optimized Convergence Speed Of Neural Network
Published 2016“…First proposed algorithm is the combination of momentum algorithm with adaptive learning rate (ALR) algorithm, and second proposed algorithm is the combination of momentum algorithm with automatic learning rate selection (ALRS) algorithm. …”
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2
Lettuce Leaf Disease Detection Using Convolutional Neural Network Algorithm
Published 2023“…The trained CNN model will then implement using OpenCV for real-time operation and Python language for the programming.…”
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Final Year Project Report / IMRAD -
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An evaluation of Monte Carlo-based hyper-heuristic for interaction testing of industrial embedded software applications.
Published 2020“…Addressing this issue, we propose to integrate the memory into EMCQ for combinatorial t-wise test suite generation using reinforcement learning based on the Q-learning mechanism, called Q-EMCQ. …”
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Path Following Using A Learning Neural Network
Published 2004“…To conduct the specified works, the MATLAB programs written by [2] have been extended and modified.…”
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Final Year Project -
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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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6
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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7
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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8
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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9
An ensemble of neural network and modified grey wolf optimizer for stock prediction
Published 2019“…The research implements stock prediction analysis as a case study for training the neural network by adopting MGWO algorithm. …”
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10
Implementation of Autonomous Vehicle Navigation Algorithms Using Event-Driven Programming
Published 2012“…The algorithm can be relatively easy translated to a suitable program with event-driven programming technique. …”
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Conference or Workshop Item -
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Implementation of autonomous vehicle navigation algorithms using event-driven programming
Published 2012“…The algorithm can be relatively easy translated to a suitable program with event-driven programming technique. …”
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Modeling the properties of terminal blend crumb rubber modified bitumen with crosslinking additives
Published 2025“…This study aimed to develop models assessing 26 machine-learning algorithms in regression analysis to predict the properties of terminal blend crumb rubber-modified bitumen (TB-CRMB) made with crosslinking additives. …”
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Evaluation of the effectiveness and efficiency of Wagner and Fischer algorithm in retrieving Hadith translated documents / Kamarul Arifin Muhamad
Published 2002“…The method has been implemented as a C programming language. In this study, Wagner and Fischer algorithm, Hadith test collection that consists of Malay Hadith translation documents, query words and relevant judgements are used. …”
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14
An application of teaching–learning-based optimization for solving the optimal power flow problem with stochastic wind and solar power generators
Published 2023“…This paper proposes the implementation of metaheuristic algorithm namely, teaching–learning-based optimization (TLBO) algorithm to solve optimal power flow (OPF) problem. …”
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15
A Modified Particle Swarm Optimization for Efficient Maximum Power Point Tracking Under Partial Shading Condition
Published 2024“…A modified initialization scheme that leverages grid partitioning and oppositional-based learning is incorporated to produce an evenly distributed initial population across P-V curve. …”
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Simulation of shortest path using a-star algorithm / Nurul Hani Nortaja
Published 2004“…The steps to calculate a shortest path using A • algorithm is shown by using appropriate examples and related figures. …”
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18
Optimal placement and sizing of FACTS devices for optimal power flow using metaheuristic optimizers
Published 2022“…These algorithms are selected from the different metaheuristics classification groups, where the implementation of these algorithms into the said problems will be tested on the modified IEEE 14-bus system. …”
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Identification of continuous-time model of hammerstein system using modified multi-verse optimizer
Published 2021“…his thesis implements a novel nature-inspired metaheuristic optimization algorithm, namely the modified Multi-Verse Optimizer (mMVO) algorithm, to identify the continuous-time model of Hammerstein system. …”
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Implementation of Color Filtering on FPGA
Published 2007“…Verilog HDL is chosen as the hardware programming language for this system and its compiled using Quartus II program. …”
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