Search Results - (( based encryption learning algorithm ) OR ( simulation optimization method algorithm ))
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A new hybrid deep neural networks (DNN) algorithm for Lorenz chaotic system parameter estimation in image encryption
Published 2023“…Then, this study aims to optimize the hyperparameters of the developed DNN model using the Arithmetic Optimization Algorithm (AOA) and, lastly, to evaluate the performance of the newly proposed deep learning model with Simulated Kalman Filter (SKF) algorithm in solving image encryption application. …”
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RENTAKA: A novel machine learning framework for crypto-ransomware pre-encryption detection
Published 2022“…This study proposed a pre-encryption detection framework for crypto-ransomware using a machine learning approach. …”
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A Machine Learning Classification Approach To Detect Tls-Based Malware Using Entropy-Based Flow Set Features
Published 2022“…The difficulty and impracticality of decrypting TLS network traffic before it reaches the Intrusion Detection System (IDS) has driven numerous research studies to focus on anomaly-based malware detection without decryption employing various features and Machine Learning (ML) algorithms. …”
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5
Optimization of turning parameters using genetic algorithm method
Published 2008“…The simulation based on Genetic Algorithm are successful develop and the optimum parameters values are obtained from the simulation.…”
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Undergraduates Project Papers -
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Hybrid firefly and particle swarm optimization algorithm for multi-objective optimal power flow with distributed generation
Published 2022“…This thesis proposes and simulates the three novel optimization algorithms to handle DG allocation, different single-objective, and multi-objective OPF problems. …”
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A discrete simulated kalman filter optimizer for combinatorial optimization problems
Published 2022“…An example of a numerical algorithm is the simulated Kalman filter (SKF). Various method has been introduced as an extension of a numerical algorithm to adapt it to a discrete search space. …”
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Route optimization using shortest path method / Muhamad Faisal Amin Shakri
Published 2025“…Therefore, the effectiveness of route planning is very essential. The method to study route optimization is called shortest path method. …”
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Exploring a Q-learning-based chaotic naked mole rat algorithm for S-box construction and optimization
Published 2023“…This paper introduces a new variant of the metaheuristic algorithm based on the naked mole rat (NMR) algorithm, called the Q-learning naked mole rat algorithm (QL-NMR), for substitution box construction and optimization. …”
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Improved particle swarm optimization by fast annealing algorithm
Published 2019“…We also apply the algorithm in clustering problem, and the results shows that the proposed method has better accuracy than the optimization methods.…”
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Proceeding Paper -
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Asynchronous simulated kalman filter optimization algorithm
Published 2018“…Simulated Kalman filter (SKF) is an optimization algorithm which is inspired by Kalman filtering method. …”
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Implementing server-side federated learning in an edge-cloud framework for precision aquaculture
Published 2025“…In this project, research and literature reviews were conducted to explore the current technologies in smart aquaculture, federated learning, and data privacy. Reviews include systems using IoT and AI-based models, along with analysis of different federated learning algorithms such as FedSGD, FedAvg, and FedProx, and privacypreserving methods such as DA, SA, HE and CKKS encryption. …”
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Final Year Project / Dissertation / Thesis -
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Simulated Kalman Filter algorithms for solving optimization problems
Published 2019“…In this research, two novel estimation-based metaheuristic optimization algorithms, named as Simulated Kalman Filter (SKF), and single-solution Simulated Kalman Filter (ssSKF) algorithms are introduced for global optimization problems. …”
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Optimization of milling parameters using ant colony optimization
Published 2008“…The simulation based on ACO algorithm are successful develop and the optimization of parameters values is to maximize the production rate is obtain from the simulation.…”
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Undergraduates Project Papers -
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Development of heuristic methods based on genetic algorithm (GA) for solving vehicle routing problem
Published 2008“…Genetic Algorithm as population-based methods are better identifying promising areas in the search space, while Tabu Search and Simulated Annealing as trajectory methods are better in exploring promising areas in search space. …”
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Monograph -
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Simulated Kalman Filter optimization algorithm for maximization of wireless sensor networks coverage
Published 2019“…Simulated Kalman Filter (SKF) is a population based optimization algorithm inspired by the Kalman filtering method. …”
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Conference or Workshop Item -
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An application of simulated Kalman filter optimization algorithm for parameter tuning in proportional-integral-derivative controllers for automatic voltage regulator system
Published 2018“…This paper reports the first attempt to tune gain values in proportional-integral-derivative (PID) controllers using an optimizer called simulated Kalman filter (SKF) algorithm. …”
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Conference or Workshop Item -
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Process Planning Optimization In Reconfigurable Manufacturing Systems
Published 2008“…The five (5) AADTs include; a variant of the simulated annealing algorithm that implements heuristic knowledge at critical decision points, two (2) cooperative search schemes based on a “loose hybridization” of the Boltzmann Machine algorithm with (i) simulated annealing, and (ii) genetic algorithm search techniques, and two (2) modified genetic algorithms. …”
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Design optimization of valve timing at various engine speeds using Multi-Objective Genetic Algorithm (MOGA)
Published 2008“…Majority of the research works in this project were in CAE software environment and method to implement optimization to 1D engine simulation. …”
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Proceeding Paper -
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MINIMIZATION OF MACHINING PROCESS SEQUENCE BASED ON ANT COLONY ALGORITHM AND CONVENTIONAL METHOD
Published 2023“…Based on the simulation, the Ant Colony algorithm method is, on average, 10.8% better than conventional methods in reducing machining time. …”
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