Search Results - (( based optimization means algorithm ) OR ( data equalization based algorithm ))
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A comparison of watermarking image quality based on dual intermediate significant bit with genetic algorithm
Published 2013“…In this case, when the two hidden bits are equal to the original bits, there will be no change to the other remaining bits.However, if the original value is not equal to the embedded one, the nearest pixel to the original one will be chosen as the watermarked image.The second method, GA method is used to embed two bits of watermarking data within every pixel of the original image and to find the optimal value based on the existing DISB.On the other hand, if the two embedded bits are equal to the original bits then this means the watermarked image is still the same as the original one without any changes, while in the other case GA is used in determining the minimum fitness value in which the fittest is the absolute value between the pixel and chromosome and the value of chromosome between 0-255.The results indicate that the two methods produce a high quality watermarked image, but there is a big difference in the processing time, so the DISB method is faster than the GA method.…”
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An Empirical Study on the Construction of A Non-Convex Risk Parity Portfolio using a Genetic Algorithm
Published 2025“…Risk-based portfolio optimization has become increasingly crucial due to the limitations and underperformance of traditional Mean-Variance (MV) portfolios. …”
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High image quality watermarking model by using genetic algorithm
Published 2012“…In this study, Genetic Algorithm (GA) method is used to embed two bits of watermarking data within every pixel of original image and to find the optimal value based on the existing Dual Intermediate Significant Bit (DISB). …”
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Proceeding Paper -
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High image quality watermarking model by using genetic algorithm
Published 2012“…Many studies try to enhance the quality by using different techniques and methods.In this study, Genetic Algorithm (GA) method is used to embed two bits of watermarking data within every pixel of original image and to find the optimal value based on the existing Dual Intermediate Significant Bit (DISB).However, if the two embedded bits is equal to the original bits then this means the watermarked image is still the same as the original one without any changing, while in the other case GA is used getting the minimum fitness value in which the fitness is the absolute value between the pixel and chromosome and the value of chromosome between 0-255.The results show that the new method improves the image quality and get the optimal value for the two embedded bits.…”
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A modified weighted support vector machine (WSVM) to reduce noise data in classification problem
Published 2021“…To overcome SVM drawback for noise data problem, WSVM using KPCM algorithm was used but WSVM using kernel-based learning algorithm such as KPCM algorithm suffer from training complexity, expensive computation time and storage memory when noise data contaminate training data. …”
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Thesis -
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A modified weighted support vector machine (WSVM) to reduce noise data in classification problem
Published 2021“…To overcome SVM drawback for noise data problem, WSVM using KPCM algorithm was used but WSVM using kernel-based learning algorithm such as KPCM algorithm suffer from training complexity, expensive computation time and storage memory when noise data contaminate training data. …”
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Technical report: genetic algorithm for vehicle routing problem / Mohammad Izwan Jamaluddin and Muhamad Syahmie Adeeb Mohd Shukri
Published 2016“…Based on the study that have been conducted the minimum routes is equal to 3990. …”
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Student Project -
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New signed-digit {0,1,3}-NAF scalar multiplication algorithm for elliptic curve over binary field
Published 2011“…Mathematical analysis is carried out to identify important features, advantages and disadvantages of the new signed-digit {0,1,3}-NAF scalar multiplication algorithm. Cost measurement is based on number of point operations per scalar throughout the execution of the scalar multiplication algorithm. …”
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Acquisition of new subscribers using analytical models in the telecommunication industry / Nik Muhammad Naim Nik Ghazali
Published 2020“…The proposed algorithm for building the analytical acquisition model benefits the Data Science community to explore the use of optimization model in their work domain. …”
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Prediction of shear strength of concrete using the artificial neural network / R. Rohim, S.F. Senin and N.F. Azman
Published 2022“…The remaining 18 (35%) mixes data were divided equally into testing and validation data sets. …”
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Meta-heuristic approaches for reservoir optimisation operation and investigation of climate change impact at Klang gate dam
Published 2023“…The Whale Optimisation Algorithm (WOA), Harris Hawks Optimisation (HHO) Algorithm, Lévy Flight WOA (LFWOA) and the Opposition-Based Learning of HHO (OBL-HHO) were proposed to simulate the initial model’s response and optimise the Klang Gate Dam (KGD) release operation with observed inflow, water level (storage), release, and evaporation rate (loss). …”
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Final Year Project / Dissertation / Thesis -
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Application of Bat Algorithm and Its Modified Form Trained with ANN in Channel Equalization
Published 2022“…An alternative approach to training neural network-based equalizers is to use metaheuristic algorithms. …”
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Optimal neural network approach for estimating state of energy of lithium-ion battery using heuristic optimization techniques
Published 2023Conference Paper -
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Optimized clustering with modified K-means algorithm
Published 2021“…Among the techniques, the k-means algorithm is the most commonly used technique for determining optimal number of clusters (k). …”
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An improved artificial bee colony algorithm based on mean best-guided approach for continuous optimization problems and real brain MRI images segmentation
Published 2024“…In this paper, a new ABC algorithm called MeanABC is introduced to achieve the search behavior balance via a modified search equation based on the information of the mean of the previous best solutions. …”
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Impact of evolutionary algorithm on optimization of nonconventional machining process parameters
Published 2025“…This paper presents the optimization of laser beam machining in additive manufacturing of polymer-based material parameters, specifically focusing on cutting speed, gas pressure of nitrogen, and focal point locations, to achieve optimal mean surface roughness. …”
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Document clustering based on firefly algorithm
Published 2015“…Document clustering is widely used in Information Retrieval however, existing clustering techniques suffer from local optima problem in determining the k number of clusters.Various efforts have been put to address such drawback and this includes the utilization of swarm-based algorithms such as particle swarm optimization and Ant Colony Optimization.This study explores the adaptation of another swarm algorithm which is the Firefly Algorithm (FA) in text clustering.We present two variants of FA; Weight- based Firefly Algorithm (WFA) and Weight-based Firefly Algorithm II (WFAII).The difference between the two algorithms is that the WFAII, includes a more restricted condition in determining members of a cluster.The proposed FA methods are later evaluated using the 20Newsgroups dataset.Experimental results on the quality of clustering between the two FA variants are presented and are later compared against the one produced by particle swarm optimization, K-means and the hybrid of FA and -K-means. …”
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Fuzzy C-Mean And Genetic Algorithms Based Scheduling For Independent Jobs In Computational Grid
Published 2006“…Our model presents the method of the jobs classifications based mainly on Fuzzy C-Mean algorithm and mapping the jobs to the appropriate resources based mainly on Genetic algorithm. …”
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