Search Results - (( using modification _ algorithm ) OR ( data optimization method algorithm ))
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A hybrid metaheuristic algorithm for identification of continuous-time Hammerstein systems
Published 2021“…The proposed hybrid method also achieved better performance in modeling of the twin-rotor system as well as the flexible manipulator system and provided better solutions compared to other optimization methods including Particle Swarm Optimizer, Grey Wolf Optimizer, Multi-Verse Optimizer and Sine Cosine Algorithm.…”
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Modification of particle swarm optimization algorithm for optimization of discrete values
Published 2011“…We propose a novel modification to the PSO algorithm to perform rapid discrete optimization. …”
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1D Multigrid Solver For Finite Element Method
Published 2022“…Usually, the mathematical problem can be solved using only one of those two methods. A sample of such code written in MATLAB programming language was found in the GitHub repository, where the implemented algorithms are far from optimal. …”
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Improved stochastic gradient descent algorithm with mean-gradient adaptive stepsize for solving large-scale optimization problems
Published 2023“…Stochastic gradient descent (SGD) is one of the most common algorithms used in solving large unconstrained optimization problems. …”
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Data-driven continuous-time Hammerstein modeling with missing data using improved Archimedes optimization algorithm
Published 2024“…This research introduces the improved Archimedes optimization algorithm (IAOA) for data-driven modeling of continuous-time Hammerstein models with missing data. …”
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Identification of continuous-time model of hammerstein system using modified multi-verse optimizer
Published 2021“…The mMVO based method is then used for identifying the parameters of linear and nonlinear subsystems in the Hammerstein model using the given input and output data. …”
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A new variant of black hole algorithm based on multi population and levy flight for clustering problem
Published 2020“…Black Hole (BH) optimization algorithm has been underlined as a solution for data clustering problems. …”
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Optimizing Decentralized Exam Timetabling with a Discrete Whale Optimization Algorithm
Published 2025“…In recent years, there has been increasing interest in intelligent optimization algorithms, such as the Whale Optimization Algorithm (WOA). …”
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Optimizing decentralized exam timetabling with a discrete whale optimization algorithm
Published 2025“…—In recent years, there has been increasing interest in intelligent optimization algorithms, such as the Whale Optimization Algorithm (WOA). …”
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Optimizing lossless compression by normalized data length in Huffman Algorithm
Published 2022“…The 4-ary/MQ method employs the characteristics of the Quadtree structure and extends the Dynamic Huffman coding mechanism (FGK rule) in node arrangement while adopting the Adaptive Huffman method that uses additional variable data. …”
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CAT CHAOTIC GENETIC ALGORITHM BASED TECHNIQUE AND HARDWARE PROTOTYPE FOR SHORT TERM ELECTRICAL LOAD FORECASTING
Published 2017“…In the hybrid scheme, the initial parameters of the modified BP neural network are optimized by using the global search ability of genetic algorithm, improved by cat chaotic mapping to enrich its optimization capability. …”
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Improving Attentive Sequence-to-Sequence Generative-Based Chatbot Model Using Deep Neural Network Approach
Published 2022“…Hence, this research’s objective aimed to propose an optimization strategy based on Structural Modification and Optimizing Training Network for improving the lacking of accuracy of response in the chatbot application, to propose the algorithm enhancement to improve the current attention mechanism in the Attentive Sequence-to-Sequence model and the network’s training optimization of its inability to memorize the dialogue history, and lastly, to evaluate the accuracy of response of the proposed solution through data training on loss function and real data testing. …”
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Prediction of UPSR Result using clonal selection algorithm (PUR) / Muhammed Khaleeq Shafii
Published 2012“…This project focuses on three main objectives to investigate the UPSR Examination of data for prediction result, to study the Clonal Selection algorithm of the term and to develop the Prediction of UPSR Result System using Clonal Selection Algorithm. …”
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A hybrid multi objective cellular spotted hyena optimizer for wellbore trajectory optimization
Published 2022“…Hopefully, this newly proposed modified algorithm will pave the way for better wellbore trajectory optimization. …”
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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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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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Optimization of the Jakim halal logo placement on qr code using enhanced genetic algorithm
Published 2018“…Pad codewords modification technique is used to minimize the error introduced by the logo while three QR code decoders are used to achieve high probability of decode feasibility. …”
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Potential of data minimization techniques approach in improving DNA sequences alignment and comparison / Syed Abdul Mutalib Al Junid … [et al.]
Published 2012“…This study will initially involve algorithm modification, mathematical formulation, logic design and simulation for data minimization and existing DNA sequences alignment algorithm. …”
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Hybrid tabu search – strawberry algorithm for multidimensional knapsack problem
Published 2022“…Next, the solution was enhanced by using the hybrid TS-SBA. The parameters setting to run the hybrid TS-SBA was determined by using a combination of Factorial Design of Experiments and Decision Tree Data Mining methods. …”
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