Search Results - (( parameter optimization strategy algorithm ) OR ( data validation using algorithm ))
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Heart disease prediction using artificial neural network with ADAM optimization and harmony search algorithm
Published 2025“…The ADAM optimizer effectively tackles challenges in continuous parameter optimization by dynamically updating the model's weights and biases, adapting the learning rate for each parameter based on accumulated historical gradient information to achieve more efficient minimization of the loss function during training. …”
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HYBRID SINE COSINE AND FITNESS DEPENDENT OPTIMIZER FOR INCOMPLETE DATASET
Published 2024“…The hybrid sine cosine and fitness dependent optimizer (SC-FDO) introduces four modifications to the original fitness dependent optimizer (FDO) algorithm to improve its exploit-explore tradeoff with a faster convergence speed. …”
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Book Chapter -
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Robust Portfolio Mean-Variance Optimization for Capital Allocation in Stock Investment Using the Genetic Algorithm: A Systematic Literature Review
Published 2024journal::journal article -
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Development of efficient t-way test data generation algorithm and execution strategies
Published 2012“…This strategy is able to reduce the number of test data, but the execution time is not optimized. …”
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Optimization of Microbial Electrolysis Cell for Sago Mill Wastewater Derived Biohydrogen via Modeling and Artificial Neural Network
Published 2023“…Model validity describes the first sub-objective, which is to solve the complexity of the nonlinear interaction of multiple MEC input variables related to the hydrogen production rate response using artificial neural networks (ANN) before validating the mathematical modeling results by comparing experimental data with the predicted substrate concentration profile and hydrogen production rate profile based on the re-estimated input values of the model parameters using single-objective optimization based on the nonlinear convex method using gradient descent algorithm. …”
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Variable Neighborhood Descent and Whale Optimization Algorithm for Examination Timetabling Problems at Universiti Malaysia Sarawak
Published 2025“…A constructive algorithm was developed to generate an initial feasible solution, which was subsequently refined using two primary approaches to evaluate their efficiency: Iterative Threshold Pipe Variable Neighborhood Descent (IT-PVND), and a modified Whale Optimization Algorithm (WOA). …”
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Discrete-time system identification using genetic algorithm with single parent-based mating technique
Published 2024“…This enhanced the GA's ability to avoid premature convergence and maintained a diverse solution set, leading to more optimal model selection. The study's results were validated using real-world data from industrial systems, including a hair dryer, an air compression system, and a flexible robot arm. …”
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Electricity load profile determination by using fuzzy C-means and probability neural network / Norhasnelly Anuar
Published 2015“…As compared with the backpropagation method in literature review, it gives better result when classifying large data sets. The objectives of this project are to use FCM as the clustering algorithm to establish TLPs. …”
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An Optimized Load Shedding Approach in Power Grids to Mitigate Cascading Failure
Published 2025“…The standard IEEE test systems have been used as a benchmark to validate the proposed approach. …”
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Proceeding -
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Deep Learning-Driven Mobility And Utility-Based Resource Management In Mm-Wave Enable Ultradense Heterogeneous Networks
Published 2025thesis::doctoral thesis -
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Predictive Functional Control With Reduced-Order Observer Design Using Particle Swarm Optimization For Pneumatic System
Published 2020“…An optimization technique will be implemented in this project using Particle Swarm Optimization (PSO) algorithm. …”
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Optimization of solenoid driver and controller for gaseous fuel high-pressure direct injector using model-based approach
Published 2022“…An optimization study was conducted using Normal Boundary Intersection (NBI) algorithm in MATLAB Model-Based Calibration (MBC) Toolbox to produce an optimal injector setup. …”
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Motion planning and control for autonomous vehicle collision avoidance systems using potential field-based parameter scheduling
Published 2024“…A particle swarm optimization algorithm is used to optimize the knowledge database information that is developed based on the perception of driver toward risk in the driving environment. …”
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Book Chapter -
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Motion planning and control for autonomous vehicle collision avoidance systems using potential field-based parameter scheduling
Published 2024“…A particle swarm optimization algorithm is used to optimize the knowledge database information that is developed based on the perception of driver toward risk in the driving environment. …”
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Optimization-driven extreme learning machine for floating photovoltaic power prediction: A teaching learning-based approach
Published 2025“…The framework was validated using comprehensive year-long operational data from a Malaysian FPV installation and benchmarked against established optimization-based ELM variants (GA-ELM, PSO-ELM, BMO-ELM). …”
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Experimental and AI-driven enhancements in gas-phase photocatalytic CO2 conversion over synthesized highly ordered anodic TiO2 nanotubes
Published 2025“…These results demonstrated the robust and effective predictive capabilities of the ANN model for CO2 conversion efficiency. The optimization of the input parameters for CO2 photoconversion was comprehensively validated using the predicted and experimental data. …”
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Analytical framework for predicting online purchasing behavior in Malaysia using a machine learning approach
Published 2025“…Feature selection techniques, such as WrapperSubsetEval, were used to improve focus on key attributes, and parameter tuning further optimized performance. …”
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On Adopting Parameter Free Optimization Algorithms for Combinatorial Interaction Testing
Published 2015“…Although useful, strategies based on the aforementioned optimization algorithms are not without limitation. …”
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Application of Machine Learning and Deep Learning Algorithms for Landslide Susceptibility Assessment in Landslide Prone Himalayan Region
Published 2025“…We carefully selected relevant metrics based on existing research and conducted a multicollinearity analysis on each parameter to ensure the model?s accuracy. We randomly split the data into training and validation sets in a 70/30 ratio. …”
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