Search Results - (( weight evaluation method algorithm ) OR ( parameter optimization method algorithm ))
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A firefly algorithm based hybrid method for structural topology optimization
Published 2020“…In this paper, a firefly algorithm based hybrid algorithm through retaining global convergence of firefly algorithm and ability to generate connected topologies of optimality criteria (OC) method is proposed as an alternative method to solve stress-based topology optimization problems. …”
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Fuzzy clustering method and evaluation based on multi criteria decision making technique
Published 2018“…A similar degree between points was utilized to get similarity density, and then by means of maximum density points selecting them as weights of the Kohonen algorithm. After the optimization of the weights by modified version of the Kohonen Network method these weights will be set as the initial centres of the Gustafson-Kessel (GK) algorithm. …”
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Hybrid Artificial Bees Colony Algorithms For Optimizing Carbon Nanotubes Characteristics
Published 2018“…Optimization is a crucial process to select the best parameters in single and multi-objective problems for manufacturing process.However,it is difficult to find an optimization algorithm that obtain the global optimum for every optimization problem.Artificial Bees Colony (ABC) is a well-known swarm intelligence algorithm in solving optimization problems.It has noticeably shown better performance compared to the state-of-art algorithms.This study proposes a novel hybrid ABC algorithm with β-Hill Climbing (βHC) technique (ABC-βHC) in order to enhance the exploitation and exploration process of the ABC in optimizing carbon nanotubes (CNTs) characteristics.CNTs are widely used in electronic and mechanical products due to its fascinating material with extraordinary mechanical,thermal,physical and electrical properties. …”
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4
Modeling and multi-objective optimal sizing of standalone photovoltaic system based on evolutionary algorithms
Published 2020“…Due to the effective attraction-repulsion mechanism of electromagnetic-like (EM) algorithm and reliable exploration and exploitation phases of differential evolution (DE), these two methods were used to determine parameters of the single diode PV model and finding optimal sizing of the SAPV system. …”
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5
Modeling time series data using Genetic Algorithm based on Backpropagation Neural network
Published 2018“…This study showed the task of optimizing the topology structure and the parameter values (e.g., weights) used in the BPNN learning algorithm by using the GA. …”
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6
PID TUNING OF DC MOTOR USING SWARM ITELLIGENCE ALGORITHM
Published 2012“…In this project, Particle Swarm Optimization (PSO) as one of Swarm Intelligence Algorithm based has proposed to be integrated with PID (Proportional, Integral, Derivative) Controller in order to achieve optimal tuning method. …”
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Final Year Project -
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Power System State Estimation In Large-Scale Networks
Published 2010“…Also the WLS algorithm is modified to include Unified Power Flow Controller (UPFC) parameters. …”
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An Experiment of Ant Algorithms : Case Study of Kota Kinabalu Central Town
Published 2005“…Both algorithms are compared. Simulation is used as a method in this study. …”
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10
Thrust optimization of linear oscillatory actuator using permeance analysis method
Published 2011“…The first method is by evaluating the calculation output. The second method is by using generic algorithm. …”
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Optimal Location And Sizing Of Distrubuted Generator Using PSO And GA Algorithms In Power Systems
Published 2019“…Some existing algorithms need to be improved while others, need to add a new parameter for improving the performance of optimization methods and making it more effective and efficient. …”
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Thrust Optimization of Linear Oscillatory Actuator Using Permeance Analysis Method.
Published 2011“…The second method is by using generic algorithm. Both output of these method giving a different result in term of LOA PM's thickness however having similar thrust characteristics. …”
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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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Improving earth surface temperature forecasting through the optimization of deep learning hyper-parameters using barnacles mating optimizer
Published 2024“…To improve the DL model's performance, an optimization algorithm called Barnacles Mating Optimizer (BMO) is integrated to optimize both weights and biases. …”
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Optimize and deploy machine learning algorithms on embedded devices for manufacturing applications
Published 2025“…This proposal discusses the techniques of optimizing and deploying machine learning algorithms on embedded devices for manufacturing applications; We investigate problems of printed circuit board (PCB) defects and artificial intelligence in embedded system. …”
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Final Year Project / Dissertation / Thesis -
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Development an accurate and stable range-free localization scheme for anisotropic wireless sensor networks
Published 2022“…The localization accuracy and robustness of comparison indicated that the developed DWGWO-DV-Hop algorithm super outperforms the other classical range-free methods. …”
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Enhancing Autonomous Guided Vehicles with Red-Black TOR Iterative Method
Published 2023“…The proposed B-MTOR technique employs red-black ordering with four different weighted parameters. By carefully choosing the optimal parameter values, the suggested B-MTOR improved the computational execution of the algorithm. …”
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Utilizing self-organization systems for modeling and managing risk based on maintenance and repair in petrochemical industries
Published 2018“…Utilizing genetic algorithms, the structures of all self-organizing systems are optimized. …”
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Development of wwm system using mlnn-ga for ph prediction of water quality in catchment area
Published 2021“…MLNN-GA contain three hidden layers and Genetic Algorithm (GA) will optimize the weight of neural network during the training process. …”
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