Search Results - (( sequence optimization means algorithm ) OR ( parameter extraction means algorithm ))*
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1
Intelligent grading of agarwood essential oil quality using artificial neural network (ANN) / Noratikah Zawani Mahabob
Published 2022“…The training and validation of the ANN was based on optimization of its training parameters and guided by the convergence of the mean squared errors (MSE). …”
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2
An enhanced swap sequence-based particle swarm optimization algorithm to solve TSP
Published 2021“…To evaluate the proposed algorithm, the solutions to the TSP problem obtained from the proposed algorithm and swap sequence based PSO are compared in terms of the best solution, mean solution, and time taken to converge to the optimal solution. …”
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3
Modified Harris Hawks Optimization Algorithm For Protein Multiple Sequence Alignment
Published 2024“…A notable entrant in this domain is the harris hawks optimization (hho) algorithm, which has distinguished itself through published optimization outcomes, positioning it as a formidable competitor among state-of-the-art metaheuristics. …”
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4
Parameters extraction of double diode photovoltaic module's model based on hybrid evolutionary algorithm
Published 2023“…Algorithms; Diodes; Errors; Extraction; Iterative methods; Mean square error; Optimization; Parameter estimation; Parameter extraction; Photovoltaic cells; Differential evolution algorithms; Diode modeling; Electromagnetism-like algorithm; Fast convergence speed; Hybrid evolutionary algorithm; IV characteristics; Photovoltaic model; Root mean square errors; Evolutionary algorithms…”
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A comparative study of evolutionary algorithms and adapting control parameters for estimating the parameters of a single-diode photovoltaic module's model
Published 2023“…Algorithms; Diodes; Errors; Iterative methods; Least squares approximations; Mean square error; Optimization; Parameter estimation; Parameter extraction; Photovoltaic cells; Coefficient of determination; Differential Evolution; Electromagnetism-like algorithm; Hybrid evolutionary algorithm; Photovoltaic; Photovoltaic modules; Root mean square errors; Single-diode models; Evolutionary algorithms; algorithm; comparative study; electromagnetic method; estimation method; experimental design; numerical method; parameterization; performance assessment; photovoltaic system…”
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Energy efficient modeling and optimization for assembly sequence planning using moth flame optimization
Published 2019“…The problem was then optimized using moth flame optimization (MFO) and compared with well-established algorithms such as genetic algorithm (GA), particle swarm optimization (PSO) and ant colony optimization (ACO). …”
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Application of intelligence based genetic algorithm for job sequencing problem on parallel mixed-model assembly line
Published 2010“…Then, it started to find the best sequence of jobs for each line based on the generated population by heuristic algorithm. …”
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Individual-tree segmentation and extraction based on LiDAR point cloud data
Published 2024“…The objective was to identify the optimal parameters for both algorithms in terms of tree height extraction precision. …”
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Biogeography based optimization (BBO) algorithm to minimise non-productive time during hole-making process
Published 2015“…The proposed approach tackles the sequencing problem when several holes must be drilled by means of different tools to reach their desired size. …”
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Effect of adopting different dispatching rules on the mean flow time in a two machine batch-shop problem
Published 2005“…Therefore, researchers concentrated on developing branch-and-bound or heuristic algorithms. Ali Allahverdi, 1998 obtained the optimal solutions for minimizing mean flow time in a two-machine flow shop with Sequence-independent set up times by using three heuristic algorithms. …”
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12
Flock optimization algorithm-based deep learning model for diabetic disease detection improvement
Published 2024“…The collected data is processed by a Gaussian filtering approach that eliminates irrelevant information, reducing the overfitting issues. Then flock optimization algorithm is applied to detect the sequence; this process is used to reduce the convergence and optimization problems. …”
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VLSI floor planning optimization using genetic algorithm and cross entropy method / Angeline Teoh Szu Fern
Published 2012“…Hence, VLSI floorplanning is important in IC design. Floorplanning optimization consists of representation and optimization algorithm. …”
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15
A neural network modal decomposition mechanism in predicting network traffic
Published 2023“…Specifically, the predictive accuracy indexes such as Mean Absolute Percentage Error (MAPE), Mean Absolute Error (MAE) and Root Mean Squared Error (RMSE) can reach a lowest optimum value of 1.1410, 0.1758 and 0.2263, and the average training time is reduced by 25.25%, 23.87% and 41.36%, respectively. …”
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Application of orthogonal optimization and feedforward backpropagation model in the microwave extraction of natural antioxidants from tropical white pepper
Published 2018“…This study investigated the combination of microwave extraction parameters for the recovery of natural antioxidants from the white pepper matrix. …”
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Modeling of vehicle trajectory using K-means and fuzzy C-means clustering
Published 2019“…Hence, the clustering of vehicle trajectory dataset for similar patterns identification is implemented with k-means and fuzzy c-means (FCM) clustering algorithm. …”
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Proceedings -
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Genetic algortihm to solve pcb component placement modeled as travelling salesman problem
Published 2013“…At the end of the project, we will be able to see how genetic algorithm used to get optimize result for TSP.…”
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Undergraduates Project Papers -
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Using a novel algorithm in ultrasound images to detect renal stones
Published 2021“…The pre-processed image is taken as input for the segmentation process. Fuzzy C-means, K-means, and Expectation–Maximization algorithms are used to segment the renal calculi from the kidney ultrasound image; further region parameters are extracted from the segmented region. …”
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Proceedings -
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Optimization of Simultaneous Scheduling for Machines and Automated Guided Vehicles Using Fuzzy Genetic Algorithm
Published 2009“…The objective of proposed FGA method is to minimize the makespan, production completion time of all jobs that they are produced simultaneously. An optimal sequence of operations is obtained by GA. …”
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