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model optimization » level optimization (Expand Search), motor optimization (Expand Search), monkey optimizations (Expand Search)
based process » batch process (Expand Search)
levels based » event based (Expand Search), models based (Expand Search)
model optimization » level optimization (Expand Search), motor optimization (Expand Search), monkey optimizations (Expand Search)
based process » batch process (Expand Search)
levels based » event based (Expand Search), models based (Expand Search)
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Predicting insulin dosage for diabetic patients to reach optimal glucose levels. (c2012)
Published 2012Get full text
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Adapted arithmetic optimization algorithm for multi-level thresholding image segmentation: a case study of chest x-ray images
Published 2023“…The solutions are evaluated using Otsu's fitness function throughout the optimization process. The picture histogram is used to display the algorithm's potential solutions. …”
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Optimized FPGA Implementation of PWAM-Based Control of Three—Phase Nine—Level Quasi Impedance Source Inverter
Published 2019“…Since, PWAM control algorithm is more complex than PSCPWM, FPGA based implementation for PWAM control is discussed. …”
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An Intensive and Comprehensive Overview of JAYA Algorithm, its Versions and Applications
Published 2021“…Initially, the optimization model and convergence characteristics of JAYA algorithm are carefully analyzed. …”
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Multiclass feature selection with metaheuristic optimization algorithms: a review
Published 2022“…Nevertheless, metaheuristic algorithms attract substantial attention to solving different problems in optimization. …”
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Multi-Objective Optimisation of Injection Moulding Process for Dashboard Using Genetic Algorithm and Type-2 Fuzzy Neural Network
Published 2024“…Its purpose was to estimate shear and residual stress levels. Additionally, the multi-objective genetic algorithm (MOGA) was utilised to extract the most optimal parameters for the injection moulding process, aiming to minimise shear and residual stress and thereby increase the resistance of the final product. …”
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Retinal imaging based glaucoma detection using modified pelican optimization based extreme learning machine
Published 2024“…For mass fundus image-based glaucoma classification, an improved automated computer-aided diagnosis (CAD) model performing binary classification (glaucoma or healthy), allowing ophthalmologists to detect glaucoma disease correctly in less computational time. …”
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Tensile Test Optimization Using the Design of Experiment and Soft Computing
Published 2023“…This study employs a hybrid soft computing approach, integrating an adaptive network-based fuzzy inference system (ANFIS), genetic algorithm (GA) optimization, and design of experiments (DOE). …”
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Clustering and Stochastic Simulation Optimization for Outpatient Chemotherapy Appointment Planning and Scheduling
Published 2022“…A Stochastic Discrete Simulation-Based Multi-Objective Optimization (SDSMO) model is developed and linked to clustering algorithms using an iterative sequential approach. …”
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Optimizing Aircraft Pitch Control Systems: A Novel Approach Integrating Artificial Rabbits Optimizer with PID-F Controller
Published 2024“…The study employs a time-domain-based objective function to guide the optimization process. …”
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Deep Learning-Based Short-Term Load Forecasting Approach in Smart Grid With Clustering and Consumption Pattern Recognition
Published 2021“…A k-Medoid based algorithm is employed for clustering whereas the forecasting models are generated for different clusters of load profiles. …”
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Machine Learning-Driven Prediction of Corrosion Inhibitor Efficiency: Emerging Algorithms, Challenges, and Future Outlooks
Published 2025“…Drawing on more than fifteen harmonized datasets that span pyrimidines, ionic liquids, graphene oxides, and additional compound families, we benchmark traditional algorithms, such as artificial neural networks, support vector machines, k-nearest neighbors, random forests, against advanced graph-based and deep architectures including three-level directed message-passing neural networks, 2D3DMol-CIC, and graph convolutional networks. …”
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