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effective implementation » effective prevention (Expand Search)
python effective » proven effective (Expand Search), 1_the effective (Expand Search), 2_the effective (Expand Search)
python model » python code (Expand Search), python tool (Expand Search), action model (Expand Search)
effective implementation » effective prevention (Expand Search)
python effective » proven effective (Expand Search), 1_the effective (Expand Search), 2_the effective (Expand Search)
python model » python code (Expand Search), python tool (Expand Search), action model (Expand Search)
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Cost functions implemented in Neuroptimus.
Published 2024“…However, using most of these software tools and choosing the most appropriate algorithm for a given optimization task require substantial technical expertise, which prevents the majority of researchers from using these methods effectively. To address these issues, we developed a generic platform (called Neuroptimus) that allows users to set up neural parameter optimization tasks via a graphical interface, and to solve these tasks using a wide selection of state-of-the-art parameter search methods implemented by five different Python packages. …”
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Summary of Tourism Dataset.
Published 2025“…The proposed TourVaRNN integrates variational autoencoders to capture latent variables representing visitor preferences and spending habits, while recurrent neural networks model complex temporal dependencies in tourism data. …”
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Segment-wise Spending Analysis.
Published 2025“…The proposed TourVaRNN integrates variational autoencoders to capture latent variables representing visitor preferences and spending habits, while recurrent neural networks model complex temporal dependencies in tourism data. …”
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Hyperparameter Parameter Setting.
Published 2025“…The proposed TourVaRNN integrates variational autoencoders to capture latent variables representing visitor preferences and spending habits, while recurrent neural networks model complex temporal dependencies in tourism data. …”
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Marketing Campaign Analysis.
Published 2025“…The proposed TourVaRNN integrates variational autoencoders to capture latent variables representing visitor preferences and spending habits, while recurrent neural networks model complex temporal dependencies in tourism data. …”
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Visitor Segmentation Validation Accuracy.
Published 2025“…The proposed TourVaRNN integrates variational autoencoders to capture latent variables representing visitor preferences and spending habits, while recurrent neural networks model complex temporal dependencies in tourism data. …”
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Integration of VAE and RNN Architecture.
Published 2025“…The proposed TourVaRNN integrates variational autoencoders to capture latent variables representing visitor preferences and spending habits, while recurrent neural networks model complex temporal dependencies in tourism data. …”
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Overview of generalized weighted averages.
Published 2025“…In this study, we propose a new generalized upper confidence bound (UCB) algorithm (GWA-UCB1) by extending UCB1, which is a representative algorithm for MAB problems, using generalized weighted averages, and present an effective algorithm for various problem settings. …”
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Microscopic Detection and Quantification of Microplastic Particles in Environmental Water Samples
Published 2025“…Image processing algorithms, implemented in Python using adaptive thresholding techniques, were applied to segment particles from the background. …”
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Code
Published 2025“…This function takes two numeric vectors representing the observations from the high-coupling and low-coupling groups and returns the estimated effect size along with confidence intervals.…”
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Core data
Published 2025“…This function takes two numeric vectors representing the observations from the high-coupling and low-coupling groups and returns the estimated effect size along with confidence intervals.…”