Search alternatives:
process optimization » model optimization (Expand Search)
robust optimization » robust estimation (Expand Search), joint optimization (Expand Search)
based process » based processes (Expand Search), based probes (Expand Search), based proteins (Expand Search)
binary based » library based (Expand Search), linac based (Expand Search), binary mask (Expand Search)
binary data » primary data (Expand Search), dietary data (Expand Search)
process optimization » model optimization (Expand Search)
robust optimization » robust estimation (Expand Search), joint optimization (Expand Search)
based process » based processes (Expand Search), based probes (Expand Search), based proteins (Expand Search)
binary based » library based (Expand Search), linac based (Expand Search), binary mask (Expand Search)
binary data » primary data (Expand Search), dietary data (Expand Search)
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A* Path-Finding Algorithm to Determine Cell Connections
Published 2025“…Pixel paths were classified using a z-score brightness threshold of 1.21, optimized for noise reduction and accuracy. The A* algorithm then evaluated connectivity by minimizing Euclidean distance and heuristic cost between cells. …”
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An Example of a WPT-MEC Network.
Published 2025“…To enhance the offloading decision-making process, the algorithm incorporates the Newton-Raphson method for fast and efficient optimization of the computation rate under energy constraints. …”
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Related Work Summary.
Published 2025“…To enhance the offloading decision-making process, the algorithm incorporates the Newton-Raphson method for fast and efficient optimization of the computation rate under energy constraints. …”
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Simulation parameters.
Published 2025“…To enhance the offloading decision-making process, the algorithm incorporates the Newton-Raphson method for fast and efficient optimization of the computation rate under energy constraints. …”
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Training losses for N = 10.
Published 2025“…To enhance the offloading decision-making process, the algorithm incorporates the Newton-Raphson method for fast and efficient optimization of the computation rate under energy constraints. …”
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Normalized computation rate for N = 10.
Published 2025“…To enhance the offloading decision-making process, the algorithm incorporates the Newton-Raphson method for fast and efficient optimization of the computation rate under energy constraints. …”
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Summary of Notations Used in this paper.
Published 2025“…To enhance the offloading decision-making process, the algorithm incorporates the Newton-Raphson method for fast and efficient optimization of the computation rate under energy constraints. …”
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Predicting Thermal Decomposition Temperature of Binary Imidazolium Ionic Liquid Mixtures from Molecular Structures
Published 2021“…The subset of optimal descriptors was screened by combining the genetic algorithm with the multiple linear regression method. …”
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IRBMO vs. variant comparison adaptation data.
Published 2025“…To adapt to the feature selection problem, we convert the continuous optimization algorithm to binary form via transfer function, which further enhances the applicability of the algorithm. …”
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Improved support vector machine classification algorithm based on adaptive feature weight updating in the Hadoop cluster environment
Published 2019“…<div><p>An image classification algorithm based on adaptive feature weight updating is proposed to address the low classification accuracy of the current single-feature classification algorithms and simple multifeature fusion algorithms. …”
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Design and implementation of the Multiple Criteria Decision Making (MCDM) algorithm for predicting the severity of COVID-19.
Published 2021“…<p>(A). The MCDM algorithm-Stage 1. Preprocessing, this stage is the process of refining the collected raw data to eliminate noise, including correlation analysis and feature selection based on P values. …”
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Multicategory Angle-Based Learning for Estimating Optimal Dynamic Treatment Regimes With Censored Data
Published 2021“…Specifically, the proposed method obtains the optimal DTR via integrating estimations of decision rules at multiple stages into a single multicategory classification algorithm without imposing additional constraints, which is also more computationally efficient and robust. …”