202461 · An air classifier is one of the main and effective devices in cement industry. In this study, a three-dimensional, steady and two-phase (solid-gas) computational fluid dynamics (CFD) simulation was performed to optimize the performance of this device in the Kerman Momtazan cement plant, Iran. After the validation of CFD results, the air flow ...
view more2020828 · Pytorch():TRAINING A CLASSIFIER. , ,。. ?. ,,,, numpy python。. , ...
view more2024615 · 1. Introduction. Membrane separation technology has significantly progressed in membrane preparation and water treatment applications (Lin et al., 2020; Obotey Ezugbe and Rathilal, 2020; Shen et al., 2023; Sun et al., 2024; Wu and Chen, 2020).Once the membrane is broken, pollutants such as macromolecular organic matter, …
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view more2020121 · Generally, the powder selection efficiency of high-efficiency cement classifier reached 65%. For any one of the classifier group, can select the efficiency of more than 90%, the simplest way is to adjust the fineness of the grinding to the fineness of the finished product, so closed circuit grinding mill will lose its significance.
view more2019105 · evaporation causing the formation of salt and gypsum in the soil [1,22]. ... algorithms, is considered a highly accurate classifier for many datasets, it can run efficiently on large .
view more202413 · ,classifier guidanceclassifier,classifier。 classifier free guidancediffusion,,,guidance_scale。
view more2016119 · Sample 8 Gypsum board Building Construction Material 1 cm ˆ 1 cm ˆ 2 cm gypsum board The second dataset obtained from a Portable Electronic Nose (PEN3) from Airsense Analytics GmbH (Schwerin ...
view moreTherefore, this paper presents the design and implementation of ProxiML - a novel quantum machine learning classifier for photonic quantum computing devices with multiple noise-aware design elements for effective model training and inference. Our extensive evaluation on a photonic device (Xanadu's X8 machine) demonstrates the effectiveness of ...
view more2024128 · Ensemble learning combines all generated base learners for better generalization performance, but weak and redundant classifiers reduce the classification system’s performance, so the researchers proposed ensemble pruning. Existing ensemble pruning methods usually utilize the classifiers’ diversity and ability to select optimal …
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