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Titlebook: Computational Science – ICCS 2023; 23rd International C Ji?í Miky?ka,Clélia de Mulatier,Peter M.A. Sloot Conference proceedings 2023 The Ed

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21#
發(fā)表于 2025-3-25 04:51:06 | 只看該作者
22#
發(fā)表于 2025-3-25 09:57:18 | 只看該作者
23#
發(fā)表于 2025-3-25 14:56:10 | 只看該作者
Anna Nagurney,Min Yu,Jonas Flodening networks, which can be established in various situations from politics to online surveys. In this regard, the network nodes can represent members of a parliament, and each edge weight aims to be a probabilistic proxy for the alignment between the edge endpoints. In order to achieve such a goal,
24#
發(fā)表于 2025-3-25 16:30:32 | 只看該作者
25#
發(fā)表于 2025-3-25 20:33:42 | 只看該作者
Madhuri S. Pathak,Sourav Bhadra,Harini. G concrete plate structures. The problem is formulated as a bounded single objective optimization problem. The performance and efficiency of the algorithms are compared under various scenarios using noise-contaminated data. The results show that these meta-heuristics are powerful methods for global o
26#
發(fā)表于 2025-3-26 00:08:15 | 只看該作者
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發(fā)表于 2025-3-26 08:05:35 | 只看該作者
Sustainability Sciences in Asia and Africacial for informing the care that a patient should receive to help manage their Diabetes before an ulcer can form. In existing practice, risk stratification is a manual process where a clinician allocates a risk category based on biomarker features captured during routine appointments. We present the
28#
發(fā)表于 2025-3-26 10:29:29 | 只看該作者
Janice Alano Ragaza,Asda Lainingimportant for stratification in the risk classes and selecting appropriate treatment. Current work is devoted to developing a robust Machine Learning (ML) protocol for predicting the survival of patients with metastatic castration-resistant prostate cancer. In particular, we aimed to identify releva
29#
發(fā)表于 2025-3-26 13:05:10 | 只看該作者
Imran Ahmad,Abdulgader Turkistanisified as complex and multifactorial, with a difficult diagnosis. In this sense, this work aims to support the diagnosis of a rare autoimmune disease using the analysis of medical records from supervised machine learning methods and to identify the models with the best performance considering the ch
30#
發(fā)表于 2025-3-26 19:52:34 | 只看該作者
Janice Alano Ragaza,Asda Lainingproposed approaches for assisting dysgraphic people based on AI algorithms. However, existing aids for dysgraphia take only one aspect of the problem faced by the patients into consideration. Indeed, while some provide writing assistance, others address spelling or grammatical problems..In this pape
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