Comprehensive benefits evaluation of low impact development using scenario analysis and fuzzy decision approach by Ting Ni, Xiaohong Zhang, Peng Leng, Mark Pelling, Jiuping Xu

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Clustering and Interpretability of Residential Electricity Demand Profiles by Sarra Kallel, Manar Amayri, Nizar Bouguila

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Machine learning-based academic performance prediction with explainability for enhanced decision-making in educational institutions by Wesam Ahmed, Mudasir Ahmad Wani, Pawel Plawiak, Souham Meshoul, Amena Mahmoud, Mohamed Hammad

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Investigating and Optimizing MINDWALC Node Classification to Extract Interpretable Decision Trees from Knowledge Graphs by Maximilian Legnar, Joern-Helge Heinrich Siemoneit, Gilles Vandewiele, Jürgen Hesser, Zoran Popovic, Stefan Porubsky, Cleo-Aron Weis

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The accuracy of an electronic-Surprise-Question defining end-of-life cohorts in a whole adult population by algorithmic digital risk stratification: the Proactive Risk-Based and Da... by Baldev M. Singh, Nisha Kumari-Dewat, Vijay Klaire, Jonathan Lampitt, Amy Palmer, Adam Ryder, Kamran Ahmed, Mona Sidhu, Hannah Jennens, Ananth Viswanath, Emma Parry

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Deepfake Face Detection and Adversarial Attack Defense Method Based on Multi-Feature Decision Fusion by Shanzhong Lei, Junfang Song, Feiyang Feng, Zhuyang Yan, Aixin Wang

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Pythagorean Fuzzy Overlap Functions and Corresponding Fuzzy Rough Sets for Multi-Attribute Decision Making by Yongjun Yan, Jingqian Wang, Xiaohong Zhang

“…Therefore, a new PFRS approximate accuracy is developed which generalizes the approximate accuracy of classical rough sets and remains applicable to the classical case. Finally, three multi-criteria decision-making (MCDM) algorithms based on PF information are proposed, and their effectiveness and rationality are validated through examples, making them more flexible for solving MCDM problems in the PF environment.…”
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Decision vector model in predicting social behavior (on the example of the secondary analysis of the pre-election surveys) by N. S. Babich, S. M. Kharun

“…The article considers a decision vector model that can be used to approximate actual behavior with some formal rules that allow to construct algorithms for predicting future states. …”
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Lightweight detection algorithms for small targets on unmanned mining trucks by Shuoqi CHENG, Yilihamu·YAERMAIMAITI, Lirong XIE, Xiyu LI, Ying MA

“…Experiments show that the improved algorithm reduces parameters by 50.2%, computational load by 46.3%, and model size by 47.6% compared to the original algorithm, with a model size of only 3.3 MB. …”
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Moving Target Oriented Opportunistic Routing Algorithm in Vehicular Networks by Yu Ding, Wendong Wang, Yong Cui, Xiangyang Gong, Bai Wang

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Tower Crane Layout Planning: Multi-Optimal Solutions Algorithm by Xiaokang Huang, Huazhou Chen, Rui Wang, Heng Wang, Shuai Li, Pengfei Zhang, Zhen Yang

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Financial engineering and the digital economy: The implementations of machine learning algorithms by Pingping Fu, Honghao Yang, Wenhao Qian, ELsiddig Idriss Mohamed, Wafa Ali J. Almohri, Huda M. Alshanbari

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Weed detection on embedded systems using computer vision algorithms by D. Shadrin, S. Illarionova, R. Kasatov, M. Akimenkova, G. Rudensky, E. Erhan

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Evolutionary Algorithms for Edge Server Placement in Vehicular Edge Computing by A. Surayya, Md Muzakkir Hussain, V. Dinesh Reddy, Ashu Abdul, Firoj Gazi

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Clinical decision support for vestibular diagnosis: large-scale machine learning with lived experience coaching by Cecilia A. Callejas Pastor, Hyun Tae Ryu, Jung Sook Joo, Yunseo Ku, Myung-Whan Suh

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TECHNOLOGIES FOR DEVELOPING DECISION SUPPORT SYSTEMS FOR THE DIAGNOSIS OF BLOOD DISORDERS USING CONVOLUTIONAL NEURAL NETWORKS by U. V. Maslikova, A. A. Supilnikov

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Does a Meta-Combining Method Lead to More Accurate forecasts in the decision-making process? by Emrah Gulay, Serkan Aras

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Sparse transformer and multipath decision tree: a novel approach for efficient brain tumor classification by Pengcheng Li, Yuqi Jin, Monan Wang, Fengjie Liu

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Thematic Analysis of Clinician Documentation Surrounding Treatment Discussions and Decision‐Making in Patients With Desmoid Tumors by Victoria Wytiaz, Tianyi Wang, Scott Schuetze, Nina J. Francis‐Levin, Rashmi Chugh

“…The rarity of desmoid tumors and the inability to accurately predict their natural history lead to challenges in developing treatment algorithms or formulaic discussions to address treatment options with patients. …”
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Enhancing decision-making on detractor-causing failures: an approach combining data mining and machine learning by Yuri A. V. da Silva, Geraldo Cardoso de Oliveira Neto, Gustavo Lima, Sidnei A. de Araújo, Rodrigo Neri Bueno da Silva, Francisco Elanio Bezerra, Marlene Amorim

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