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Titlebook: Hybrid ArtificialIntelligent Systems, Part II; 5th International Co Emilio Corchado,Manuel Gra?a Romay,Alexandre Manha Conference proceedin

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41#
發(fā)表于 2025-3-28 17:13:05 | 只看該作者
P. C. Pop,O. Matei,C. Pop Sitar,C. Chirag Data including the main characteristics volume, velocity and variety. Thereafter, we discuss data pipelines and the Big Data Value (BDV) Reference Model that is referred to repeatedly in the book. The layered reference model ranges from data acquisition from sensors up to visualization and user in
42#
發(fā)表于 2025-3-28 20:16:09 | 只看該作者
43#
發(fā)表于 2025-3-29 02:06:32 | 只看該作者
Laura Cruz Reyes,Carlos Alberto Ochoa Ortíz Zezzatti,Claudia Gómez Santillán,Paula Hernández Hernándous flow, are often accompanied by dire need for real-time processing. One aspect of data streams deals with storage management and processing of continuous queries for aggregation. Another significant aspect pertains to discovery and understanding of hidden patterns to derive actionable knowledge u
44#
發(fā)表于 2025-3-29 05:29:31 | 只看該作者
E. A. de la Cal,E. M. Fernández,R. Quiroga,J. R. Villar,J. Sedanohavior in an ideal mathematical optimization framework and had dominated orthodox economics for a substantial period of the entire twentieth century, would “evolve” into the paradigm of . which emphasizes the consideration of the psychological, cultural, and social factors that constrain a human’s r
45#
發(fā)表于 2025-3-29 09:36:53 | 只看該作者
Ander Garcia,Olatz Arbelaitz,Pieter Vansteenwegen,Wouter Souffriau,Maria Teresa Linaza stands to revolutionize Computational Social Science and Humanities. Increasingly we live in a quantitative world. The ability to read, store, and manipulate larger and larger amounts of data is becoming a prerequisite to be on the cutting edge of research. Econometric methods utilizing big data an
46#
發(fā)表于 2025-3-29 14:13:17 | 只看該作者
SIFT-SS: An Advanced Steady-State Multi-Objective Genetic Fuzzy System,jective genetic fuzzy systems (MOGFS) has capture the attention of the fuzzy community. Despite the good results obtained, most of existent MOGFS are based on a gross usage of the classic multi-objective algorithms. This paper takes an existent MOGFS and improves its convergence by modifying the und
47#
發(fā)表于 2025-3-29 17:06:30 | 只看該作者
48#
發(fā)表于 2025-3-29 21:15:21 | 只看該作者
49#
發(fā)表于 2025-3-30 02:13:51 | 只看該作者
Analysis of the Effectiveness of G3PARM Algorithm,ARM, uses an auxiliary population made up of its best individuals that will then act as parents for the next generation. The individuals are defined through a context-free grammar and it allows us to obtain datatype-generic and valid individuals. We compare our approach to . and . algorithms and dem
50#
發(fā)表于 2025-3-30 06:21:19 | 只看該作者
Reducing Dimensionality in Multiple Instance Learning with a Filter Method,tance learning is considered an extension of traditional supervised learning where each example is made up of several instances and there is no specific information about particular instance labels. In this scenario, traditional supervised learning can not be applied directly and it is necessary to
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