檢索結果 - differences evolution (algorithm OR algorithms)

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  1. Gradient Expectations Downing, Keith L.

    出版 2023
    “...Synthesizing critical research in neuroscience, cognitive science, and connectionism, Gradient Expectations offers unique depth and breadth of perspective on predictive neural-network models, including a grasp of predictive neural circuits that enables the integration of computational models of prediction with evolutionary algorithms....”
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  2. Medical Data Processing and Analysis

    出版 2023
    “...Using image classification or segmentation algorithms, they find a region of interest (ROI) pointing to a specific location within the given image or an outcome of interest in the form of a label pointing to a diagnosis or prognosis. ...”
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  3. Risk Management Technologies for Deep Excavations in Water-Rich Areas

    出版 2024
    主題: “...differential evolution algorithm (DE)...”
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  4. Network-on-Chip Kundu, Santanu, Chattopadhyay, Santanu

    出版 2025
    “...It describes NoC research and developments, incorporates theoretical proofs strengthening the analysis procedures, and includes algorithms used in NoC design and synthesis. In addition, it considers other upcoming NoC issues, such as low-power NoC design, signal integrity issues, NoC testing, reconfiguration, synthesis, and 3-D NoC design. ...”
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  5. New Perspectives in Optical Design

    出版 2025
    主題: “...differential evolution algorithm...”
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  6. INTEGRATIVE OPPORTUNITIES OF NATIONAL ECONOMIES

    出版 2025
    “...The fourth section proves that the digitalization of governance and the growth of the role of algorithms create new risks of the “illusion of technological neutrality”, which can level the human dimension of integration. ...”
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  7. Inteligencia Artificial Aplicada a Procesamiento de Lenguaje Natural (NLP) con Python y Machine Learning. Sangacha Tapia, Lady Mariuxi, Celi, Ricardo Javier, Acosta Guzmán, Ivan Leonel, Varela Tapia, Eleanor Alexandra

    出版 2026
    “...Chapter 1 mentions concepts and the evolution of the different branches of knowledge that encompasses artificial intelligence (AI), the understanding of NLP, machine learning, types of learning to solve problems such as supervised, unsupervised and reinforcement. ...”
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