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Computational Methods and Application in Machine Learning

“…Machine learning is an interdisciplinary subject involving probability theory, statistics, approximation theory, convex analysis, optimization, algorithm complexity theory, etc. It focuses on how computers simulate or realize human learning behaviors in order to obtain new knowledge or skills. …”
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10th Anniversary of Technologies-Recent Advances and Perspectives

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Today's TBB 著者: Voss, Michael J., Reinders, James R.

“…It then introduces the major components of TBB including parallel algorithms, flow graphs, and task groups that help you fully leverage the power of multicore systems. …”
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Advances in Artificial Intelligence

“…This issue also explores developments in natural language processing and multimodal data analysis, alongside optimization strategies inspired by evolutionary algorithms and probabilistic models, such as Gaussian processes. …”
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Mathematics in Robot Control for Theoretical and Applied Problems

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Smart Wearable Technology: Thermal Management and Energy Applications

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Future Civil Engineering

“…From high-precision breakthroughs in thermodynamic, non-destructive testing to the discovery of vibration enhancement mechanisms for UHPC and from high-strength composite material performance optimization models to a 20% accuracy leap in dynamic monitoring algorithms, every technological innovation point leading to the reconstruction of the entire lifecycle effectiveness of infrastructure was analyzed. …”
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Automatic Code Generation for Massively Parallel Applications in Computational Fluid Dynamics 著者: Kuckuk, Sebastian

“…As domain, we choose PDE solvers and, in particular, those from the group of geometric multigrid methods. …”
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Recent Advances in Chaos, Fractal and Complex Dynamics in Nonlinear Systems

“…The topics include new methods for detecting chaos, novel types of attractors (including hidden attractors), fractal features in fractional-order systems, and the applications of chaotic and fractal dynamics in areas such as secure communication and optimization algorithms. We hope that this reprint will serve as a valuable reference for researchers and practitioners engaged in the study of nonlinear systems, and in particular, those exploring chaos theory, bifurcation analysis, fractal geometry, and the complex behavior of emerging dynamical models.…”
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Minimal Spanning Tree Algorithm Applied to the Implementation of an Efficient Isolation Forest for Anomaly Detection 著者: Gałka, Łukasz

“…Within this review, particular emphasis is placed on those publications focused on the improvements and extensions of the basic IF algorithm. …”
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New Perspectives on Optimization Algorithms Research

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Machine Learning for Pattern Recognition (2nd Edition)

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Distributed Energy Resources Management 著者: Faria, Pedro

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Entropy Measures for Data Analysis: Theory, Algorithms and Applications 著者: Keller, Karsten

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Green, Energy-Efficient and Sustainable Networks

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Intelligent Control in Energy Systems 著者: Dounis, Anastasios

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Management and evolution of the European Union member states in the Big Data era. The impact of Big Data on the organization of the European market 著者: Constantin, Anghelache, Ghislaine, Pellat

“…New behaviors are observed on the markets thanks to algorithmic optimizations or via the technology of the “Blockchain”. …”
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Quantitative Biology: Dynamics of Living Systems 著者: Noriko Hiroi, Douglas B. Murray, Viji M. Draviam, Chun-Biu Li, Hiroaki Takagi, Ziya Kalay, Tetsuya J. Kobayashi, Akira Funahashi, Akatsuki Kimura, Rinshi S. Kasai, Naoki A. Irie, Jason Edward Shoemaker

“…With the emergence of Systems Biology, there is a greater realization that the whole behavior of a living system may not be simply described as the sum of its elements. …”
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Computational Simulations and Applications

“…The purpose of this book is to introduce researchers and graduate students to a broad range of applications of computational simulations, with a particular emphasis on those involving computational fluid dynamics (CFD) simulations. …”
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Computational Methods for the Analysis of Genomic Data and Biological Processes

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