Computational Sciences and Artificial Intelligence in Industry
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Computational Sciences and Artificial Intelligence in Industry

Computational Sciences and Artificial Intelligence in Industry


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About the Book

  • Novel strategies for data-driven evolutionary optimization
  • Machine learning using distance-based methods
  • Counting cells and predicting immunoscore using gradient boosted convolutional neural networks
  • Kubelka-Munk model and stochastic model comparison in skin physical parameter retrieval using neural networks
  • A combined approach of neural networks and graphical models in skin cancer inference using spectral imaging
  • Using wave propagation simulations and convolutional neural networks to retrieve thin coating's thickness from hyperspectral images
  • Predicting future overweight and obesity from childhood growth data: A case study
  • Variable selection under a value acquisition budget
  • Stochastic approximation by successive piecewise linearization
  • Non-convex robust low-rank matrix recovery
  • Neural network learning via successive piecewise linearization
  • Learning for scientific computing purposes
  • Computational intelligence in design of new nanomaterials
  • Modeling flow, reactive transport and geomechanics in porous media
  • Physics constrained machine learning for industrial applications
  • Parameter and type identification in partial differential equations using deep neural networks
  • Stability maximization for layered moving web with total mass constraint
  • Similarity solutions for condensation on a non-isothermal vertical plate
  • Enhanced topology optimization approach using moving morphable components coupled with NURBS curves
  • Combined model order reduction and artificial neural network for data assimilation and damage detection in structures
  • Towards the optimization of fuzzy pattern trees by abs - linearization
  • Support vector machines in clusterwise linear regression
  • A Second-order method with enriched hessian information for composite sparse optimization problems
  • Missing value imputation via nonsmooth optimization and clusterwise linear regression
  • Parsimonious neural networks
  • Nobody can stop advancing artificial intelligence (AI) where developing
  • Computational sciences, physics field theories and geometry
  • Mini-symposium on ethics in AI
  • Essentializing software engineering practices for ethically designing and developing artificial intelligence systems 30 Ethics is important, but how can we implement it? Survey on software developers' views on AI ethics
  • Industrial IoT capabilities in reducing the LCOE of offshore wind energy: A review
  • High-Performance data analysis with the Helmholtz Analytics Toolkit (HeAT)
  • Dynamic data-driven application systems based on tensor factorization: learning the physics of model evolution
  • Predicting customer experience
  • Puhti-AI: Finland's new AI supercomputer
  • Using Artificial Intelligence to Classify Textual Applications for Reporting Purposes Application of machine learning methods to error control of approximate solutions
  • Iterative data selection strategy in offline data-driven evolutionary multiobjective optimization
  • On surrogate management in interactive multiobjective building energy system design
  • A modified deep neural network for the rapid inversion of geo-physical resistivity measurements
  • Using agents for automatic meta-modelling algorithm selection in data-driven multiobjective optimization problems
  • Future cooperation between Computational Science and AI in Industrial and Societal Applications - challenges, impact and expectations?
  • Artificial Intelligence, Deep Lea


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Product Details
  • ISBN-13: 9783030707866
  • Publisher: Springer International Publishing
  • Publisher Imprint: Springer
  • Height: 234 mm
  • No of Pages: 275
  • Series Title: Intelligent Systems, Control and Automation: Science and Eng
  • Sub Title: New Digital Technologies for Solving Future Societal and Economical Challenges
  • Width: 156 mm
  • ISBN-10: 3030707865
  • Publisher Date: 28 Aug 2021
  • Binding: Hardback
  • Language: English
  • Returnable: Y
  • Spine Width: 18 mm
  • Weight: 634 gr


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