Smart Urban Energy Systems: Data Layer

Related lectures (32)

Page 3 of 4

Explores optimization and approximation in deep neural networks, including optimal control and numerical experiments.

Delves into solving the XOR problem using a two-layer neural network.

Covers the Runge-Kutta method and its variations, discussing error minimization and stability in non-linear systems.

Covers the precise description of the relative positioning of objects in space.

Covers the practical use of QGIS for spatial data analysis and visualization, including georeferencing historical maps and manipulating vector data.

Explores the shift pathway in smart urban transportation systems, focusing on new mobility services and their integration.

Explores water consumption data in Geneva, including charts on consumption and losses, available datasets, and data processing phases.

Explores improper integrals, convergence criteria, comparison theorems, and solid revolution.

Explores vector-vector interactions, SQL queries, QGIS functions, cutting operations, and boolean operations in geographic information analysis.

Explores two-layer neural networks and backpropagation for learning feature spaces and approximating continuous functions.