[HTML][HTML] Household standards and socio-economic aspects as a factor determining energy consumption in the city
Political or economic attempts to mitigate climate change by increasing fossil fuel prices lead
to and an increase in energy poverty, ie, social effects. The ideal solution would be to …
to and an increase in energy poverty, ie, social effects. The ideal solution would be to …
Using OpenStreetMap data and machine learning to generate socio-economic indicators
D Feldmeyer, C Meisch, H Sauter… - … International Journal of …, 2020 - mdpi.com
Socio-economic indicators are key to understanding societal challenges. They disassemble
complex phenomena to gain insights and deepen understanding. Specific subsets of …
complex phenomena to gain insights and deepen understanding. Specific subsets of …
Methodology for processing of 3D multibeam sonar big data for comparative navigation
Autonomous navigation is an important task for unmanned vehicles operating both on the
surface and underwater. A sophisticated solution for autonomous non-global navigational …
surface and underwater. A sophisticated solution for autonomous non-global navigational …
Methodology for develo** a combined bathymetric and topographic surface model using interpolation and geodata reduction techniques
J Lubczonek, M Wlodarczyk-Sielicka, M Lacka… - Remote Sensing, 2021 - mdpi.com
The research in this paper is concerned with the development of a continuous elevation
model in the coastal zones of inland waters. The source data for the creation of numerical …
model in the coastal zones of inland waters. The source data for the creation of numerical …
Soft trees with neural components as image-processing technique for archeological excavations
M Woźniak, D Połap - Personal and Ubiquitous Computing, 2020 - Springer
There are situations when someone finds a certain object or its remains. Particularly the
second case is complicated, because having only a part of the element, it is difficult to …
second case is complicated, because having only a part of the element, it is difficult to …
Processing of bathymetric data: The fusion of new reduction methods for spatial big data
M Wlodarczyk-Sielicka, W Blaszczak-Bak - Sensors, 2020 - mdpi.com
Floating autonomous vehicles are very often equipped with modern systems that collect
information about the situation under the water surface, eg, the depth or type of bottom and …
information about the situation under the water surface, eg, the depth or type of bottom and …
[HTML][HTML] Metaheuristic Algorithm and Laser Projection for Adjusting the Model of the Last Lower Surface to a Footprint
JAM Rodríguez - Biomimetics, 2024 - mdpi.com
Nowadays, metaheuristic algorithms have been applied to optimize last lower-surface
models. Also, the last lower-surface model has been adjusted through the computational …
models. Also, the last lower-surface model has been adjusted through the computational …
The reduction method of bathymetric datasets that preserves true geodata
Water areas occupy over 70 percent of the Earth's surface and are constantly subject to
research and analysis. Often, hydrographic remote sensors are used for such research …
research and analysis. Often, hydrographic remote sensors are used for such research …
[PDF][PDF] Research and applications of artificial neural networks in spatial analysis
I Garczyńska - Zeszyty Naukowe Akademii Morskiej w Szczecinie, 2023 - bibliotekanauki.pl
The conducted review presents the possibility of using artificial neural networks in sectors
related to environmental protection, agriculture, forestry, land uses, groundwater and …
related to environmental protection, agriculture, forestry, land uses, groundwater and …
Collaborative learning with taboos for machine learning methods in big data problems
D Połap, M Woźniak - 2020 IEEE Symposium Series on …, 2020 - ieeexplore.ieee.org
The practical application of artificial intelligence methods has two big disadvantages. The
first one is the amount of data needed to train models, and the other one is the lack of …
first one is the amount of data needed to train models, and the other one is the lack of …