Titlebook: Disruptive Information Technologies for a Smart Society; Proceedings of the 1 Miroslav Trajanović,Nenad Filipović,Milan Zdravkov Conference

礼节

The outcomes of the different methods are discussed with domain experts. It was concluded that PCA, Isolation Forest and Hotelling method provide relevant results. Finally, we adopt the ensemble method (selection based on the agreement of all three methods on the detected outliers) as the final approach.

不如乐死去

Inexorable

XGBoost “is All You Need”: the Case of Forecasting Transmitted Heat Energy in District Heating Systeavailability. The reduced computational demands of conventional ML approaches not only result in cost savings but also minimize the carbon footprint associated with data analysis tasks in energy systems.

Entreaty

古文字学

Conference proceedings 2024which changed the perception of the productivity and effectiveness and opened a gateway to more than ever dynamic advances in solving the important societal challenges..."Disruptive Information Technologies for a Smart Society" is the proceedings book of the 14th International Conference for Informa

肮脏

a traditional regulation curve used to manage the flow and heat exchange in the DHS secondary line based on the outside ambient temperature, with the hyperplane defined by introduced predictor features.

烦忧

cross two different scales of data. The findings demonstrate improvements in data interoperability and efficient management of smart-grid systems, contributing to the broader goal of sustainable and efficient energy use in residential communities.

MIRTH

XAI4HEAT: Towards Demand-Driven, AI Facilitated Management of District Heating Systemsa traditional regulation curve used to manage the flow and heat exchange in the DHS secondary line based on the outside ambient temperature, with the hyperplane defined by introduced predictor features.

BOAST

FLUSH

a deep neural network to build a model that integrates multispectral satellite data with in-situ measurements, the research provides a comprehensive analysis with augmented data. It demonstrates high predictive accuracy for significant water quality indicators for the Danube River. The R2-result exc