Titlebook: New Trends in Disruptive Technologies, Tech Ethics, and Artificial Intelligence; The DITTET 2024 Coll Daniel H. de la Iglesia,Juan F. de Pa

Project

Ensemble Learning Models for?Wind Power Forecasting, mean absolute error, and root mean squared error, was employed to evaluate its performance in forecasting wind power time series. This evaluation was conducted at time intervals of 10, 30, 60, and 120?min for two wind farms situated in Bahia, Brazil. The findings suggest that the ensemble method,

hair-bulb

Fibrin

轉(zhuǎn)折點(diǎn)

Explaining Social Recommendations Using Large Language Modelsm’s usability and the effectiveness of explanation clarity. Our study contributes to the broader human-AI interaction literature by outlining a novel system architecture, identifying user interaction patterns, and suggesting directions for future enhancements to improve decision-making processes in

騷動(dòng)

FLIT

中世紀(jì)

Incorporating Electric Vehicles in Strategic Management or Value Creation Initiatives with a Focus o need for innovation strategies in automotive industry organizations, consumers, and public entities to create value within a global sustainability logic. This study highlights the relationship between the electric vehicle industry and the value creation strategy and sustainability in a digital worl

IRATE

注意力集中

EgiCool - IoT Solution for Datacenter Environmental Control and Energy Consumption MonitoringIoT, stored in AWS DynamoDB, processed and presented in a web application. We concluded the first phase of development of the proposed IoT solution with the construction of a prototype and a feasibility study analysis.

幼兒

New Trends in Disruptive Technologies, Tech Ethics, and Artificial IntelligenceThe DITTET 2024 Coll