Hub

What history can teach us about AI

As the AI era unfolds around us, Johns Hopkins' historians Angus Burgin and Louis Hyman reflect on lessons learned from the ...
Michigan Technological University

Michigan Tech Experts Model the Future of Data Science

Data science is everywhere, a driving force behind modern decisions. When a streaming service suggests a movie, a bank sends ...
PsycheOpinion

Why chatbot therapists can’t offer what we need

Today’s world is fuelling a craving to be truly seen by another – and that’s exactly what AI therapists can’t ever deliver ...
IEEE

Constant Voltage and Constant Current Control Strategy for WPT Systems Based on Dynamic Programming Reinforcement Learning Algorithm

Abstract: Different kinds of compensation topologies in wireless power transfer (WPT) systems usually can only achieve constant voltage (CV) or constant current (CC) output at the same time when the ...
IEEE

Economically Optimal Power Flow Management of Grid-Connected Photovoltaic Microgrid Based on Dynamic Programming Algorithm and Grid I/O Strategy for Different Weather Scenarios

Abstract: This paper proposes an economically optimal energy management approach for grid-connected photovoltaic microgrid. The approach is derived based on the dynamic programming algorithm and grid ...
Frontiers

Distributed hierarchical control of islanded active distribution networks with dynamic consensus algorithm and adaptive virtual impedance

In the event of an upstream grid fault, the Active Distribution Network (ADN) can switch to autonomous operation, coordinating controllable Distributed Generators (DGs) and Energy Storage Systems (ESS ...