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Artificial Brain Releases New Quantum Algorithm to Find Optimal Locations for EV Charging Stations

Electric vehicle charging, close-up
Electric vehicle charging, close-up
Artificial Brain’s quantum algorithm helps customers identify optimal locations for placing electric vehicle charging stations. (Image: Envato)

PRESS RELEASE — As the number of electric vehicles grows, the placement of electric vehicle charging stations will become a major optimization challenge. Due to the rapid adoption of electric vehicles, there is a need for more charging stations and even to convert existing gas stations to electric charging stations.

Novel Quantum Algorithm
​Artificial Brain, a quantum computing company that is developing hybrid quantum-classical algorithms to solve complex business problems in the fields of Energy, Aviation, Finance, and Climate change has announced its success in developing a novel algorithm that helps customers to identify optimal locations for placing electric vehicle charging stations by using quantum computers.

The proposed algorithm solves this problem by considering the point of interest (POI) and already existing electric charging locations and then optimally placing new charging points to cover as many people as possible. 

This novel quantum algorithm returns result from an actual quantum computer in less than 3 seconds for 8543811434435330 (8.5 * 10^15) combinations.

Demo: http://tinyurl.com/EV-Quantum-Demo

Novel Quantum + Genetic Algorithm Framework
Artificial Brain has also created a novel framework by combining quantum computing and genetic algorithms that can provide better results (as high as 40%) than vanilla quantum computing for specific use cases such as EV location optimization, etc.

Research paper: https://tinyurl.com/EV-Quantum-Paper

Future Developments
Artificial Brain plans to modify this novel quantum algorithm to find optimal locations for wind and solar farms, as well as for other sustainability use cases.

The Future of Materials Discovery: Reducing R&D Costs significantly with GenMat’s AI and Machine Learning Tools

When: July 13, 2023 at 11:30am

What: GenMat Webinar

Jake Vikoren

Jake Vikoren

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Deep Prasad

Deep Prasad

Company Speaker

Araceli Venegas

Araceli Venegas

Company Speaker

Matt Swayne

With a several-decades long background in journalism and communications, Matt Swayne has worked as a science communicator for an R1 university for more than 12 years, specializing in translating high tech and deep tech for the general audience. He has served as a writer, editor and analyst at The Quantum Insider since its inception. In addition to his service as a science communicator, Matt also develops courses to improve the media and communications skills of scientists and has taught courses. [email protected]

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The Future of Materials Discovery: Reducing R&D Costs significantly with GenMat’s AI and Machine Learning Tools

When: July 13, 2023 at 11:30am

What: GenMat Webinar

Jake Vikoren

Jake Vikoren

Company Speaker

Deep Prasad

Deep Prasad

Company Speaker

Araceli Venegas

Araceli Venegas

Company Speaker

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