Robotics & Machine Learning Daily News2024,Issue(Jul.1) :100-101.

Studies from Chongqing University Yield New Information about Machine Learning ( Forward and Reverse Design of Adhesive In Batteries Via Dynamics and Machine Lea rning Algorithms for Enhanced Mechanical Safety)

重庆大学的研究提供了关于机器学习的新信息(通过动力学和机器学习算法实现电池粘合剂的正向和逆向设计以增强机械安全性)

Robotics & Machine Learning Daily News2024,Issue(Jul.1) :100-101.

Studies from Chongqing University Yield New Information about Machine Learning ( Forward and Reverse Design of Adhesive In Batteries Via Dynamics and Machine Lea rning Algorithms for Enhanced Mechanical Safety)

重庆大学的研究提供了关于机器学习的新信息(通过动力学和机器学习算法实现电池粘合剂的正向和逆向设计以增强机械安全性)

扫码查看

摘要

一位新闻记者兼机器人与机器学习每日新闻的工作人员新闻编辑在一份新的报告中讨论了机器学习的研究结果。根据《新闻周刊》编辑在重庆发表的新闻报道,研究称,“电动汽车的日益普及给电池行业带来了机遇和挑战。设计人员需要开发可靠的电池组,以确保消费者财产和乘客生命安全。”本研究经费来源于国家自然科学基金(NSFC)。

Abstract

By a News Reporter-Staff News Editor at Robotics & Machine Learning Daily News – Research findings on Machine Learning are discuss ed in a new report. According to news reporting out of Chongqing, People’s Repub lic of China, by NewsRx editors, research stated, “The growing popularity of ele ctric vehicles brings opportunities and challenges to the battery industry. Desi gners need to develop reliable battery packs to ensure the safety of consumers’ property and passengers’ lives.” Financial support for this research came from National Natural Science Foundatio n of China (NSFC).

Key words

Chongqing/People's Republic of China/A sia/Algorithms/Cyborgs/Emerging Technologies/Machine Learning/Chongqing Uni versity

引用本文复制引用

出版年

2024
Robotics & Machine Learning Daily News

Robotics & Machine Learning Daily News

ISSN:
段落导航相关论文