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T
Tao Li
H-index:10
Citation Count:443
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End-to-end deep reinforcement learning enables bionic fish to learn efficient obstacle avoidance in unknown underwater environments
端到端深度强化学习使仿生鱼能够在未知水下环境中学习高效的障碍物规避。
AIP ADVANCES
IF1.4
AgBr/TiO2/g-C3N4 ternary composites with dual Z-scheme heterojunction for efficient removal of organic dye
AgBr/TiO2/g-C3N4双Z型异质结三元复合材料用于高效去除有机染料
Spider web-structured Sb2MoO6@C@CNF composites with conductive-stable dual carbon skeletons toward durable sodium-ion batteries
蛛网结构Sb2MoO6@C@CNF复合材料，具有导电-稳定双碳骨架，用于耐用的钠离子电池
CrystEngComm
IF2.6
A hybrid immersed boundary-lattice Boltzmann method for flow and heat transfer within a fluid heat exchanger
一种用于流体换热器内流动与传热的混合浸没边界-格子玻尔兹曼方法
PHYSICS OF FLUIDS
IF4.3
Simulating fish autonomous swimming behaviours using deep reinforcement learning based on Kolmogorov-Arnold Networks
基于kolmogorov-arnold网络的深度强化学习模拟鱼类自主游泳行为
