Results 221 to 230 of about 7,724,255 (252)

Reinforcement Q-Learning-Based Adaptive Encryption Model for Cyberthreat Mitigation in Wireless Sensor Networks. [PDF]

Sensors (Basel)
Premakumari SBN, Sundaram G, Rivera M, Wheeler P, Guzmán REP.   +4 more
europepmc   +1 more source

A Molecular Engineering Strategy to Fine‐Tune Phototoxicity of AIE Probes for Super‐Resolution Imaging of Mitochondrial Cristae Dynamics

Advanced Science, EarlyView.
Regulation of molecular packing, phototoxicity, and ROS output of AIE photosensitizers is achieved through carboxylation and alkyl‐chain‐length tuning. The probe designed via this strategy enables super‐resolution visualization of inner‐mitochondrial‐membrane cristae dynamics under controlled oxidative stress, and fluorescence‐lifetime imaging of ...
Kongqi Chen, Mengjie Wang, Chuen Kam, Zhiming Wang, Qinrong Zhang, Sijie Chen   +5 more
wiley   +1 more source

Comparative analysis of Q-learning, SARSA, and deep Q-network for microgrid energy management. [PDF]

Sci Rep
Ramesh S, N SB, Sathyavarapu SJ, Sharma V, A A NK, Khanna M.   +5 more
europepmc   +1 more source

Integrating Machine Learning With Constant‐Potential Simulation to Unravel Charge‐Transfer Mechanisms in Electrochemical Nitrogen Fixation

Advanced Science, EarlyView.
Integrating interpretable machine learning with the fixed‐potential method reveals a novel mechanism: the catalytic activity of the electrochemical nitrogen reduction reaction is governed by partial charge transfer, induced by variations in the intermediate potential of zero charge under constant potential.
Yufei Xue, Dushuo Feng, Yuefei Zhang, Yang Zhang, Yalong Jiao, Aijun Du, Guoping Gao   +6 more
wiley   +1 more source

A reinforcement learning approach for reducing traffic congestion using deep Q learning. [PDF]

Sci Rep
Swapno SMMR, Nobel SMN, Meena P, Meena VP, Azar AT, Haider Z, Tounsi M.   +6 more
europepmc   +1 more source

Unifying Composition and Process Design: A Heterogeneous Graph Neural Network for Discovering High‐Performance Cu Alloys

Advanced Science, EarlyView.
By overcoming the fixed‐path limitations of conventional machine learning, a heterogeneous graph neural network fundamentally reconstructs material data representation. Integrating variable processing sequences with intrinsic elemental features, this framework enables exploratory optimization across high‐dimensional spaces.
Jie Yin, Qian Lei, Wei Yan, Yue Li, Tong Xie, Shuang Zhou, Chong Wang, Bram Hoex, Qiang Long, Caoyang Jiang, Min Song, Zhou Li, Zhangwei Wang   +12 more
wiley   +1 more source

Artificial intelligence-empowered functional design of semi-transparent optoelectronic and photonic devices via deep Q-learning. [PDF]

Sci Rep
Cetinkaya C, Cokduygulular E, Aykut MY, Erkal O, Aydogmus F, Kinaci B.   +5 more
europepmc   +1 more source

An Unequal Clustering and Multi-Hop Routing Protocol Based on Fuzzy Logic and Q-Learning in WSNs. [PDF]

Entropy (Basel)
Wang Z, Duan J.
europepmc   +1 more source

A secure and efficient blockchain enabled federated Q-learning model for vehicular Ad-hoc networks. [PDF]

Sci Rep
Ahmed HA, Jasim HM, Gatea AN, Al-Asadi AAA, Al-Asadi HAA.   +4 more
europepmc   +1 more source

Inter-Spacecraft Rapid Transfer Alignment Based on Attitude Plus Angular Rate Matching Using Q-Learning Kalman Filter. [PDF]

Sensors (Basel)
Xiong K, Zhou P, Huang X.
europepmc   +1 more source