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Advancements in Machine Learning for Microrobotics in Biomedicine
Microrobotics is an innovative technology with great potential for noninvasive medical interventions. However, controlling and imaging microrobots pose significant challenges in complex environments and in living organisms. This review explores how machine learning algorithms can address these issues, offering solutions for adaptive motion control and ...
Amar Salehi+6 more
wiley +1 more source
An improved multiple adaptive neuro fuzzy inference system based on genetic algorithm for energy management system of island microgrid. [PDF]
Cheng Y+6 more
europepmc +1 more source
The use of image quality metrics in combination with machine learning enables automatic image quality assessment for fluorescence microscopy images. The method can be integrated into the experimental pipeline for optical microscopy and utilized to classify artifacts in experimental images and to build quality rankings with a reference‐free approach ...
Elena Corbetta, Thomas Bocklitz
wiley +1 more source
Optimizing weak grid integrated wind energy systems using ANFIS-SRF controlled DSTATCOM. [PDF]
Ramana PV, Rosalina KM.
europepmc +1 more source
The systematic design of memristor‐based neural network is provided by analog conductance state parameters to accurately emulate the software‐based high‐resolution weight at discrete device level. The requirement of discrete analog conductance of memristor device is measured as ≈50 states with nonlinearity value of ≈0.142 within the deviation range of ...
Jingon Jang, Yoonseok Song, Sungjun Park
wiley +1 more source
Adaptive fuzzy-PI controlled dynamic voltage restorer for mitigating voltage sags. [PDF]
Mallick N+5 more
europepmc +1 more source
Sliding Mode Control Based on Fuzzy Model for Active Magnetic Bearing System.
許 有志, 野波 健蔵
openalex +2 more sources