Results 201 to 210 of about 245,638 (344)

Improved many-objective particle swarm optimization based welding sequence optimization research. [PDF]

PLoS One
Dong L, Gu S, Dong J, Ji Q, Liu J.
europepmc   +1 more source

What to Make and How to Make It: Combining Machine Learning and Statistical Learning to Design New Materials

Advanced Intelligent Discovery, EarlyView.
Combining machine learning and probabilistic statistical learning is a powerful way to discover and design new materials. A variety of machine learning approaches can be used to identify promising candidates for target applications, and causal inference can help identify potential ways to make them a reality.
Jonathan Y. C. Ting, Amanda S. Barnard
wiley   +1 more source

Fuzzy energy management using a chaotic model to improve fuel consumption of fuel cell-battery hybrid fixed-wing UAVs operating under uncertainty control. [PDF]

Sci Rep
Rostami M, Habibi P, Farajollahi A.
europepmc   +1 more source

Optimization of Threshing Quality Control Strategy Based on Type-2 Fuzzy Logic Controller

, 2020
Baoyan Xu, Xindong Ni, Yüan Wang, Yuxiang Wang, Yehong Liu, Xin Wang   +5 more
openalex   +2 more sources

A Solution for Exosome‐Based Analysis: Surface‐Enhanced Raman Spectroscopy and Artificial Intelligence

Advanced Intelligent Discovery, EarlyView.
Exosomes are emerging as powerful biomarkers for disease diagnosis and monitoring. This review highlights the integration of surface‐enhanced Raman spectroscopy with artificial intelligence to enhance molecular fingerprinting of exosomes. Machine learning and deep learning techniques improve spectral interpretation, enabling accurate classification of ...
Munevver Akdeniz, Zakarya Al‐Shaebi, Omer Aydin   +2 more
wiley   +1 more source

Artificial neural network modeling and optimization of an electrochemical biosensor for plasma miR-155-based breast cancer detection. [PDF]

Sci Rep
Imani A, Hosseinpour S, Azimzadeh M, Salehi A.   +3 more
europepmc   +1 more source

Deep Learning Prediction of Surface Roughness in Multi‐Stage Microneedle Fabrication: A Long Short‐Term Memory‐Recurrent Neural Network Approach

Advanced Intelligent Discovery, EarlyView.
A sequential deep learning framework is developed to model surface roughness progression in multi‐stage microneedle fabrication. Using real‐world experimental data from 3D printing, molding, and casting stages, an long short‐term memory‐based recurrent neural network captures the cumulative influence of geometric parameters and intermediate outputs ...
Abdollah Ahmadpour, Sara Soltanabadi Farshi, Tuanna Ozcan, Amir Mohammad Ketabchi, Alper Kiraz, Savas Tasoglu   +5 more
wiley   +1 more source

Optimizing renewable energy investments using artificial intelligence-based multi-facet fuzzy decision models. [PDF]

Sci Rep
Dinçer H, Yüksel S, Aksoy T, Hacıoğlu Ü.   +3 more
europepmc   +1 more source

CrossMatAgent: AI‐Assisted Design of Manufacturable Metamaterial Patterns via Multi‐Agent Generative Framework

Advanced Intelligent Discovery, EarlyView.
CrossMatAgent is a multi‐agent framework that combines large language models and diffusion‐based generative AI to automate metamaterial design. By coordinating task‐specific agents—such as describer, architect, and builder—it transforms user‐provided image prompts into high‐fidelity, printable lattice patterns.
Jie Tian, Martin Taylor Sobczak, Dhanush Patil, Jixin Hou, Lin Pang, Arunachalam Ramanathan, Libin Yang, Xianyan Chen, Yuval Golan, Xiaoming Zhai, Hongyue Sun, Kenan Song, Xianqiao Wang   +12 more
wiley   +1 more source

Multiple trajectory optimization and control of robotic agents using hybrid fuzzy embedded artificial intelligence technique for multi target problems. [PDF]

Sci Rep
Kumar S, Pandey KK, Parhi DR, Muni MK.
europepmc   +1 more source