Results 161 to 170 of about 613,158 (317)

Adaboost with SVM-Based Classifier for the Classification of Brain Motor Imagery Tasks [PDF]

, 2011
Jue Wang, Lin Gao, Haoshi Zhang, Jin Xu
openalex   +1 more source

Artificial Intelligence‐Driven Insights into Electrospinning: Machine Learning Models to Predict Cotton‐Wool‐Like Structure of Electrospun Fibers

Advanced Intelligent Discovery, EarlyView.
Electrospinning allows the fabrication of fibrous 3D cotton‐wool‐like scaffolds for tissue engineering. Optimizing this process traditionally relies on trial‐and‐error approaches, and artificial intelligence (AI)‐based tools can support it, with the prediction of fiber properties. This work uses machine learning to classify and predict the structure of
Paolo D’Elia, Giovanna Pappalardo, Aldo R. Boccaccini, Liliana Liverani   +3 more
wiley   +1 more source

Aeronautical γ Spectrum Noise Reduction Method Based on LS-SVM Segmentation Regression

, 2019
Ying Ci, Jun Liu, Lei Chen, Guang Li, Feng Yang   +4 more
openalex   +1 more source

Retracted: Risk Evaluation on China Government Bonds with EWMAVaR and SVM Methods [PDF]

, 2023
Security and Communication Networks
openalex   +1 more source

Artificial Intelligence for Bone: Theory, Methods, and Applications

Advanced Intelligent Discovery, EarlyView.
Advances in artificial intelligence (AI) offer the potential to improve bone research. The current review explores the contributions of AI to pathological study, biomarker discovery, drug design, and clinical diagnosis and prognosis of bone diseases. We envision that AI‐driven methodologies will enable identifying novel targets for drugs discovery. The
Dongfeng Yuan, Haicang Zhang, Liping Tong, Di Chen   +3 more
wiley   +1 more source

Topology‐Aware Machine Learning for High‐Throughput Screening of MOFs in C8 Aromatic Separation

Advanced Intelligent Discovery, EarlyView.
We screened 15,335 Computation‐Ready, Experimental Metal–Organic Frameworks (CoRE‐MOFs) using a topology‐aware machine learning (ML) model that integrates structural, chemical, pore‐size, and topological descriptors. Top‐performing MOFs exhibit aromatic‐enriched cavities and open metal sites that enable π–π and C–H···π interactions, serving as ...
Yu Li, Honglin Li, Jialu Li, Wan‐Lu Li
wiley   +1 more source

Large Language Model in Materials Science: Roles, Challenges, and Strategic Outlook

Advanced Intelligent Discovery, EarlyView.
Large language models (LLMs) are reshaping materials science. Acting as Oracle, Surrogate, Quant, and Arbiter, they now extract knowledge, predict properties, gauge risk, and steer decisions within a traceable loop. Overcoming data heterogeneity, hallucinations, and poor interpretability demands domain‐adapted models, cross‐modal data standards, and ...
Jinglan Zhang, Xinyi Chen, Xu Ye, Yulin Yang, Bin Ai   +4 more
wiley   +1 more source

Utilizing spatial artificial intelligence to develop pavement performance indices: a case study. [PDF]

Sci Rep
Milad A, Ali AA, Al-Sulaimi ZS, Al-Kindi KM.   +3 more
europepmc   +1 more source

Comparative Study of SVM Methods Combined with Voxel Selection for Object Category Classification on fMRI Data

, 2011
Sutao Song, Zhichao Zhan, Zhiying Long, Jiacai Zhang, Yao Li   +4 more
openalex   +2 more sources

SVM-based analysis and prediction on network traffic [PDF]

, 2007
Weidong Luo, Xingwei Liu, Jian Zhang
openalex   +1 more source