Results 141 to 150 of about 176,187 (274)

GWKNN: an enhanced k-nearest neighbor algorithm with G metric reconstruction and Grey Wolf Optimizer. [PDF]

Sci Rep
Guo Z, Liu G, Liu W, Ni Z, Jiang F.
europepmc   +1 more source

KB-CB-N classification: towards unsupervised approach for supervised learning [PDF]

, 2011
Abdallah, Z., Gaber, M.
core   +1 more source

AI‐based localization of the epileptogenic zone using intracranial EEG

Epilepsia Open, EarlyView.
Abstract Artificial intelligence (AI) is rapidly transforming our lives. Machine learning (ML) enables computers to learn from data and make decisions without explicit instructions. Deep learning (DL), a subset of ML, uses multiple layers of neural networks to recognize complex patterns in large datasets through end‐to‐end learning.
Atsuro Daida, Yipeng Zhang, Sotaro Kanai, Richard Staba, Vwani Roychowdhury, Hiroki Nariai   +5 more
wiley   +1 more source

Giant photostriction rate for remote opto-ultrasonic structural health monitoring. [PDF]

Nat Commun
Yin J, Yang Y, Shi X, Zhao C, Lin C, Tao H, Zhang Y, Lim DBK, Jiang C, Lei L, Song Y, Wu H, Ding X, Sun J, Li F, Wu J, Yao K.   +16 more
europepmc   +1 more source

Artificial intelligence in preclinical epilepsy research: Current state, potential, and challenges

Epilepsia Open, EarlyView.
Abstract Preclinical translational epilepsy research uses animal models to better understand the mechanisms underlying epilepsy and its comorbidities, as well as to analyze and develop potential treatments that may mitigate this neurological disorder and its associated conditions. Artificial intelligence (AI) has emerged as a transformative tool across
Jesús Servando Medel‐Matus, Cesar Santana‐Gomez, Ruby G. Escalante, Dominique Duncan, Pedro F. Viana, Giulia Sofia Cereda, Naoto Kuroda, Aristea S. Galanopoulou   +7 more
wiley   +1 more source

A Hybrid Fuzzy–Support Vector Machine Framework for Real‐Time Dust Detection and Thermal Mapping in Photovoltaic Panels

Energy Science &Engineering, EarlyView.
A hybrid Fuzzy–SVM framework for real‐time dust detection and thermal mapping in PV panels. ABSTRACT Dust accumulation significantly degrades the energy output of photovoltaic (PV) panels, particularly in arid and semi‐arid regions. While existing studies have separately explored image‐based dust detection, environmental modeling, and machine learning (
Debasish Sarker, S. M. Rezaul Karim, MD. Shouquat Hossain, Md. Moshaddek Hossain, Md. Monirul Kabir   +4 more
wiley   +1 more source

Intent Arabic text categorisation based on different machine learning and term frequency

IET Networks, EarlyView., 2022
Abstract The complexity of Internet network configurations has made managing networks a complicated undertaking. Intent‐Based Networking (IBN) is a potential solution to this issue. In contrast to conventional networks, where a concrete description of the settings typically conveys a network administrator's goal kept on each device, an administrator's ...
Mohammad Fadhil Mahdi, Mahmoud Shuker Mahmoud   +1 more
wiley   +1 more source

B-kNN to Improve the Efficiency of kNN

Proceedings of the 6th International Conference on Data Science, Technology and Applications, 2017
Lunjin Lu, Dae-Kyoo Kim, Dhrgam AL Kafaf
openaire   +1 more source

Real‐Time Data‐Driven Fault Diagnosis of Photovoltaic Arrays Using an Edge‐Server Machine‐Learning Framework

Energy Science &Engineering, EarlyView.
A real‐time, data‐driven framework detects and classifies photovoltaic array faults using edge sensing and server‐side machine learning. Ensemble tree models achieve near‐perfect accuracy with low latency, enabling practical, low‐cost deployment for reliable PV monitoring and intelligent maintenance.
Premkumar Manoharan, Sowmya Ravichandran, Deepak Kumar Sinha, Chandran Ramakrishnan, Omar Almomani   +4 more
wiley   +1 more source

Parametric design method of building structured cabling system oriented to data mining

IET Networks, EarlyView., 2022
This paper puts forward the method of secondary development and design software through the research of building structured cabling system (SCS), and uses data mining technology to carry out parametric design of building SCS. Then, the feasibility of the design is tested by comparing the data of the traditional design and the parametric design ...
Bing Wang, Wei Yue
wiley   +1 more source