Physics-informed neural networks: a deep learning framework for solving forward and inverse problems involving nonlinear partial differential equations J Comput Phys, 378 (2019), pp. 686-707 View PDFView articleView in ScopusGoogle Scholar [46] J.W. Taylor, R. Buizza Neural network load forecast...
FeDN2: Fuzzy-Enhanced Deep Neural Networks for Improvement of Sentence-Level Sentiment AnalysisNgoc-Thanh.Nguyen@pwr.edu.plNgoc Thanh NguyenDinh Tai PhamHuyen Trang Phan
Adaptive neuro-fuzzy inference system ANN: Artificial neural networks BMA: Bayesian model averaging CGR: Corrected gamma ray DL: Deep learning DT: Sonic transition time DT: Decision tree FNO: Fourier neural operator GBM: Generalized boosted regression models GMDH: Group method of data ...
Deep convolutional neural networks with Bee Collecting Pollen Algorithm (BCPA)-based landslide data balancing and spatial prediction. Journal of Intelligent and Fuzzy Systems, 2024, 46(1): 597-617. DOI:10.3233/JIFS-234924 51. Kucuker, D.M.. Analyzing landslide susceptibility of forest roads ...
- 《Physics in Medicine & Biology》 被引量: 43发表: 2013年 Local bone enhancement fuzzy clustering for segmentation of MR trabecular bone images Segmentation of trabecular bone from magnetic resonance (MR) images is a challenging task due to spatial resolution limitations, signal-to-noise ratio ...
Informed by the quantification of uncertainty and the related statistical quantities, we present the Scalable Windowing Approach for Pairwise-similarity Search (SWAPS) algorithm. SWAPS utilises the expected mean, E[ϕ](meanbase), and the variance, varbase, as baseline parameters to regulate its ...
The non-linearity of these variables and energy consumption has led to the creation of intelligent solutions, such as evolutionary computation, fuzzy models, neural networks, and convolutional neural networks for non-linear analysis and simulation. Modeling energy usage is typically based on the ...
Fuzzy system based medical image processing for brain disease prediction. Front. Neurosci. 2021, 15, 714318. [Google Scholar] [CrossRef] Kleesiek, J.; Urban, G.; Hubert, A.; Schwarz, D.; Maier-Hein, K.; Bendszus, M.; Biller, A. Deep MRI brain extraction: A 3D convolutional ...
Deep Learning Toolbox™ provides functions, apps, and Simulink®blocks for designing, implementing, and simulating deep neural networks. The toolbox provides a framework to create and use many types of networks, such as convolutional neural networks (CNNs) and transformers. You can visualize and...
We introduce an adaptive fuzzy logic deep-learning equalizer (AFL-DLE) for 64 QAM-CAP modulated UVLC systems dependent on complex-valued neural networks and a constellation partitioning algorithm to overwhelm the linear and nonlinear imperfections in UVLC. The system’s efficiency is improved by utili...