Results 41 to 50 of about 9,482,218 (334)

SDUST2023BCO: a global seafloor model determined from a multi-layer perceptron neural network using multi-source differential marine geodetic data

Earth System Science Data
. Seafloor topography, as a fundamental marine spatial geographic information, plays a vital role in marine observation and science research. With the growing demand for high-precision bathymetric models, a multi-layer perceptron (MLP) neural network is ...
Shuai Zhou, Jinyun Guo, Hui-Ying Zhang, Yongjun Jia, Heping Sun, Xin Liu, Dechao An   +6 more
semanticscholar   +1 more source

Detail of the hyperparameters retained for Multi-layer Perceptron (MLP), convolutional neural network (ConvNet), recurrent neural network (RNN) and DeepConvLSTM.

, 2020
Detail of the hyperparameters retained for Multi-layer Perceptron (MLP), convolutional neural network (ConvNet), recurrent neural network (RNN) and DeepConvLSTM.
Tomoya Suzuki (562515), Vincent Hernandez (2286730), Gentiane Venture (4184269)   +2 more
core   +1 more source

Learning Work Function via Implicit Reasoning on Electrostatic Potential Landscapes. [PDF]

Adv Sci (Weinh)
StructPot‐CLR establishes a cross‐modal contrastive learning framework that aligns the crystal structures of 2D materials with plane‐averaged electrostatic potential landscapes for physically informed work‐function prediction. The model achieves an MAE of 0.265 eV and an R2 of 0.902 on the held‐out test set while accurately preserving key morphological
Wan H, Wu Y, Su T, Pan D.
europepmc   +2 more sources

On-Line Modelling And Forecasting Of Carbon Monoxide Concentrations Using Hybird Multilayered Perceptron Network. [PDF]

, 2005
This paper discusses on-line modelling and forecasting of carbon monoxide (CO) concentrations using Hybrid Multilayered Perceptron (HMLP) Network.
Mashor, M.Y., Ali, A.N., Sadullah, A.F., Raji, Usharani   +3 more
core   +1 more source

Prediction of maximum annual flood discharges using artificial neural network approaches

Građevinar, 2020
The applicability of artificial neural network (ANN) approaches for estimation of maximum annual flows is investigated in the paper. The performance of three neural network models is compared: multi layer perceptron neural networks (MLP_NN), generalized ...
Tugce Anilan, Sinan Nacar, Murat Kankal, Omer Yuksek   +3 more
doaj   +1 more source

Multi-Layer Perceptron Neural Network and Markov Chain Based Geospatial Analysis of Land Use and Land Cover Change

Journal of Environmental Informatics Letters, 2020
We combined multi-layer perceptron (MLP) neural network and Markov Chain (MC) modeling with object-based image analysis (OBIA) to map and predict land use and land cover (LULC) changes in Stoney Creek Watershed (SCW), British Columbia, Canada ...
L. Shen, J.-B. Li, R. Wheate, J. Yin, S. S. Paul   +4 more
semanticscholar   +1 more source

Predicting Prediabetes Using Simple a Multi-Layer Perceptron Neural Network Model

, 2023
In over 60% of patients with prediabetes, the evolution to diabetes can be stopped by changing lifestyle. Application of prediabetes criteria existing in accredited guidelines is very useful, representing an effective way to avoid prediabetes and diabetes. Although these guidelines imposed by the international diabetes federation are constantly updated,
Oana Vîrgolici, Horia Virgolici
openaire   +2 more sources

Discrimination of high impedance fault in microgrid power network using semi-supervised machine learning algorithm

Ain Shams Engineering Journal
This work proposes a semi-supervised classification approach for discriminating high-impedance (HI) faults and other transients in a photovoltaic (PV) interconnected microgrid (MG) network.
Arangarajan Vinayagam, S.T. Suganthi, C.B. Venkatramanan, Ayoob Alateeq, Abdullah Alassaf, Nur Fadilah Ab Aziz, Mohd Helmi Mansor, Saad Mekhilef   +7 more
doaj   +1 more source

Teaching learning-based whale optimization algorithm for multi-layer perceptron neural network training.

Mathematical biosciences and engineering : MBE, 2020
This paper presents an improved teaching learning-based whale optimization algorithm (TSWOA) used the simplex method. First of all, the combination of WOA algorithm and teaching learning-based algorithm not only achieves a better balance between ...
Yong-Quan Zhou, Yanbiao Niu, Qifang Luo, Ming Jiang   +3 more
semanticscholar   +1 more source

Research on Ice Accretion Prediction Model for Wind Turbine Blades Based on Multi-Layer Perceptron Neural Network

发电技术
ObjectivesIn cold regions, the icing problem on wind turbine blades significantly reduces power generation efficiency and increases safety risks, making accurate icing prediction technology crucial. To improve the accuracy of ice accretion prediction for
HAN Bin, ZENG Zhixiang, KONG Fanxin, XIE Nan, LIU Zhiqiang   +4 more
doaj   +1 more source