Neural network

Electricity demand is increasing, transmission line development can not keep up with it. This puts the power system in a full load state which puts the power system operating near the boundary of stability. This paper applies deep neural networks to predict power system dynamic stability.

10p viling 11-10-2024 2 1   Download

In this paper, we propose a wavelet type-2 fuzzy brain imitated controller (WT2FBIC) for nonlinear robotic systems. The suggested method combines a wavelet type-2 fuzzy system (WT2FS) and a brain imitated controller (BIC) to improve learning efficiency.

11p viling 11-10-2024 1 1   Download

In this study, we explore the potential of graph neural networks (GNNs), in combination with transfer learning, for the prediction of molecular solubility, a crucial property in drug discovery and materials science. Our approach begins with the development of a GNN-based model to predict the dipole moment of molecules.

8p viling 11-10-2024 1 1   Download

In this paper, we used Convolution neural network (CNN) that exploits the visual properties of the input data to obtain features from network traffic, thereby achieving good intrusion detection performance.

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In this paper, author uses 8-bit fixed-point quantization to greatly reduce the memory space requirement of the feature maps and weights and the accuracy of LeNet-5 with MNIST dataset is only slightly reduced. In the hardware accelerator, author proposes a highly flexible CNN accelerator with reconfigurable layers.

14p viling 11-10-2024 3 1   Download

Ultra-wideband (UWB) radars are getting much attention for maritime applications of smart and luxury ships in which UWB radar could be integrated into Bridge Navigational Watch & Alarm System - BNWAS. One of the interesting applications of UWB radar is vital signs measurement, which is a contactless method. UWB radar measures respiration and heartbeat rate by the motion of thorax for detecting and checking the state of people on the bridge.

5p vifilm 11-10-2024 3 1   Download

This paper introduces the application of artificial intelligence to build a security control software system in local military units. This software system uses state-of-the-art convolutional neural networks (CNN SOTA) for facial recognition by testing two of the best facial recognition models currently available: the FaceNet model and the VGGFace model.

8p vifilm 11-10-2024 6 1   Download

The process of neural stem cell (NSC) differentiation into neurons is crucial for the development of potential cell-centered treatments for central nervous system disorders. However, predicting, identifying, and anticipating this differentiation is complex. In this study, we propose the implementation of a convolutional neural network model for the predictable recognition of NSC fate, utilizing single-cell brightfield images.

7p viengfa 28-10-2024 2 2   Download

This paper is structured as follows. The following section presents related work. Section 3 summarizes the characteristics of the two datasets utilized in the model and the system’s overall architecture for image-based disease diagnosis. Section 4 provides our experimental results that compare the performance metrics with other studies.

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In this study, we propose the application of CycleGAN to generate T2 pulse sequence MRI images of the human brain from T2 Flair pulse sequence images of the same type and vice versa, thereby increasing the number of MRI images of various types.

8p viengfa 28-10-2024 4 2   Download

This study presents a novel neural network (NN) framework for developing force fields specific to graphene monolayers, utilizing data obtained from first-principles calculations. The authors analyze three primary force components, force magnitude and the cosines of two angles across different configurations of surrounding carbon atoms.

7p viengfa 28-10-2024 5 2   Download

Accurate forecasting of the electrical load is a critical element for grid operators to make well-informed decisions concerning electricity generation, transmission, and distribution. In this study, an Extreme Learning Machine (ELM) model was proposed and compared with four other machine learning models including Artificial Neural Networks (ANN), Convolutional Neural Networks (CNN), Long Short-Term Memory (LSTM) and Gated Recurrent Unit (GRU).

10p viengfa 28-10-2024 2 1   Download

Bài giảng "Học sâu và ứng dụng: Bài 3 - Giới thiệu về mạng tích chập Conv Neural Networks" nhằm giúp sinh viên làm quen với một trong những kiến trúc học sâu quan trọng nhất – mạng nơ-ron tích chập (Convolutional Neural Networks - CNN) – được ứng dụng rộng rãi trong lĩnh vực xử lý ảnh và thị giác máy tính.

47p gaupanda088 11-04-2025 1 0   Download

Artificial neural networks, which are an essential tool in Machine Learning, are used to solve many types of problems in different fields. This article will introduce an application of the artificial neural network model in the diagnosis of heart disease based on the heart.csv data file.

6p viengfa 28-10-2024 3 2   Download

The main objective of this study is to predict accurately the loaddeflection of composite concrete bridges using two popular machine learning (ML) models namely Random Tree (RT) and Artificial Neural Network (ANN). Data from 83 track loading tests conducted on various bridges in Vietnam were collected and analyzed.

9p viengfa 28-10-2024 3 2   Download

This study introduces and evaluates the Long-term Traffic Prediction Network (LTPN), a specialized machine learning framework designed for realtime traffic prediction in urban environments.

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The results of this study would be useful in quickly and accurately predicting CPI to the management agencies, investors, construction contractors to pre-plan the construction investment costs. This will also help in suitably adjusting changing construction cost with time.

11p viengfa 28-10-2024 2 2   Download

In this study, we propose a machine learning technique for estimating the shear strength of CRC beams across a range of service periods. To do this, we gathered 158 CRC beam shear tests and used Artificial Neural Network (ANN) to create a forecast model for the considered output.

12p viengfa 28-10-2024 3 2   Download

This paper develops an Artificial Neural Network (ANN) model based on 96 experimental data to forecast the dynamic modulus of asphalt concrete mixtures. This study applied the repeated KFold cross-validation technique with 10 folds on the training data set to make the simulation results more reliable and find a model with more general predictive power.

9p viengfa 28-10-2024 5 2   Download

In this study, an artificial neural networkbased Bayesian regularization (ANN) model is proposed to predict the compressive strength of concrete. The database in this study includes 208 experimental results synthesized from laboratory experiments with 9 input variables related to temperature change and design material composition.

12p viengfa 28-10-2024 2 2   Download