Multiparameter Logging Evaluation of Chang 73 Shale Oil in the Jiyuan Area, Ordos Basin by Bobiao Liu, Chengqian Tan, Yinchao Huai, Yuhan Tan, Han Zhang, Zhao Feng

“…The p-wave time difference curves calculated by the artificial neural network (ANN) method and the conventional logging curve fitting method were compared. …”
Get full text

Downscaling Global Weather Forecast Outputs Using ANN for Flood Prediction by Nam Do Hoai, Keiko Udo, Akira Mano

“…This paper presents an empirical-statistical downscaling method for precipitation prediction which uses a feed-forward multilayer perceptron (MLP) neural network. The MLP architecture was optimized by considering physical bases that determine the circulation of atmospheric variables. …”
Get full text

Application of Artificial Intelligence for the Estimation of Concrete and Reinforcement Consumption in the Construction of Integral Bridges by Željka Beljkaš, Miloš Knežević, Snežana Rutešić, Nenad Ivanišević

“…The estimation model was developed by using artificial neural networks. The best artificial neural network model showed high accuracy in material consumption estimation expressed as the mean absolute percentage error, 8.56% for concrete consumption estimate and 17.31% for reinforcement consumption estimate.…”
Get full text

Probabilistic Prediction of Mine Dynamic Disaster Risk Based on Multiple Factor Pattern Recognition by Tianwei Lan, Chaojun Fan, Sheng Li, Hongwei Zhang, Adrian Sergaevich Batujin

“…The risk probability prediction criteria of mine dynamic disasters and the risk probability values of each unit in the prediction area are determined by using the method of neural network and fuzzy mathematics. The dangerous area, threat area, and safety area of mine dynamic disasters are divided to evaluate the dangerous degree. …”
Get full text

Adaptation optimizes sensory encoding for future stimuli. by Jiang Mao, Constantin A Rothkopf, Alan A Stocker

“…We further tested our hypothesis by analyzing the internal sensory representations of a recurrent neural network trained to predict the next frame of natural scene videos (PredNet). …”
Get full text

Lane-Changing Behavior Prediction Based on Game Theory and Deep Learning by Shuo Jia, Fei Hui, Cheng Wei, Xiangmo Zhao, Jianbei Liu

“…For the deep-learning component, long short-term memory and a convolutional neural network are used to extract and learn data features during the lane-changing process as well as combine the output of the game theory component to obtain the prediction result of whether the vehicle will change lanes. …”
Get full text

Multimodel Modeling and Predictive Control for Direct-Drive Wind Turbine with Permanent Magnet Synchronous Generator by Lei Wang, Tao Shen, Chen Chen

“…In this strategy, wind turbine with direct-drive permanent magnet synchronous generator is modeled and a backpropagation artificial neural network is designed to estimate the wind speed loaded into the turbine model in real time through the estimated turbine shaft speed and mechanical power. …”
Get full text

Breast Cancer Prediction Using the Affinity Propagation Clustering with Regard to the Weights of Variables by Sina Dami, Zeinab Hatamchuri

“…In addition, the Wilcoxon assumption test confirmed the superiority of the combined neural network compared to other methods.…”
Get full text

Scheme Analysis for Enhancing Autonomous Driving Based on Computer Vision by Chen Xinyi, Luo Binbin, Xu Ziyue

“…Thesis adopted both literature review and technical analysis, focusing on recent developments in key technologies such as image processing, hybrid convolutional neural network (CNN)-transformer models, object detection, and multi-sensor fusion. …”
Get full text

Single-cell RNA-seq data augmentation using generative Fourier transformer by Nima Nouri

“…Moreover, comparisons of scGFT with leading neural network-based GMs highlight its superior performance, driven by its analytical mechanism. …”
Get full text

Predictive Modeling of Tool Life in Turning Using ANN-Taguchi Hybridization by Shrishail Sollapur B., Shubham R. Suryawanshi, Mitali Mhatre S., Dipak K. Dond, Ganesh Chate, Abhijit Bhowmik

“…In this research, we delve into the complex relationship between tool lifespan and cutting speed through experiments guided by the Taguchi method and artificial neural network (ANN) models. Several case studies have been conducted to test the practicality and effectiveness of this method in representing complex tool lifespan-cutting speed relationships.…”
Get full text

A New Hybrid Model Predictive Controller Design for Adaptive Cruise of Autonomous Electric Vehicles by Yuanhang Chen, Guodong Feng, Shaofang Wu, Xiaojun Tan

“…The driving modes are divided into following and cruising, and the MPC algorithm based on simplified dual neural network (SDNN) and proportional-integral-derivative (PID) based on single neuron (SN) are applied to the following mode and the cruising mode, respectively. …”
Get full text

Model Architecture Analysis and Implementation of TENET for Cell–Cell Interaction Network Reconstruction Using Spatial Transcriptomics Data by Ziyang Wang, Yujian Lee, Yongqi Xu, Peng Gao, Chuckel Yu, Jiaxing Chen

“…Researchers have shown that shallow neural networks can effectively reconstruct the CCI from the abundant molecular data captured in spatial transcriptomics (ST). …”
Get full text

Building Arabic Speech Recognition System Using HuBERT Model and Studying the Sources of Errors [Arabic] by Rima Sbih, Assef Jafar, Ali Kazem

“…This paper presents the development of a speech recognition system for the Arabic language that can handle continuous speech and a large number of words, independent of the speaker, using deep neural network models trained by self-supervised learning. …”
Get full text

Brain Tumor Detection Using a Deep CNN Model by Sonia Ben Brahim, Samia Dardouri, Ridha Bouallegue

“…Our study involves the application of a deep convolutional neural network (DCNN) to diagnose brain tumors from MR images. …”
Get full text

Deep Learning for Automatic Recognition of Magnetic Type in Sunspot Groups by Yuanhui Fang, Yanmei Cui, Xianzhi Ao

“…We present in this study, based on the SDO/HMI SHARP data taken during the time interval 2010-2017, an automatic procedure for the recognition of the predefined magnetic types in sunspot groups utilizing a convolutional neural network (CNN) method. Three different models (A, B, and C) take magnetograms, continuum images, and the two-channel pictures as input, respectively. …”
Get full text

Enhancing Brain Tumor Detection: A Comparative Study of CNN Architectures Using MRI Data by Zhu Zhimeng

“…Existing Convolutional Neural Network (CNN) models like Visual Geometry Group 19 (VGG19), Residual Network 18 (ResNet18), and Residual Network 34 (ResNet34), despite their success in image classification and recognition, face challenges such as unclear boundary detection, limited generalization, and lower computational efficiency in detecting brain tumors. …”
Get full text

Degradation State Recognition of Rolling Bearing Based on K-Means and CNN Algorithm by Qicai Zhou, Hehong Shen, Jiong Zhao, Xingchen Liu, Xiaolei Xiong

“…Then, the convolutional neural network recognition model is built, which takes the bearing vibration signals as input, and outputs the degradation state category. …”
Get full text

A Repeatable Optimization for Kinematic Energy System with Its Mobile Manipulator Application by Ying Kong, Ruiyang Zhang, Yunliang Jiang, Xiaoyun Xia

“…To remedy deviations between initial position and desired position of each kinematic joint angle, a special kind of repeatable optimization for kinematic energy minimization based on terminal-time Zhang neural network (TTZNN) with finite-time convergence is proposed for inverse kinematics of mobile manipulators. …”
Get full text

Scientific Article Writing: Will ChatGPT Help? by I. M. Zashikhina

“…The cases of writing academic papers using ChatGPT have led to a number of publications analyzing the pros and cons of using this neural network. In this paper, we investigate the possibility of using ChatGPT to write an introduction to a scientific paper on a topical issue of the Arctic governance. …”
Get full text