Research Progress of Synthesis and Modification Methods Based on Dynamic Substructures by Jintao Su, Bangdong Wang

“…In terms of substructure modification, the reference datum method, function dynamic modification method, neural network model modification, and frequency response function modification are analyzed, and the shortcomings of the dynamic substructure modification method are summarized. …”
Get full text

Spam Email Detection using Naïve Bayes classifier by Wang Liansong

“…Various algorithms such as the tree-based model, support vector machine Algorithm, and Convolutional Neural Network have been explored in prior research to tackle this challenge. …”
Get full text

A Prediction Method for the RUL of Equipment for Missing Data by Chen Wenbai, Liu Chang, Chen Weizhao, Liu Huixiang, Chen Qili, Wu Peiliang

“…We present a prediction framework to estimate the remaining useful life (RUL) of equipment based on the generative adversarial imputation net (GAIN) and multiscale deep convolutional neural network and long short-term memory (MSDCNN-LSTM). …”
Get full text

Lung cancer Prediction and Classification based on Correlation Selection method Using Machine Learning Techniques by Dakhaz Mustafa Abdullah, Adnan Mohsin Abdulazeez, Amira Bibo Sallow

“…This paper endeavors to inspect accuracy ratio of three classifiers which is Support Vector Machine (SVM), K-Nearest Neighbor (KNN)and, Convolutional Neural Network (CNN) that classify lung cancer in early stage so that many lives can be saving. …”
Get full text

Revolutionizing colorectal cancer detection: A breakthrough in microbiome data analysis. by Mwenge Mulenga, Arutchelvan Rajamanikam, Suresh Kumar, Saharuddin Bin Muhammad, Subha Bhassu, Chandramathi Samudid, Aznul Qalid Md Sabri, Manjeevan Seera, Christopher Ifeanyi Eke

“…This innovative approach markedly enhances the Area Under the Curve (AUC) performance of the Deep Neural Network (DNN) algorithm in colorectal cancer (CRC) detection using gut microbiome data, elevating it from 0.800 to 0.923. …”
Get full text

Time Series Prediction Based on Complex-Valued S-System Model by Bin Yang, Wenzheng Bao, Yuehui Chen

“…The experiment results show that the predicted data are very close to the target ones and our method could obtain the better RMSE, MAP, MAPE, POCID, R2, and ARV performances than ARIMA, radial basis function neural network (RBFNN), flexible neural tree (FNT), ordinary differential equation (ODE), and S-system.…”
Get full text

Annual Energy Consumption Forecasting Based on PSOCA-GRNN Model by Huiru Zhao, Sen Guo

“…The generalized regression neural network (GRNN) model was employed to forecast the annual energy consumption due to its good ability of dealing with the nonlinear problems. …”
Get full text

Flexural Strength Prediction of Welded Flange Plate Connections Based on Slenderness Ratios of Beam Elements Using ANN by Amir A. Hedayat, Ehsan Jazebi, Saman AsadAbadi, Amin Iranpour

“…Proposed theoretical formulas and artificial neural network- (ANN-) based models developed in this study were able to adequately predict the connection strength.…”
Get full text

Comparing ChatGPT And LSTM In Predicting Changes In Quarterly Financial Metrics by Vitali Chaiko

“…The performance of ChatGPT is compared against Long Short-Term Memory (LSTM) neural network models developed as part of this research. …”
Get full text

FSE-RBFNN-Based AILC of Finite Time Complete Tracking for a Class of Time-Varying NPNL Systems with Initial State Errors by Chunli Zhang, Lei Yan, Yangjie Gao

“…Addressing the difficulty of nonlinear parameterization terms in system models, a new function approximator (FSE-RBFNN) which is combined with radial basis function neural network (RBFNN) and Fourier series expansion (FSE) is introduced to model each time-varying nonlinear parameterization function. …”
Get full text

Use of Directional Spectra for Detection of Engine Cylinder Power Fault by Chong-Won Lee, Yun-Sik Han, Jong-Po Park

“…As spectral estimators, the maximum likelihood and FFT methods are compared, and the multi-layer neural network is employed for pattern recognition. Experimental results show that the success rate for identifying the misfired cylinder is much higher with the use of two-sided directional power spectra than conventional one-sided power spectra.…”
Get full text

Real-Time Prediction of the Trend of Ground Motion Intensity Based on Deep Learning by Tao Liu, Zhijun Dai

“…According to the different sampling frequencies, the neural network is constructed by several subnetworks, and the output of each subnetwork is combined into one. …”
Get full text

Research on Small Sample Nonlinear Cointegration Test and Modeling Based on the LS-SVM Optimized by PSO by Jungang Du

“…We also compare the prediction results with the wavelet neural network algorithm, and the results show that the generalization ability of LS-SVM Optimized by PSO is better, and the prediction accuracy of small samples is higher.…”
Get full text

Research on Application of the Feature Transfer Method Based on Fast R-CNN in Smoke Image Recognition by Xi Cheng

“…To further improve the accuracy of smoke detection, an automatic feature extraction and classification method based on fast regional convolution neural network (fast R–CNN) was introduced in the study. …”
Get full text

The Impacts of Internet + Rural Financial Industry on County Economy and Industrial Growth Algorithm by Yuanhui Huang, Yimao Ye

“…To better develop rural finance and county economy, this paper constructs an artificial neural network model and FA model to predict the rural finance industry, and four indicators are selected to test the performance measurement of the model. …”
Get full text

An Improved Gesture Segmentation Method for Gesture Recognition Based on CNN and YCbCr by Yan Luo, Gaoxiang Cui, Deguang Li

“…In order to enhance the features of gesture recognition, firstly, the hand skin color is filtered through YCbCr color space to separate the gesture region to be recognized, and the Gaussian filter is used to process the noise of gesture edge; secondly, the morphological gray open operation is used to process the gesture data, the watershed algorithm based on marker is used to segment the gesture contour, and the eight-connected filling algorithm is used to enhance the gesture features; finally, the convolution neural network is used to recognize the gesture data set with fast convergence speed. …”
Get full text

A Machine Learning Approach to Optimize, Model, and Predict the Machining Factors in Dry Drilling of Nimonic C263 by S. Lakshmana Kumar, V. Jacintha, A. Mahendran, R. M. Bommi, M. Nagaraj, Umamahesawari Kandasamy

“…The feed forward neural network (FFNN) was used to develop a predictive model. …”
Get full text

Adaptive Neural Control and Modeling for Continuous Stirred Tank Reactor with Delays and Full State Constraints by Dongjuan Li, Dongxing Wang, Ying Gao

“…In this paper, an adaptive neural network control method is described to stabilize a continuous stirred tank reactor (CSTR) subject to unknown time-varying delays and full state constraints. …”
Get full text

Resistance Spot Welding Defect Detection Based on Visual Inspection: Improved Faster R-CNN Model by Weijie Liu, Jie Hu, Jin Qi

“…Additionally, a new pruning model is introduced, reducing unnecessary layers and parameters in the neural network, leading to faster processing times without sacrificing accuracy. …”
Get full text

Using object-oriented databases in face recognition by X. C. Dong, V. I. Ionin

“…Using a convolutional neural network in the algorithm allows the transition from specific features of the image to more abstract details.…”
Get full text