EMD-GM-ARMA Model for Mining Safety Production Situation Prediction by Menglong Wu, Yicheng Ye, Nanyan Hu, Qihu Wang, Huimin Jiang, Wen Li

“…Finally, aiming to predict the mining safety production situation, the EMD-GM-ARMA model was constructed via superimposing the prediction results of each subsequence, thereby compared to the ARIMA model, wavelet neural network model, and PSO-SVM model. The results demonstrated that the EMD-GM-ARMA model and the PSO-SVM model hold the highest prediction accuracy in the short-term prediction, and the wavelet neural network has the lowest prediction accuracy. …”
Get full text

Wind turbine blade damage detection based on acoustic signals by Chenchen Yang, Shaohu Ding, Guangsheng Zhou

“…Considering the computational challenges of spectral subtraction under extreme noise intensities, a pretrained sound source separation neural network was used to distinguish between random wind noise and mechanical noise in wind turbine sound signals. …”
Get full text

Optimizing colorectal polyp detection and localization: Impact of RGB color adjustment on CNN performance by Jirakorn Jamrasnarodom, Pharuj Rajborirug, Pises Pisespongsa, Kitsuchart Pasupa

“…This study explores the impact of RGB color adjustment on Convolutional Neural Network (CNN) models for improving polyp detection and localization in colonoscopic images. …”
Get full text

Development and external validation of machine learning-based models to predict patients with cellulitis developing sepsis during hospitalisation by Li Hu, Xilingyuan Chen, Rentao Yu

“…In external validation, the AUC of the artificial neural network (ANN) model was the highest, 0.830, while the AUC of the logistic regression (LR) model was the lowest, 0.792. …”
Get full text

Development and validation of a deep learning system for detection of small bowel pathologies in capsule endoscopy: a pilot study in a Singapore institution by Bochao Jiang, Michael Dorosan, Justin Wen Hao Leong, Marcus Eng Hock Ong, Sean Shao Wei Lam, Tiing Leong Ang

“…We used convolutional neural network-based models pretrained on large-scale open-domain data to extract spatial features of CE images that were then used in a dense feed-forward neural network classifier. …”
Get full text

A Novel AI-Based Integrated Cybersecurity Risk Assessment Framework and Resilience of National Critical Infrastructure by Sardar Muhammad Ali, Abdul Razzaque, Muhammad Yousaf, Sardar Sadaqat Ali

“…We trained three ML classifiers: Support Vector Machine (SVM), Naïve Bayes (NB), and K-Nearest Neighbors (KNN), along with three DL models: Long Short-Term Memory (LSTM), Recurrent Neural Network (RNN), and Convolutional Neural Network (CNN). …”
Get full text

Prediction method of gas emission in working face based on feature selection and BO-GBDT by MA Wenwei

“…Comparison with random forest, support vector machine, and neural network models showed that the BO-GBDT model achieved the highest accuracy and generalization, with an average relative error of 2.61%. …”
Get full text

A comparative study on different machine learning approaches with periodic items for the forecasting of GPS satellites clock bias by Longjiang Song, Jiahao Liu, Leilei Wang, Ziyi Wang, Yibo Yuan

“…Specifically, we utilize precision satellite clock bias data from the International GNSS Service forecast experiments and assess the predictive effects of various models including backpropagation neural network (BPNN), wavelet neural network (WNN), long short-term memory (LSTM), and gated recurrent units (GRUs). …”
Get full text

Klasifikasi Penyakit Alzheimer Dari Scan Mri Otak Menggunakan Convnext by Yehezkiel Stephanus Austin, Haikal Irfano, Juan Young Christopher, Lintang Cahyaning Sukma, Octo Perdana Putra, Riyadh Ilham Ardhanto, Novanto Yudistira

“…Teknologi machine learning dan neural network dapat mendukung deteksi dini melalui penggunaan model ConvNeXt yang telah dilatih dengan metode transfer learning menggunakan bobot awal dari ImageNet, dan di-fine-tune untuk mengklasifikasikan empat tingkat keparahan Alzheimer berdasarkan hasil pemindaian MRI otak, yaitu Mild Demented, Moderate Demented, Non Demented, dan Very Mild Demented. …”
Get full text

Wind Energy Resource Prediction and Optimal Storage Sizing to Guarantee Dispatchability: A Case Study in the Kenyan Power Grid by Hampfrey Odero, Cyrus Wekesa, George Irungu

“…The historical weather data, namely wind speed, ambient temperature, relative humidity, wind direction, and generation output from LTWPP, are employed in the training, testing, and validation of the neural network. LTWPP and BESS are modelled in MATLAB R2016a software. …”
Get full text

The New Approach Research on Singing Voice Detection Algorithm Based on Enhanced Reconstruction Residual Network by Lilin Liu

“…Traditional feedforward neural networks are prone to lose local information when extracting singing voice features. …”
Get full text

Deep learning technology: enabling safe communication via the internet of things by Ramiz Salama, Hitesh Mohapatra, Tuğşad Tülbentçi, Fadi Al-Turjman

“…Specifically, the Cuda-deep neural network (Cu-DNN), Cuda-bidirectional long short-term memory (Cu-BLSTM), and Cuda-gated recurrent unit (Cu-DNNGRU) classifiers are utilized for effective threat detection. …”
Get full text

Predicting Screening Efficiency of Probability Screens Using KPCA-GRNN with WP-EE Feature Reconstruction by Qingtang Chen, Yijian Huang

“…The results show that WP-EE-GRNN achieves superior prediction accuracy compared to box dimension (d)-GRNN, box dimension-back propagation neural network (BPNN), and d-weighted least squares support vector machine, WP-d-GRNN, WP-EE-BPNN, EMD-EE-GRNN, and VMD-EE-GRNN. …”
Get full text

Parallelization in combining the SOM and Sammon's mapping by Gintautas Dzemyda, Olga Kurasova, Virginijus Marcinkevičius

“… In this paper, we propose a parallel algorithm for multidimensional data visualization combining the neural network (the self-organizing map-SOM) and Sammon’s mapping. …”
Get full text

Mapping error in the parallel realizations of SAMANN algorithm by Viktor Medvedev, Gintautas Dzemyda

“…We investigate an unsupervised back-propagation algorithm to train a multilayer feed-forward neural network (SAMANN) to perform the Sammoil's nonlinear projection and propose a parallel algorithm for SAMANN network.   …”
Get full text

A Case Study on Computer-Based Analysis of the Stochastic Stability of Mechanical Structures Driven by White and Colored Noise: Utilizing Artificial Intelligence Techniques to Desi... by Aydin Azizi

“…The Ring Probabilistic Logic Neural Network (RPLNN) architecture has been adopted to design the proposed controller, and the pavement condition has been modelled utilizing Gaussian white noise. …”
Get full text

Optimization of the learning rate in the algorithm for data visualization by Viktor Medvedev, Gintautas Dzemyda

“…The paper describes an unsupervised backpropagation algorithm to train a multilayer feed-forward neural network (SAMANN) to perform the Sammon‘s nonlinear projection. …”
Get full text

Research on the Spatial Network Connection Characteristics and Influencing Factors of Chengdu–Chongqing Urban Agglomeration from the Perspective of Flow Space by Yangguang Hao, Zhongwei Shen, Jiexi Ma, Jiawei Li, Mengqian Yang

“…Based on the results of the SOM neural network machine learning model, the connectivity capabilities of cities within the CCUA are divided into five levels. …”
Get full text

A Comparative Study between Time Series and Machine Learning Technique to Predict Dengue Fever in Dhaka City by Tanzina Akter, Md. Tanvirul Islam, Md. Farhad Hossain, Mohammad Safi Ullah

“…According to the findings of this research, neural networks outperform time series analysis when it comes to making predictions. …”
Get full text

Construction and effect of interactive teaching methods in the college badminton classroom using fuzzy-assisted virtual reality modeling: a case study in Chinese universities by Yinghao Li, Mohd Jawis

“…The article proposes VR-ITM, or fuzzy-assisted  VR interactive teaching techniques, to teach badminton in universities using neural networks. This study examines the advantages and disadvantages of utilizing fuzzy-assisted  VR to teach badminton in PE classes and the difficulties and solutions teachers have found for these issues through a neural network. …”
Get full text