Trajectory Tracking Control Study of a New Parallel Mechanism with Redundant Actuation by Haiqiang Zhang, Hairong Fang, Dan Zhang, Qi Zou, Xueling Luo

“…In this paper, an efficient trajectory tracking control scheme for the new redundantly actuated parallel mechanism by integrating force/position hybrid control with the combination of inertia feed-forward control and back propagation (BP) neural network PID control is proposed. The dynamic models including the joint space and task space are formulated explicitly in efficient and compact form by means of the principle of virtual work and d’Alembert formulations. …”
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Optimization of Sample Size, Data Points, and Data Augmentation Stride in Vibration Signal Analysis for Deep Learning-Based Fault Diagnosis of Rotating Machines by Fasikaw Kibrete, Dereje Engida Woldemichael, Hailu Shimels Gebremedhen

“…This study utilizes a one-dimensional convolutional neural network (1-D CNN) as the deep learning model for fault classification. …”
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Optimising deep learning models for ophthalmological disorder classification by S. Vidivelli, P. Padmakumari, C. Parthiban, A. DharunBalaji, R. Manikandan, Amir H. Gandomi

“…In this article, we have used different deep learning models for the categorisation of ophthalmological disorders into multiple classes and multiple labels utilising transfer learning-based convolutional neural network (CNN) methods. The Ocular Disease Intelligent Recognition (ODIR) database is used for experiments, and it contains fundus images of the patient’s left and right eyes. …”
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Writer identification and writer retrieval based on NetVLAD with Re‐ranking by Shervin Rasoulzadeh, Bagher BabaAli

“…A novel pipeline is proposed for the problem at hand by employing a unified neural network architecture consisting of the ResNet‐20 as a feature extractor and an integrated NetVLAD layer, inspired by the vector of locally aggregated descriptors (VLAD), in the head of the latter part. …”
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Tribological Behavior and Analysis on Surface Roughness of CNC Milled Dual Heat Treated Al6061 Composites by A. Bovas Herbert Bejaxhin, G.M. Balamurugan, S.M. Sivagami, K. Ramkumar, V. Vijayan, S. Rajkumar

“…The influencing factors are identified by the Taguchi, genetic algorithm (GA), and Artificial Neural Network (ANN) techniques and compared within it. …”
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3D Simulation Design and Application of Traditional Hanfu Based on Internet of Things by Li Lin, Wen Gan

“…In this study, the feasibility of the 3D simulation design of Hanfu was fully studied by combining the Internet of Things technology and the convolutional neural network method. The research results show that the Internet of Things technology can efficiently and accurately collect the characteristics of patterns, colors, shapes, and historical information of Hanfu. …”
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Lion Algorithm-Optimized Long Short-Term Memory Network for Groundwater Level Forecasting in Udupi District, India by B. S. Supreetha, Narayan Shenoy, Prabhakar Nayak

“…The prediction accuracy of the hybrid LSTM-LA model was better than that of the feedforward neural network (FFNN) and the isolated LSTM models. The hybrid LSTM-LA-based forecasting model is promising for a larger dataset.…”
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Fault Diagnosis Method Research of Mechanical Equipment Based on Sensor Correlation Analysis and Deep Learning by Tangbo Bai, Jianwei Yang, Lixiang Duan, Yanxue Wang

“…Meanwhile, a convolutional neural network-based deep learning method is developed to process the matrix and to discover the relationship between results and equipment states for fault diagnosis. …”
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Generative Adversarial Network-Based Edge-Preserving Superresolution Reconstruction of Infrared Images by Yuqing Zhao, Guangyuan Fu, Hongqiao Wang, Shaolei Zhang, Min Yue

“…The convolutional neural network has achieved good results in the superresolution reconstruction of single-frame images. …”
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Expandable Orbit Decay Prediction Using Continual Learning by Junhua He, Hua Wang, Haitao Wang, Xuankun Fang, Chengyi Huo

“…The plasticity of the proposed model is discussed, which originates from the uncertainty of neural network (NN) parameters. The proposed method overcomes the negative effects of uncertain physical parameters and complex space environments. …”
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Surface Feature Prediction Modeling and Parameter Optimization for Turning TC17 Titanium Alloy by Zhibo Deng, Zhe Wang, Xuehong Shen

“…Data obtained from the Box-Behnken design experiments were used to develop the response surface methodology (RSM) and artificial neural network (ANN) models. Through analysis of variance (ANOVA), the relative effects of each cutting parameter on the responses have been determined. …”
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Deteksi Dan Klasifikasi Hama Potato Beetle Pada Tanaman Kentang Menggunakan YOLOV8 by Daniel Geoffrey Manurung, Mohammad Ryan Pinasthika, Muhammad Azka Obila Vasya, Rania Aprilia Dwi Setya Putri, Agustinus Parasian Tampubolon, Rakan Fadhil Prayata, Septia Khoirin Nisa, Novanto Yudistira

“…Metode yang digunakan untuk mendeteksi dan mengklasifikasikan potato beetle adalah Convolutional Neural Network (CNN) yang merupakan algoritma jaringan syaraf tiruan yang efektif dalam pengolahan citra. …”
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Impact of carbapenem-resistant infections on mortality in mechanically ventilated acute respiratory distress syndrome patients: A comparison with hypoxemia severity – An observatio... by Thejesh Srinivas, Shwethapriya R, Gagana Hanumaiah, Pratibha Todur, Souvik Chaudhuri, Ganesh Paramasivam, Prithvishree Ravindra, Vinutha R. Bhat, Sagar Shanmukhappa Maddani, Shobha U. Kamath, Danavath Nagendra, Vishwas P, Likith Hanumaiah, Pratik Paran Medhi, Prabha Prakash

“…Univariate and multivariable logistic regression analyses and artificial neural network model, were employed to analyze mortality outcomes. …”
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Prediksi Kesiapan Sekolah Menggunakan Machine Learning Berbasis Kombinasi Adam dan Nesterov Momentum by Indah Mustika Rahayu, Ahmad Yusuf, Mujib Ridwan

“…Penelitian menggunakan algoritma Artificial Neural Network dengan metode optimasi kombinasi Adam dan Nesterov Momentum. …”
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Guaranteeing Prescribed Performance Control for Gyrostabilized Platform with Unknown Control Direction Preceded by Hysteresis by Yexing Wang, Humin Lei, Jikun Ye, Xiangwei Bu, Yali Xue

“…Besides, through ingenious transformation, radial basis function neural network (RBFNN) is applied to estimate the unknown control gains preceded by hysteresis. …”
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Cloud-Based Framework for COVID-19 Detection through Feature Fusion with Bootstrap Aggregated Extreme Learning Machine by Amjad Rehman Khan, Tanzila Saba, Tariq Sadad, Seng-phil Hong

“…An extreme learning machine (ELM) is a neural network modification with a high capability for pattern recognition and classification problems for COVID-19 detection. …”
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Characterization of Short-Term Strength Properties of Fiber/Cement-Modified Slurry by Ping Jiang, Tianhao Mao, Na Li, Liang Jia, Fang Zhang, Wei Wang

“…A formula satisfying the accuracy requirement was obtained by fitting the stress-strain curves using the back propagation (BP) neural network algorithm. Five parameters, including peak strength, failure strain, initial elastic modulus, residual strength, and energy dissipation, were used to characterize the short-term strength properties of fiber/cement-modified slurry. …”
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Portable motorized telescope system for wind turbine blades damage detection by Alejandro Carnero, Cristian Martín, Manuel Díaz

“…The application tries to carry out a complete sweep of the surface of the wind turbine blades in an autonomous way based on the predictions of neural network models and finally presents the defects found to the user. …”
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Research on Multilevel Classification of High-Speed Railway Signal Equipment Fault Based on Text Mining by Fan Gao, Fan Li, Zhifei Wang, Wenqi Ge, Xinqin Li

“…In the multilevel classification model, the single-layer classification model was designed based on stacking integrated learning idea; the recurrent neural network BiGRU and BiLSTM were used as primary learners, and the weight combination calculation method was designed for secondary learners, and k-fold cross verification was used to train the stacking model. …”
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Optimization Modeling and Empirical Research on Gasoline Octane Loss Based on Data Analysis by Ji Guo, Yujia Lou, Wanyi Wang, Xianhua Wu

“…Firstly, the data are screened and the high-dimensional data are reduced to construct the neural network prediction model optimized by genetic algorithm. …”
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