Prediction, modeling and characterization of surface texturing by sulfuric etchant on non-toxic titanium bio-material using artificial neural networks and fuzzy logic systems by Khanlou Hossein Mohammad, Ang Bee Chin, Barzani Mohsen Marani

“…Multilayer feed forward network, radial biased function network, generalized regression neural network and adaptive network-based fuzzy inference system (ANFIS) were used to predict the surface roughness of Ti-13Zr-13Nb alloy in etching sulfuric acid. …”
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SEMG-based multifeatures and predictive model for knee-joint-angle estimation by Chen Yang, Xugang Xi, Sijia Chen, Seyed M. Miran, Xian Hua, Zhizeng Luo

“…The back propagation neural network, generalized regression neural network, and least-square support vector regression machine (LS-SVR) were used as predictive models. …”
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Ferroelectric Field-Effect Transistor-Based 3-D NAND Architecture for Energy-Efficient on-Chip Training Accelerator by Wonbo Shim, Shimeng Yu

“…Different from the deep neural network (DNN) inference process, the training process produces a huge amount of intermediate data to compute the new weights of the network. Generally, the on-chip global buffer (e.g., SRAM cache) has limited capacity because of its low memory density; therefore, off-chip DRAM access is inevitable during the training sequences. …”
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Mine roadway field strength prediction based on improved convolutional neural network by WANG Anyi, ZHOU Xiaoming

“…The improved CNN adds batch normalization layer after each convolutional layer to replace the original pooling layer so as to avoid the loss of data characteristics due to down-sampling of the pooling layer, to keep the output of each convolutional layer similarly distributed, to improve the network generalization capacity and to speed up the network convergence. …”
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Sharp Bounds of Local Fractional Metric Dimensions of Connected Networks by Muhammad Javaid, Mohsin Raza, Poom Kumam, Jia-Bao Liu

“…A complete characterization of the connected networks whose LFMDs attain the exactly lower bound is obtained and some particular classes of networks (complete networks, generalized windmill and <inline-formula> <tex-math notation="LaTeX">$h$ </tex-math></inline-formula>-level windmill) whose LFMDs attain the exactly upper bound are also addressed. …”
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Tokamak edge localized mode onset prediction with deep neural network and pedestal turbulence by Semin Joung, David R. Smith, G. McKee, Z. Yan, K. Gill, J. Zimmerman, B. Geiger, R. Coffee, F.H. O’Shea, A. Jalalvand, E. Kolemen

“…We further investigate the network generality in terms of the selected frequency band to ensure the use of BES-ELMnet for various operation regimes without changing the trained architecture. …”
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Deep Convolutional Network Aided by Non-Local Method for Hyperspectral Image Denoising by Gabriel A. De Oliveira, Larissa Medeiros De Almeida, Eduardo R. De Lima, Luis Geraldo P. Meloni

“…All the bands paired with their pre-denoised versions in a second step feed a Convolutional Neural Network. To network generalization, one of the inputs is the noise level of the input image, allowing a single model to work with different noise levels. …”
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Enhancing the integration of the GPS/INS during GPS outage using LWT-IncRGRU by H. Alaeiyan, M.R. Mosavi, A. Ayatollahi

“…Moreover, regularization is a technique that improves the network's generalization and avoids overfitting by adding some constraints or penalties to the model. …”
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A Deep Neural Network Architecture for Intrusion Detection in Software-Defined Networks by Somayeh Jafari Horestani, Somayeh Soltani, Seyed Amin Hosseini Seno

“…Therefore, the introduction of a high-precision intrusion detection system is critical for the network. Generally, the general framework of the proposed intrusion detection models is the use of text classification, and today deep neural networks (DNNs) are one of the top classifiers. …”
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A Robust Dirichlet Reputation and Trust Evaluation of Nodes in Mobile Ad Hoc Networks by Eric Chiejina, Hannan Xiao, Bruce Christianson, Alexios Mylonas, Chidinma Chiejina

“…To improve the security in MANETs, reputation and trust management systems (RTMS) have been developed to mitigate some attacks and threats arising from abnormal behaviours of nodes in networks. Generally, most reputation and trust systems in MANETs focus mainly on penalising uncooperative network nodes. …”
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An adaptive estimation method to predict thermal comfort indices man using car classification neural deep belief by Alireza Entezari, Fatemeh Mayvaneh, Khosro Rezaie, Fatemeh Rahimi

“…The power of neural networks, prediction of future performance network (generalized orientation) it simply is not possible and the new model presented in this paper have been restricted Boltzmann machine-based neural networks or neural networks is used deep belief. …”
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Convergence of a Gradient-Based Learning Algorithm With Penalty for Ridge Polynomial Neural Networks by Qinwei Fan, Jigen Peng, Haiyang Li, Shoujin Lin

“…In order to make the convergence speed faster and the network generalization ability stronger, we introduce a regularization model for RPNN with Group Lasso penalty, which deals with the structural sparse problem at the group level in this paper. …”
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Identification of the Structure of Liquid–Gas Flow in a Horizontal Pipeline Using the Gamma-Ray Absorption and a Convolutional Neural Network by Robert Hanus, Marcin Zych, Piotr Ochał, Małgorzata Augustyn

“…The latest publications in this field concern the use of computational intelligence methods for flow structure recognition, which include, for example, expert systems and artificial neural networks. Generally, machine learning methods exploit various characteristics of sensors signals in the value, time, frequency, and time–frequency domain. …”
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Generalizable Machine Learning in Neuroscience Using Graph Neural Networks by Paul Y. Wang, Paul Y. Wang, Sandalika Sapra, Sandalika Sapra, Vivek Kurien George, Vivek Kurien George, Gabriel A. Silva, Gabriel A. Silva, Gabriel A. Silva

“…In our experiments, we found that graph neural networks generally outperformed structure agnostic models and excel in generalization on unseen organisms, implying a potential path to generalizable machine learning in neuroscience.…”
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Review of Indoor Positioning: Radio Wave Technology by Tan Kim Geok, Khaing Zar Aung, Moe Sandar Aung, Min Thu Soe, Azlan Abdaziz, Chia Pao Liew, Ferdous Hossain, Chih P. Tso, Wong Hin Yong

“…The indoor positioning system (IPS) is becoming increasing important in accurately determining the locations of objects by the utilization of micro-electro-mechanical-systems (MEMS) involving smartphone sensors, embedded sources, mapping localizations, and wireless communication networks. Generally, a global positioning system (GPS) may not be effective in servicing the reality of a complex indoor environment, due to the limitations of the line-of-sight (LoS) path from the satellite. …”
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Modeling Evapotranspiration Response to Climatic Forcings Using Data-Driven Techniques in Grassland Ecosystems by Xianming Dou, Yongguo Yang

“…These models were compared with the extensively utilized data-driven models, including artificial neural network, generalized regression neural network, and support vector machine (SVM). …”
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Robust Automatic Modulation Classification in Low Signal to Noise Ratio by To Truong An, Byung Moo Lee

“…TADs reduce noise power and clean input signals, which are then passed on to CNN for classification. The TAD network generally consists of three components: the batch normalization layer, the autoencoder, and the threshold denoise. …”
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Domain Generalization Model of Deep Convolutional Networks Based on SAND-Mask by Jigang Wang, Liang Chen, Rui Wang

“…The SAND-Mask method is extended to the fault diagnosis domain, and the DCNG model (Deep Convolutional Network Generalization) is proposed. Finally, multi-angle experiments were conducted on three publicly available bearing datasets, and diagnostic performances of more than 90%, 99%, and 70% were achieved on all transfer tasks. …”
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Numerical algorithm for neural network recognition of persistent and antipersistent market conditions by Aleksandr I. Ivanov, Dmitriy V. Tarasov

“…The purpose of the work is to synthesize a neural network generalization of the Hurst index (the Hurst neuron is amplified by two additional neurons). …”

Deeply Recursive Low- and High-Frequency Fusing Networks for Single Image Super-Resolution by Cheng Yang, Guanming Lu

“…However, a larger network generally consumes more computational and memory resources, making it difficult to train the network and increasing the prediction time. …”
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