Physics Informed by Deep Learning: Numerical Solutions of Modified Korteweg-de Vries Equation by Yuexing Bai, Temuer Chaolu, Sudao Bilige

“…In this paper, with the aid of symbolic computation system Python and based on the deep neural network (DNN), automatic differentiation (AD), and limited-memory Broyden-Fletcher-Goldfarb-Shanno (L-BFGS) optimization algorithms, we discussed the modified Korteweg-de Vries (mkdv) equation to obtain numerical solutions. …”
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Optimization of Solar Panel Deployment Using Machine Learning by Shoaib Kamal, P. S. Ramapraba, Avinash Kumar, Bikash Chandra Saha, M. Lakshminarayana, S. Sanal Kumar, Anitha Gopalan, Kuma Gowwomsa Erko

“…The study takes into concern several topologies that includes series parallel topology, parallel topology, bridge link topology, honeycomb topology, and total cross tied. The artificial neural network-based topology reconfiguration strategy allows for optimal working conditions for PV arrays. …”
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Deep learning for compressed sensing based sparse channel estimation in FDD massive MIMO systems by Yuan HUANG, Yigang HE, Yuting WU, Tongtong CHENG, Yongbo SUI, Shuguang NING

“…For FDD massive multi-input multi-output (MIMO) downlink system, a novel deep learning method for compressed sensing based sparse channel estimation was proposed, which was called convolutional compressed sensing network (ConCSNet).In the ConCSNet, the convolutional neural network was utilized to solve the inverse transformation process from measurement vector y to signal h and solve the underdetermined optimization problem through data-driven method without sparsity.Simulation results show that the algorithm can recover the channel state information in massive MIMO Systems with unknown sparsity more quickly and accurately.…”
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Machine learning-based analyses of contributing factors for the development of hypertension: a comparative study by Marenao Tanaka, Yukinori Akiyama, Kazuma Mori, Itaru Hosaka, Keisuke Endo, Toshifumi Ogawa, Tatsuya Sato, Toru Suzuki, Toshiyuki Yano, Hirofumi Ohnishi, Nagisa Hanawa, Masato Furuhashi

“…The AUCs of ML models were 0.765–0.825, and discriminatory capacity was significantly improved in the artificial neural network model compared to that in the logistic regression model.Conclusions The development of hypertension can be simply and accurately predicted by each ML model using systolic blood pressure, age and FLI as selected features. …”
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Evaluation of sustainable energy use in sugarcane production: A holistic model from planting to harvest and life cycle assessment by Molood Behnia, Mohammad Ghahderijani, Ali Kaab, Marjan Behnia

“…The analysis compares Artificial Neural Network and Adaptive Neuro-Fuzzy Inference Systems models for predicting energy outputs and environmental effects. …”
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Individual behavior tracking of heifers by using object detection algorithm YOLOv4 by Sarah Jahn, Gabriel Schmidt, Lisa Bachmann, Helen Louton, Timo Homeier-Bachmann, Anne K. Schütz

“…For each model, the neural network YOLOv4 was adapted as a detector and trained with an own training set (685 images and 160 images, respectively). …”
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Enhanced automated text categorization via Aquila optimizer with deep learning for Arabic news articles by Muhammad Swaileh A. Alzaidi, Alya Alshammari, Abdulkhaleq QA Hassan, Shouki A. Ebad, Hanan Al Sultan, Mohammed A. Alliheedi, Ali Abdulaziz Aljubailan, Khadija Abdullah Alzahrani

“…In the area of text classification for Arabic news articles, deep learning (DL) methods, namely recurrent neural network (RNN) and convolutional neural network (CNN), were effectively used. …”
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Wearable Regionally Trained AI-Enabled Bruxism-Detection System by Anusha Ishtiaq, Jahanzeb Gul, Zia Mohy Ud Din, Azhar Imran, Khalil El Hindi

“…The augmented data has been trained, validated, and tested on six machine-learning classifiers and three deep-learning models. The Recurrent Neural Network provided the highest accuracy 0.99 and a recall value 0.98 for the temporalis muscle dataset. …”
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A tactile sensor for recognition of softness using interlocking structure of carbon nanoparticle- polydimethylsiloxane composite by Sangmin Lee, Jaewon Jang, Wanjun Park

“…This is supported by tests conducted using a one-dimensional convolutional neural network (1D-CNN).…”
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EMG- BASED HAND GESTURE RECOGNITION USING DEEP LEARNING AND SIGNAL-TO-IMAGE CONVERSION TOOLS by SABRINA AKTER, BIMAL KUMAR PRAMANIK, MD EKRAMUL HAMID

“…A very deep convolutional neural network (CNN) is proposed as the gesture classifier. …”
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A Novel Relative Navigation Control Strategy Based on Relation Space Method for Autonomous Underground Articulated Vehicles by Fengqian Dou, Yu Meng, Li Liu, Qing Gu

“…In the RSM, a self-organizing, competitive neural network is used to identify the space around the vehicle, and the spatial geometric relationships of the identified space are used to determine the vehicle’s optimal driving direction. …”
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Real-Time Visualization Optimization Management Simulation of Big Data Stream on Industrial Heritage Cloud Platform by Mengya Gao

“…The big data prediction model of the GRU neural network based on a spark distributed framework is constructed to realize the prediction of industrial genetic data. …”
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Detection of Two-Level Inverter Open-Circuit Fault Using a Combined DWT-NN Approach by Bilal Djamel Eddine Cherif, Azeddine Bendiabdellah

“…This paper work addresses a diagnostic technique based on the discrete wavelet transform (DWT) algorithm and the approach of neural network (NN), for the detection of an inverter IGBT open-circuit switch fault. …”
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An Efficient Algorithm for Ill-Conditioned Separable Nonlinear Least Squares by Jiayan Wang, Lanlan Guo, Zongmin Li, Xueqin Wang, Zhengqing Fu

“…Numerical experiments are performed using RBF neural network data, and the experimental results are analyzed in terms of both qualitative and quantitative indicators. …”
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CNN-Based Channel Estimation Method for OTFS System in Satellite-Ground Scenario by Cheng GUO, Le YU, Lidong ZHU

“…Orthogonal time frequency space (OTFS) is fully applied in high Doppler communication scenarios due to its good Doppler frequency bias and time delay adaptability.The channel estimation methods for OTFS systems have shortcomings such as high complexity and poor BER performance.A CNN-based channel estimation method for OTFS systems in the terrestrial-satellite scenario using a convolutional neural network (CNN) approach was proposed.Simulation results showed that the deep learning-based method outperformed the conventional method in terms of algorithm complexity and BER in the terrestrial-satellite scenario, thus demonstrating that deep learning is a promising tool for channel estimation in OTFS systems.…”
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A Scheme Based on Deep Learning for Fruit Classification by Ali Orangzeb Panhwar, Anwar Ali Sathio, Nadeem Manzoor Shah, Sumaira Memon

“…We used a Convolutional Neural Network (CNN) methodology involving comparing a custom-built CNN and the VGG pre-trained models. …”
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Design of knowledge enhanced semantic communication receiver by Rongpeng LI, Bingyan WANG, Honggang ZHANG, Zhifeng ZHAO

“…To address the problem that existing semantic communication do not make sufficient use of prior knowledge and have limited decoding capability at the receiver side, a knowledge enhanced semantic communication framework was proposed, in which the receiver could more actively utilize the prior knowledge in the knowledge base for semantic reasoning and decoding, without extra modifications to the neural network structure of the transmitter.Specifically, a transformer-based knowledge extractor was designed to find relevant factual triples for the received noisy signal.Extensive simulation results on the WebNLG dataset demonstrate that the proposed framework has significantly improved performance on the basis of knowledge graph enhanced decoding.…”
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INTELLIGENT PREDICTION METHOD ON STABILITY OF THIN-WALL STEEL COMPONENT WITH NON CONTINUOUS CROSS SECTION by SONG YiMing, LV ZhiJun, CHEN Dong, WU YongMei

“…According to the characteristics of the non continuous cross section,based on performance testing and finite element analysis of columns,with the method of BP neural network intelligent stability prediction,the stability prediction model of the columns is established. …”
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RBF Nonsmooth Control Method for Vibration of Building Structure with Actuator Failure by Jianhui Wang, Chunliang Zhang, Houyao Zhu, Xiaofang Huang, Li Zhang

“…In order to accommodate the actuator failure, the finite-time stable nonsmooth control method with RBF neural network is used to suppress the structural vibration. …”
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Android malware detection method based on byte-code image and deep learning by Tieming CHEN, Binbin XIANG, Mingqi LV, Bo CHEN, Xie JIANG

“…Finally, the convolutional neural network as classifier was employed to classify aforementioned images. …”
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