Improved Backpropagation Using Genetic Algorithm for Prediction of Anomalies and Data Unavailability by Gunadi Widi Nurcahyo, Akbari Wafridh, Yuhandri

“…Various methods address these issues, including the Backpropagation Neural Network (BPNN) for data prediction. However, BPNN can get stuck in local minima, resulting in suboptimal error values. …”
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Comparison of Classification Algorithms with Wrapper-Based Feature Selection for Predicting Osteoporosis Outcome Based on Genetic Factors in a Taiwanese Women Population by Hsueh-Wei Chang, Yu-Hsien Chiu, Hao-Yun Kao, Cheng-Hong Yang, Wen-Hsien Ho

“…To elucidate relationships between osteoporosis and SNPs in this population, three classification algorithms were applied: multilayer feedforward neural network (MFNN), naive Bayes, and logistic regression. …”
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REMAINING USEFUL LIFE OF ROLLING BEARING BASED ON t⁃SNE by ZHONG JianHua, HUANG Cong, ZHONG ShunCong, XIAO ShunGen

“…Due to the limited bearing degradation data under actual working conditions,it is impossible to obtain enough degradation data to train the neural network,it is difficult to obtain good prediction results in the deep learning network,so a new fusion method was proposed.Firstly,the features of the original vibration signal was extracted,dozens of dimensional features were obtained through the ensemble empirical mode decomposition(EEMD)and the singular value decomposition(SVD),and the effective features such as kurtosis and mean value commonly used in remaining useful life prediction were added,then the decision tree to filter out 15⁃dimensional features was used the data was obtained by double exponential model fitting and the degraded signal was reduced to a linear trend through t⁃SNE.The linear degradation trend has better generalization in prediction than the exponential trend,and the prediction accuracy is superior to support veotor regression(SVR)and deep belief network(DBN)model.…”
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Mathematical modelling-based blockchain with attention deep learning model for cybersecurity in IoT-consumer electronics by Hayam Alamro, Mohammed Maray, Jawhara Aljabri, Saad Alahmari, Monir Abdullah, Jehad Saad Alqurni, Faiz Abdullah Alotaibi, Abdelmoneim Ali Mohamed

“…Besides, the attention long short-term memory neural network (ALSTM-NN) model is employed to detect and classify cyberattacks. …”
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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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Transformers for Neuroimage Segmentation: Scoping Review by Maya Iratni, Amira Abdullah, Mariam Aldhaheri, Omar Elharrouss, Alaa Abd-alrazaq, Zahiriddin Rustamov, Nazar Zaki, Rafat Damseh

“…Currently, hybrid convolutional neural network-transformer architectures achieve state-of-the-art performances on benchmark datasets over standalone models. …”
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Innovative Deep Learning Architecture for the Classification of Lung and Colon Cancer From Histopathology Images by Menatalla M. R. Said, Md. Sakib Bin Islam, Md. Shaheenur Islam Sumon, Semir Vranic, Rafif Mahmood Al Saady, Abdulrahman Alqahtani, Muhammad E. H. Chowdhury, Shona Pedersen

“…This study leveraged the LC25000 dataset, encompassing 25,000 images of lung and colon tissue, introducing an innovative approach by employing a self-organized operational neural network (Self-ONN) to accurately detect lung and colon cancer in histopathology images. …”
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Efficient Pattern Recognition of Sundanese Script Variants Using CNN by Muhammad Husni Wahid, Erik Iman Heri Ujianto

“…This research aims to apply pattern recognition technology, specifically through the Convolutional Neural Network (CNN) approach, in identifying and translating Sundanese script accurately. …”
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Wetland vegetation mapping improved by phenological leveraging of multitemporal nanosatellite images by Lucas T. Fromm, Laurence C. Smith, Ethan D. Kyzivat

“…Maximum Likelihood (MLC), Support Vector Machine (SVM), and Artificial Neural Network (ANN) classification algorithms are tested on individual, monthly- and multi-seasonal composite images. …”
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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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Physics-informed deep learning quantifies propagated uncertainty in seismic structure and hypocenter determination by Ryoichiro Agata, Kazuya Shiraishi, Gou Fujie

“…Here, we address this issue by employing a physics-informed deep learning (PIDL) approach that quantifies uncertainty in two-dimensional seismic velocity structure modeling and its propagation to hypocenter determination by introducing neural network ensembles trained on active seismic survey data, earthquake observation data, and the physical equation of wavefront movement. …”
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Multi-scale aware dual path network for face detection in resource-constrained edge computing environment by Qi QI, Yingxin MA, Jingyu WANG, Haifeng SUN, Jianxin LIAO

“…Aiming at the problem that face detectors with complex deep neural structures are difficult to deploy in the resource-constrained edge computing environment,to reduce the resource consumption while maintain the accuracy in complex scenes such as multi-scale face changes,occlusion,blur,and illumination,SDPN(multi-scale aware dual path network) for face detection was proposed.The Face-ResNet (face residual neural network) was improved,and a dual path shallow feature extractor was used to understand the multi-scale information of the image through parallel branches.Then the deep and shallow feature fusion module,a combination of the underlying image information and the high-level semantic feature,was used in conjunction with the multi-scale awareness training strategy to supervise the multi-branch learning discriminating features.The experimental results show that SDPN can extract more diversified features,which effectively improve the accuracy and robustness of face detection while maintaining the efficiency of the model and low inference delay.…”
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An artificial intelligence optimization of NOx conversion efficiency under dual catalytic mechanism reaction based on multi-objective gray wolf algorithm by Zhiqing Zhang, Zicheng He, Yuguo Wang, Feng Jiang, Weihuang Zhong, Bin Zhang, Yanshuai Ye, Zibin Yin, Dongli Tan

“…In this study, a fuzzy gray relational analysis coupled with random forest (RF) and back propagation artificial neural network (BP-ANN) model was developed. This model was trained based on the Langmuir-Hinshelwood and Eley-Rideal coupled mechanism for SCR reaction mechanism, and had good fitting effect on the heat transfer rate, catalytic efficiency and ammonia (NH3) slip rate of the catalytic reaction under loading conditions. …”
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Research and Implementation of Fast-LPRNet Algorithm for License Plate Recognition by Zhichao Wang, Yu Jiang, Jiaxin Liu, Siyu Gong, Jian Yao, Feng Jiang

“…Aiming at the problems of traditional license plate recognition algorithms such as the low accuracy, slow speed, and the recognition rate being easily affected by the environment, a Convolutional Neural Network- (CNN-) based license plate recognition algorithm-Fast-LPRNet is proposed. …”
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Fractional Analysis of MHD Boundary Layer Flow over a Stretching Sheet in Porous Medium: A New Stochastic Method by Imran Khan, Hakeem Ullah, Hussain AlSalman, Mehreen Fiza, Saeed Islam, Muhammad Shoaib, Muhammad Asif Zahoor Raja, Abdu Gumaei, Farkhanda Ikhlaq

“…In this article, an effective computing approach is presented by exploiting the power of Levenberg-Marquardt scheme (LMS) in a backpropagation learning task of artificial neural network (ANN). It is proposed for solving the magnetohydrodynamics (MHD) fractional flow of boundary layer over a porous stretching sheet (MHDFF BLPSS) problem. …”
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Joint QoS prediction for Web services based on deep fusion of features by Jianxun LIU, Linghang DING, Guosheng KANG, Buqing CAO, Yong XIAO

“…In order to solve the problem of insufficient accuracy of Web service QoS prediction, a joint QoS prediction method for Web services based on the deep fusion of features was proposed with considering of the hidden environmental preference information in QoS and the common features of multi-class QoS.First, QoS data was modeled as a user-service bipartite graph and multi-component graph convolution neural network was used for feature extraction and mapping, and the weighted fusion method was used for the same dimensional mapping of multi-class of QoS features.Subsequently, the attention factor decomposition machine was used to extract the first-order features, second-order interactive features, and high-order interactive features of the mapped feature vector.Finally, the results of each part were combined to achieve the joint QoS prediction.The experimental results show that the proposed method is superior to the existing QoS prediction methods in terms of root mean square error (RMSE) and average absolute error (MAE).…”
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One-Shot M-Array Pattern Based on Coded Structured Light for Three-Dimensional Object Reconstruction by Xiaojun Jia, Zihao Liu

“…A deep convolution neural network (DCNN) and chain sequence features are used to accurately classify pattern elements and key points (KPs), respectively. …”
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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. …”
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Improving source code suggestion with code embedding and enhanced convolutional long short‐term memory by Yasir Hussain, Zhiqiu Huang, Yu Zhou

“…First, DeepSN uses an enhanced hierarchical convolutional neural network combined with code‐embedding to automatically extract the top‐notch features of the source code and to learn useful semantic information. …”
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Estimating Body Related Soft Biometric Traits in Video Frames by Olasimbo Ayodeji Arigbabu, Sharifah Mumtazah Syed Ahmad, Wan Azizun Wan Adnan, Salman Yussof, Vahab Iranmanesh, Fahad Layth Malallah

“…This paper presents an approach for estimating body related soft biometrics; specifically we propose a new approach based on body measurement and artificial neural network for predicting body weight of subjects and incorporate the existing technique on single view metrology for height estimation in videos with low frame rate. …”
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