Prediction of BlastInduced Ground Vibration (BIGV) of Metro Construction Using Difference Evolution AlgorithmOptimized Gaussian Process (DE-GP) by Tengfei Jiang, Annan Jiang, Shuai Zheng, Mengfei Xu

“…The proposed model is compared with the empirical formulas, least square support vector machine (LSSVM), artificial neural network (ANN), and GP model, and its prediction performance is evaluated by statistical indicators such as root mean square error (RMSE). …”
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Hybrid Wind Speed Forecasting Model Study Based on SSA and Intelligent Optimized Algorithm by Wenyu Zhang, Zhongyue Su, Hongli Zhang, Yanru Zhao, Zhiyuan Zhao

“…The present study investigated singular spectrum analysis (SSA) with a reduced parameter algorithm in three time series models, the autoregressive integrated moving average (ARIMA) model, the support vector machine (SVM) model, and the artificial neural network (ANN) model, to forecast the wind speed in Shandong province, China. …”
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Important Citation Identification by Exploding the Sentiment Analysis and Section-Wise In-Text Citation Weights by Shahzad Nazir, Muhammad Asif, Shahbaz Ahmad, Hanan Aljuaid, Rimsha Iftikhar, Zubair Nawaz, Yazeed Yasin Ghadi

“…The first technique is based on extracting the different sections of the research articles and performing citation count. We applied Neural Network and Multiple Regression on section-wise citations for automatic weight assignment. …”
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Mathematical Modeling of Cyberattack Defense Mechanism Using Hybrid Transfer Learning With Snow Ablation Optimization Algorithm in Critical Infrastructures by Mohamad Khairi Ishak

“…For the cybersecurity classification process, the presented CDMHTL-SAOA technique applies the hybrid of convolutional neural network and bi-directional long short-term memory (CNN-BiLSTM) method. …”
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Person Detection for an Orthogonally Placed Monocular Camera by Pavel Skrabanek, Petr Dolezel, Zdenek Nemec, Dominik Stursa

“…The first approach is the utilization of an appropriate convolutional neural network (ConvNet), which is currently the prevailing approach in computer vision. …”
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Automated Measurements of Tooth Size and Arch Widths on Cone-Beam Computerized Tomography and Scan Images of Plaster Dental Models by Thong Phi Nguyen, Jang-Hoon Ahn, Hyun-Kyo Lim, Ami Kim, Jonghun Yoon

“…The third step uses a decentralized convolutional neural network to calculate key points representing the parameters. …”
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Analysis of ADR reports of cetuximab based on the FDA adverse event reporting system database by Shuai Zhao, Yan Wang, Xiaoli Deng, Xi Chen, Zhaoyi Lu

“…Disproportionality analyses, including the reporting odds ratio (ROR), the proportional reporting ratio (PRR), the Bayesian confidence propagation neural network (BCPNN), and the empirical Bayesian geometric mean (EBGM) algorithms, were employed to quantify the signals of cetuximab-associated AEs. …”
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Multiobjective Neuro-Fuzzy Controller Design and Selection of Filter Parameters of UPQC Using Predator Prey Firefly and Enhanced Harmony Search Optimization by Koganti Srilakshmi, Gummadi Srinivasa Rao, Katragadda Swarnasri, Sai Ram Inkollu, Krishnaveni Kondreddi, Praveen Kumar Balachandran, C. Dhanamjayulu, Baseem Khan

“…The reference signals for voltage source converters of UPQC are produced by the Levenberg–Marquardt back propagation (LMBP) trained artificial neural network control (ANNC). This method removes the necessity for conventional dq0, abc complex shifting. …”
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Resnet-1DCNN-REA bearing fault diagnosis method based on multi-source and multi-modal information fusion by Xu Chen, Wenbing Chang, Yongxiang Li, Zhao He, Xiang Ma, Shenghan Zhou

“…At the same time, the time-frequency statistical features of the fused 1D signal were extracted from the integrated perspective of time and frequency domains and inputted into the improved 1D convolutional neural network model based on the residual block and attention mechanism (1DCNN-REA) model to realize fault diagnosis. …”
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Multiobjective Optimization of Surface Roughness and Tool Wear in High-Speed Milling of AA6061 by Machine Learning and NSGA-II by Anh-Tu Nguyen, Van-Hai Nguyen, Tien-Thinh Le, Nhu-Tung Nguyen

“…Four ML models were used to predict Ra and Vbmax: linear regression (LIN), support vector machine regression (SVR), a gradient boosting tree (GBR), and an artificial neural network (ANN). The input variables were the significant factors that affect the surface quality and tool wear: the feed rate, depth of cut, cutting speed, and cutting time. …”
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Integrating electrocardiogram and fundus images for early detection of cardiovascular diseases by K. A. Muthukumar, Dhruva Nandi, Priya Ranjan, Krithika Ramachandran, Shiny PJ, Anirban Ghosh, Ashwini M, Aiswaryah Radhakrishnan, V. E. Dhandapani, Rajiv Janardhanan

“…These EMD values were then concatenated, forming a comprehensive feature set that was fed into a Neural Network classifier. This approach, leveraging the FFT’s spectral insights and EMD’s capability to capture nuanced data differences, offers a robust representation for CVD classification. …”
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The Significant Effects of Threshold Selection for Advancing Nitrogen Use Efficiency in Whole Genome of Bread Wheat by Mohammad Bahman Sadeqi, Agim Ballvora, Said Dadshani, Md. Nurealam Siddiqui, Mohammad Kamruzzaman, Ahossi Patrice Koua, Jens Léon

“…By incorporating the neural network algorithm, it is possible to improve the reliability of FDR threshold and increase the probability of identifying true genetic associations while minimizing the risk of false positives in GWAS results.…”
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Identification of Spectrally Similar Materials From Multispectral Imagery Based on Condition Number of Matrix by Maozhi Wang, Shu-Hua Chen, Jun Feng, Wenxi Xu, Daming Wang

“…The results for a case study to identify water, ice, snow, shadow, and other materials from Landsat 8 OLI data indicate that SF-CNM can identify the materials specified by the given samples successfully and accurately and that SF-CNM significantly outperforms those of spectral angle mapper algorithm, Mahalanobis classifier, maximum likelihood, and artificial neural network, and produces the performance similar to, even slightly better than that of support vector machine.…”
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Abnormality detection in nailfold capillary images using deep learning with EfficientNet and cascade transfer learning by Mona Ebadi Jalal, Omar S. Emam, Cristián Castillo-Olea, Begoña García-Zapirain, Adel Elmaghraby

“…Our proposed model achieved superior performance, with accuracy, precision, recall, F1 score, and ROC_AUC of 1.00, significantly outperforming both models of single transfer learning on the pre-trained EfficientNet-B0 and cascade transfer learning on a convolutional neural network, which each attained an accuracy, precision, recall, and F1 score of 0.67 and a ROC_AUC of 0.83. …”
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Improving Proton Exchange Membrane Fuel Cell Operational Reliability Through Cabin-Based Fuzzy Control in Costal Standalone Observation Systems in Antarctica by Jin Wang, Yinke Dou, Guangyu Zuo, Bo Fan, Yuru Xing

“…A temperature-coordinated control system leveraging a BP neural network, fuzzy logic rules, and the fuzzy-based active disturbance rejection control (Fuzzy-ADRC) strategy are proposed to ensure that the temperature of the PEMFC and cabin can reach the optimal state rapidly and that the output voltage is stable. …”
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Portable optical spectroscopy and machine learning techniques for quantification of the biochemical content of raw food materials by Cosimo Ricci, Agata Gadaleta, Annamaria Gerardino, Angelo Didonna, Giuseppe Ferrara, Francesca Romana Bertani

“…Results Considering the specific samples, the obtained results of the classification models indicate a validation mean absolute error of 0.8% (percentage of total protein content in dry matter) for two species of wheat using Convolutional Neural Network following normalization procedures and 0.32% using Partial Least Square (PLS) analysis applied to Tritordeum samples; visible reflectance spectra have been used to discriminate the two cereal species. …”
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Intelligent Ensemble Deep Learning System for Blood Glucose Prediction Using Genetic Algorithms by Dae-Yeon Kim, Dong-Sik Choi, Ah Reum Kang, Jiyoung Woo, Yechan Han, Sung Wan Chun, Jaeyun Kim

“…Although there are numerous deep learning algorithms available, this study applied five algorithms, namely, recurrent neural network (RNN), which is optimized for sequence data (e.g., time-series), and RNN-based algorithms (e.g., long short-term memory (LSTM), stacked LSTM, bidirectional LSTM, and gated recurrent unit). …”
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Regional Boundary Control of Traffic Network Based on MFD and FR-PID by Xin Yang, Juncheng Chen, Mantun Yan, Zhao He, Ziyan Qin, Jiandong Zhao

“…In order to effectively alleviate the traffic congestion of the regional road network, aiming at the problem of lack of accurate OD data of the road network, a regional boundary control method of the traffic network based on fuzzy RBF neural network PID (FR-PID) is proposed by combining the theory of macroscopic fundamental diagram (MFD). …”
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A performance-based generative design framework based on a design grammar for high-rise office towers during early design stage by Liwei Chen, Ye Zhang, Yue Zheng

“…Case study results demonstrate that, with the support of Artificial Neural Network, utilizing this system can not only globally explore the diversity of tower morphologies but also efficiently uncover greater energy-saving potential in complex architectural forms compared to simpler cubic forms, with an improvement of up to 7.76% during the early stages of design. …”
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Unveiling midcrustal seismic activity at the front of the Bolivian altiplano, Cochabamba region by Gonzalo Antonio Fernandez M, Benoit Derode, Laurent Bollinger, Bertrand Delouis, Mayra Nieto, Felipe Condori, Nathan Sarret, Jean Letort, Stephanie Godey, Mathilde Wimez, Teddy Griffiths, Walter Arce

“…This study highlights the initial 6-month seismic bulletin made by manual and automated deep-neural-network based seismic phase picking. We also test the network's ability to resolve focal mechanisms of moderate to small events with a combined inversion of waveforms and polarities. …”
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