Feature Importance Analysis for Compressive Bearing Capacity of HSCM Piles Based on GA-BPNN by Fangzhou Chu, Jiakuan Ma, Yang Luan, Shilin Chen

“…To address the complex pile–soil interaction mechanisms in predicting the compressive bearing capacity of HSCM piles (Helix Stiffened Cement Mixing piles) in marine soft soil regions, this study proposes an intelligent prediction method based on a GA-BPNN (Genetic Algorithm-Optimized Back Propagation Neural Network). …”
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Optimization of the heat recovery performance of enhanced geothermal system based on PSO-GA-BP neural networks and analytic hierarchy process by Ling Zhou, Jingchao Sun, Yanjun Zhang, Yunjuan Chen, Honglei Lei

“…Based on the numerical simulation data, optimized Back-Propagation Neural Network (BPNN) prediction models combining the Particle Swarm Optimization (PSO) and the Genetic Algorithm (GA) were developed to investigate the impact of various factors on the heat recovery performance of a three-horizontal-well EGS in the Zhacang geothermal field. …”
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Improvement of Single-phase Four-quadrant Converter Dual-loop Control by LI Wei

“…Because of the shortcoming of dual-loop control based on coordinate transformation method for single-phase fourquadrant rectifier, the mathematical model on rotational coordinates was proposed. The improved algorithm based on current state feedback and predictive current control was proposed and implemented. …”
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A Proactive Complex Event Processing Method for Large-Scale Transportation Internet of Things by Yongheng Wang, Kening Cao

“…Based on a multilayered adaptive dynamic Bayesian model, a Bayesian network structure learning algorithm using search-and-score is proposed to support accurate predictive analytics. …”
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Artificial Intelligence in Pediatric Blood Transfusion during Anesthesia: A Scoping Review by Parisa Akbarpour, Parisa Moradimajd, Azam Saei, Maryam Aligholizadeh, Siavash Sangi

“…Relevant keywords, including artificial intelligence, machine learning, predictive model, neural network, predictive algorithm, blood transfusion, children, pediatric, neonates, anesthesia, surgery, and operation, were extracted from the Medical Subject Headings (MeSH). …”
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Time-delayed vibration control and parameter optimization of semi-active vehicle suspension designed for random road excitation by Yong Guo, Yong-Jing Li, Yan-Bo Wei

“…Under the influence of road excitations, the acquisition of optimal time-delayed feedback control parameters is deemed crucial for the improvement of the vibration reduction effect of semi-active vehicle suspension systems. …”
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OBJECT DETECTION IN COMPUTER VISION SYSTEMS: A VISUAL SALIENCY BASED APPROACH by V. A. Kachurka, K. .. Madani, C. .. Sabourin, V. A. Golovko, P. A. Kachurka

“…Experimental results show viability and efficiency of this approach as compared with state-of-art algorithms, and predict its usability on the broader class of tasks - applied variations of eye fixation problem.…”
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A Reinforcement Learning-Based Generative Approach for Event Temporal Relation Extraction by Zhonghua Wu, Wenzhong Yang, Meng Zhang, Fuyuan Wei, Xinfang Liu

“…To bridge the gap between the optimization objective and task performance metrics, we employ the REINFORCE algorithm to optimize our generative model, designing a novel reward function to simultaneously capture the accuracy of temporal prediction and the quality of generation. …”
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Differential diagnosis of hematogenous osteomyelitis and malignant bone tumors by A. N. Tkachenko, O. F. Nur, A. A. Korneenkov, L. E. Sharova, I. E. Itskovich, I. I. Kushnirchuk, A. Yu. Cherkasov

“…Indicators of the validity of the test was: Sensitivity – 83.05 %, Specificity (Sp) – 86.67 %. Positive Predictive Value (PPV) was 96.08 %, Negative Predictive Value (NPV) – 56.52 %, Accuracy – 83.78 %, which allowed to shorten the time of examination and send patients to specialized hospitals.…”
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Physics-informed modeling and process optimization of friction stir welding of AA7075-T6 with a zinc interlayer by Dejene Alemayehu Ifa, Dame Alemayehu Efa, Naol Dessalegn Dejene, Sololo Kebede Nemomsa

“…The models that are included in the hybrid framework of ANN, SVR, and RFR have all demonstrated noteworthy prediction strengths. The optimum FSW parameters were shown to be: a tool speed of 600 rpm, a pin radius of 5.71 mm, a shoulder radius of 20 mm, and a plunge force of 6369.48 N, with a predicted peak temperature value of 675.71 K. …”
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The Relationship Between Horizontal Jumping and Sprinting Ability Across Sexes in Young Active Adults by Adam Kleeberger, Dana Agar-Newman, Ming-Chang Tsai, Marc Klimstra

“…Further, athlete mass is a significant factor in the prediction of acceleration ability but not maximum speed, and horizontal jumps were significant factors in the prediction of max speed but not acceleration.…”
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Multiple Regression-Based Dynamic Amplification Factor Investigation of Monorail Tourism Transit Systems by Hong Zhang, Changxing Wu, Wenlong Liu, Shiqi Wei, Yonggang Wang

“…On this basis, the key regression parameters were selected by using the Pearson correlation coefficient method and the random forest algorithm, and the DAFs prediction model was constructed based on the least absolute shrinkage and selection operator (LASSO) regression theory. …”
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DAFDM: A Discerning Deep Learning Model for Active Fire Detection Based on Landsat-8 Imagery by Xu Gao, Wenzhong Shi, Min Zhang, Lukang Wang

“…The proposed method outperforms other AF detection algorithms, achieving IoU and F1-score of 87.28% and 93.21%, respectively. …”
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ALGORITMOS SUPERVISADOS PARA LA PREDICCIÓN DEL ANCHO DE BANDA DE LAS APLICACIONES EN AMAZON WEB SERVICE DESDE UNA PYME RURAL by Ramiro Osorio Diaz, Martha Yaneth Segura Ruiz, Mauricio Alonso Villalba

“…A comparative study of threeneural network algorithms that model a multilayer neural network is performed, selecting the one that has a minimumerror that approaches zero; the selected algorithm is trained from a data source to predict the network traffic thatconnects to the cloud. …”
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Reducing False Alarm in Target Sidelobes Using Time-Varying Trajectories in Range-Doppler Diagram With Conditional 3D-DCNN by Jiyeon Choi, Daegun Oh, Youngwook Kim

“…The proposed method was validated using frequency-modulated continuous wave radar to detect low-RCS targets and demonstrated a reduction in FAs in clutter environments. Verification with 200 simulation datasets showed a 99.8 % reduction in FAs excluding the sidelobe region along the range axis compared to CFAR and a 95.22 % reduction compared to 3D-DCNN, while all FAs in the Doppler sidelobe region were eliminated (100 % reduction). …”
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Integrated Bidding and Battery Scheduling in a Microgrid for Sealed-Bid Double Auction Power Trading With Peer Microgrids Under Uncertainty and Its Blockchain-Based Implementation by Zubin J. B., Sunitha R., Gopakumar Pathirikkat

“…The Q-learning relies solely on its historical bidding outcomes without attempting to predict the bids of other participants. In parallel, battery operations are optimized using a hybrid method that combines Genetic Algorithm (GA) and Simulated Annealing (SA), explicitly incorporating the bid buffer capacity to align scheduling with market commitments. …”
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Evaluation of Baby Leaf Products Using Hyperspectral Imaging Techniques by Antonietta Eliana Barrasso, Claudio Perone, Roberto Romaniello

“…Utilizing a large dataset of 261 wavelengths from the hyperspectral imaging system, the feature selection minimum redundancy maximum relevance (FS-MRMR) algorithm was applied, leading to the development of a neural network-based prediction model. …”
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An Investigation in Analyzing the Food Quality Well-Being for Lung Cancer Using Blockchain through CNN by Mohamed Abdelkader Aboamer, Mohamed Yacin Sikkandar, Sachin Gupta, Luis Vives, Kapil Joshi, Batyrkhan Omarov, Sitesh Kumar Singh

“…This research is going to analyze the extension of blockchain with the help of CNN for lung cancer prediction and making food safer. CNN algorithm has been trained with a huge number of images by altering the filters, features, epoch values, padding value, kernel size, and resolution. …”
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Prognosticating salvage stereotactic radiosurgery outcomes in relapsed primary central nervous system lymphoma: A machine learning-driven decision tree analysis by Huili Zhao, Shenao Zhang, Lang Chen, Xin Liu, Aihong Cao, Peng Du

“…The cohort was randomly divided into training and validation sets (7:3 ratio). The C5.0 algorithm was employed to develop a decision tree model for predicting treatment response. …”
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Application of Categorical Boosting to Modelling the Friction Behaviour of DC05 Steel Sheets in Strip Drawing Test by Marek Szewczyk, Krzysztof Szwajka, Sherwan Mohammed Najm, Salwa O Mohammed

“…A Shapley decision plot exhibits the coefficient of friction prediction models via cumulative SHapley Additive exPlanations (SHAP) data. …”
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