A recurrent sigma pi sigma neural network by Fei Deng, Shibin Liang, Kaiguo Qian, Jing Yu, Xuanxuan Li

“…The RSPSNN is successfully applied to the function approximation problem, prediction problem, parity problem, classification problem, and image simulation, which verifies its effectiveness and practicability.…”
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Dynamic VaR Measurement of Gold Market with SV-T-MN Model by Fenglan Li, Jie Wang, Liyun Su, Bao Yang

“…Secondly, future sample volatility prediction was realized by using approximate filtering algorithm. …”
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Artificial Neural Network Model for Monitoring Oil Film Regime in Spur Gear Based on Acoustic Emission Data by Yasir Hassan Ali, Roslan Abd Rahman, Raja Ishak Raja Hamzah

“…The methods used in this paper shows accurate predictions from ANN and the feed-forward network performance is superior to the Elman neural network.…”
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Cotton T-Shirt Size Estimation Using Convolutional Neural Network by John King D. Alfonso, Ckyle Joshua G. Casumpang, Jocelyn F. Villaverde

“…The estimation accuracy was 70%. Inaccurate predictions were attributed to the precision of body measurements from computer vision and image quality, which needs to be solved in further studies.…”
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Review of the Research on Underwater Explosion Ice-Breaking Technology by Xiao Huang, Zi-Xian Zhong, Xiao Luo, Yuan-Dong Wang

“…Future advancements require multiscale fluid–structure interaction models integrating brine migration effects, enhanced experimental diagnostics for transient processes, and optimized numerical algorithms to enable reliable predictions for engineering applications.…”
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MicroRNA-dependent mechanisms of taxane resistance in breast cancer by V. S. Apollonova, E. I. Sidina, E. V. Tkachenko, A. V. Malek

“…However, currently used algorithms of taxan-based regimens application do not always provide with desire effect. …”
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A comprehensive review on smart manufacturing using machine learning applicable to fused deposition modeling by Swapnil Deokar, Narendra Kumar, Ravi Pratap Singh

“…This study focuses on the use of ML algorithms for predicting part quality of AM parts, such as tensile strength, wear strength, detection of defect, geometric accuracy and minimizing the material waste.…”
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Proteomic-based biomarker discovery reveals panels of diagnostic biomarkers for early identification of heart failure subtypes by Narainrit Karuna, Claire Tonry, Mark Ledwidge, Nadezhda Glezeva, Joe Gallagher, Ken McDonald, Chris J. Watson

“…Moreover, a random forest algorithm demonstrated that combining these candidate biomarkers with BNP measurement significantly improved the prediction of HF subtypes. …”
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Revealing key regulatory factors in lung adenocarcinoma: the role of epigenetic regulation of autophagy-related genes from transcriptomics, scRNA-seq, and machine learning by Xianchang Zeng, Lingyun Wei, Lu Lv, Di Wu, Yingying Shen, Xinliang Lu, Xianghui Kong, Zhijian Cai, Jianli Wang, Jianli Wang

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Exploring the role of ELOVLs family in lung adenocarcinoma based on bioinformatic analysis and experimental validation by Zihan Wang, Wenjing Cui, Long Liang, Jingge Qu, Yuqiang Pei, Danyang Li, Ying Luo, Yue Zhang, Yifan Qiu, Yongchang Sun

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Heterogeneity in willingness to share personal health information: a nationwide cluster analysis of 20,000 adults in Japan by Miho Sassa, Akifumi Eguchi, Keiko Maruyama-Sakurai, Takanori Fujita, Yumi Kawamura, Takayuki Kawashima, Yuta Tanoue, Daisuke Yoneoka, Hiroaki Miyata, Takanori Yamashita, Naoki Nakashima, Shuhei Nomura

“…Clustering analysis using Uniform Manifold Approximation and Projection (UMAP) and Ordering Points to Identify the Clustering Structure (OPTICS) algorithms was performed to identify distinct patterns in sharing preferences. …”
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Machine learning classification of consumption habits of creatine supplements in gym goers by Patrícia C. Magalhães, Samuel Encarnação, Andre C. Schneider, Pedro Forte, José Teixeira, Antonio Miguel Monteiro, Tiago M. Barbosa, Ana M. Pereira

“…The aim is to identify usage patterns and the main factors that influence creatine supplementation, providing a basis for future educational interventions and recommendations for safe and effective use. …”
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Screening and Validation of Potential Biomarkers of Immune Cells in Childhood Asthma Patients via Mendelian Randomization and Machine Learning by Zhang Y, Hai Y, Song B, Xu J, Cao L, Yasen R, Xu W, Zhang J, Hu J

“…LASSO logistic regression and SVM algorithms were used to identify key genes associated with childhood asthma. …”
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Design Optimization Method and Application of High-Efficiency and Variable-Pitch Axial Flow Fan by Lee Chan, Yang Sang Ho, Lee Sang Yeol

“…The design program for constructing axial flow fan geometry is developed by combining fan blade section design and through-flow performance prediction methods. The optimization technique of this study is Hybrid Metaheuristic Algorithm which is combined with the design program to find optimal design values of blade setting angles, camber angles and chord lengths, and then to maximize the fan efficiency. …”
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FUNCTIONING OF THE CAR PARKING PLACES NEAR HOUSES: FORMULATION OF THE PROBLEM OF THE ROAD CITY NETWORK by I. E. Agureev, D. A. Yurchenko

“…The basis of the research was the development in the field of predictive simulation of automobile transport systems. …”
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Multi-Agent System for Emulating Personality Traits Using Deep Reinforcement Learning by Georgios Liapis, Ioannis Vlahavas

“…Conventional personality assessment methods depend on subjective input, while game-based AI predictive methods offer a dynamic and objective framework. …”
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Optimization of Wear Behavior of DLC Coatings Through Optimization of Deposition Conditions by Ming-Der JEAN, Cheng-Wu LIU, Pao-Hua YANG, Wen-Hsien HO

“…Based on genetic algorithm (GA) and fuzzy neural network, a new method for the study of sputtering process is proposed in this paper. …”
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Hybrid modeling for optimizing electrospun polyurethane nanofibrous membranes in air filtration applications by Majid Sohrabi, Milad Razbin

“…An advanced statistical approach is used to systematically collect and analyze data, followed by modeling these relationships using artificial neural networks (ANN) and analytical formulas to enhance predictive accuracy. A genetic algorithm (GA) is subsequently utilized to refine electrospinning parameters, facilitating the production of nanofibers with enhanced filtration efficiency and optimized airflow resistance. …”
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Research on Highly Real-Time and High Precision Localization Method for Rail Transit by HUANG Wenyu, PAN Wenbo, LI Yuanzhengyu, CHEN Zhiwei, YANG Zhenyu, YUAN Chao

“…First, the results from inertial computation are directly used as predictive input values for the filter, to fully leverage the dynamic response characteristics of inertial sensors. …”
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AI-Supported Shared Decision-Making (AI-SDM): Conceptual Framework by Mohammed As'ad, Nawarh Faran, Hala Joharji

“…AI-SDM is a structured, multimodel framework that synthesizes predictive modeling, evidence-based recommendations, and generative AI techniques to produce adaptive, context-sensitive explanations. …”
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