Automatic Identification of Critical Damage Value with In-situ Shearing Test and Notched Plate Tensile Test with Image Analysis by Yoshida Yoshinori, Kutsukake Asuka

“…In ADFEA, a machine-learning-based optimization algorithm searches for critical damage values by minimizing the error between simulated and experimental fracture test results. …”
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ADAPTIVE QUASICONTINUUM SIMULATION OF ELASTIC-BRITTLE DISORDERED LATTICES by Karel Mikeš, Milan Jirásek

“…In this work, the QC method is combined with an adaptive algorithm, to obtain correct predictions of crack trajectories in failure simulations. …”
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Current Feed-forward Control for Buck Converter Based on Extended Kalman Filter by LI Hao, LIU Haitao, GAN Weiwei, ZHONG Yuan, DING Leilei, DU Chao

“…In order to improve the response speed of Buck converter to load mutation, it proposed an inductive current feed-forward control algorithm based on extended Kalman filter (EKF). Based on Buck converter state equation, an inductor current predictor was established based on EKF and the predicted inductor current was compensated for the given current to improve the effect of load current variation on the output voltage. …”
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Design of Self-Tuning Regulator for Large-Scale Interconnected Hammerstein Systems by Mourad Elloumi, Samira Kamoun

“…This self-tuning control is developed on the basis of the minimum variance approach and is combined by a recursive algorithm in the estimation step. The parametric estimation step is performed on the basis of the prediction error method and the least-squares techniques. …”
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Novel machine learning driven design strategy for high strength Zn Alloys optimization with multiple constraints by Chenfeng Pan, Wenwen Lin, Jianxing Zhou, Wei Jian, Ka Chun Chan, Yuk Lun Chan, Lu Ren

“…Furthermore, a ML-based Zn alloy composition design system (ZACDS) was proposed by integrating the Bayesian optimization algorithm. A novel high-strength Zn alloy was successfully designed using ZACDS, demonstrating good agreement between predicted and experimental mechanical properties. …”
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A multi‐objective feature optimization strategy for developing high‐entropy alloys with optimal strength and ductility by Yan Zhang, Shewei Xin, Wei Zhou, Xiao Wang, Yangyang Xu, Yanjing Su

“…Results show that the optimized feature subsets reduce prediction errors by 20% for strength and 11% for ductility. …”
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Detecting Botrytis Cinerea Control Efficacy via Deep Learning by Wenlong Yi, Xunsheng Zhang, Shiming Dai, Sergey Kuzmin, Igor Gerasimov, Xiangping Cheng

“…The innovations include (1) combining channel attention mechanism, multi-head self-attention mechanism, and multi-scale feature extractor to improve prediction accuracy and (2) introducing the Shapley value algorithm to achieve a precise quantitative analysis of environmental variables’ contribution to colony growth. …”
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Design of a Deep Learning-Based Metalens Color Router for RGB-NIR Sensing by Hua Mu, Yu Zhang, Zhenyu Liang, Haoqi Gao, Haoli Xu, Bingwen Wang, Yangyang Wang, Xing Yang

“…In this study, we propose a deep learning network capable of forward prediction across a broad wavelength range, combined with a particle swarm optimization algorithm to design metalens efficiently. …”
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Learning atomic forces from uncertainty-calibrated adversarial attacks by Henrique Musseli Cezar, Tilmann Bodenstein, Henrik Andersen Sveinsson, Morten Ledum, Simen Reine, Sigbjørn Løland Bore

“…We propose the Calibrated Adversarial Geometry Optimization (CAGO) algorithm to discover adversarial structures with user-assigned errors. …”
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Cycling Injury Risk in London: Impacts of Road Characteristics and Infrastructure by Thomas Adams, Rachel Aldred

“…It controlled for exposure by using a case-crossover method alongside an algorithm developed by Transport for London to predict cyclist routes. …”
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盘型凸轮轮廓曲线参数化设计系统的开发 by 王林艳, 沈云波, 李少康

“…The profile curve of the disc cam is a sort of non-round complex curve.Its parameterized design system is realized effectively and accurately by the secondary development of AutoCAD.The friendly interface and the outstanding extensibility system of disc cam profile curre parametrization design is developed,and the fuction of parameters input,the parameters check,design calculation and drawing output are realized.According to the design theory of the disc cam,the method for the parameters check is researched and the algorithm of identifying the reasonable step length for the given fitting precision is educed.Finally,the example on the profile curve of disc cam with offset translating roller pushing bar is used to verify the system and the result is shown.…”
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BROWSER-BASED COMPUTER BUSINESS GAME AS AN INTERACTIVE LEARNING ENVIRONMENT FOR MANAGERS by В. П. Дюков

“…The analysis of the game play and the algorithm for developing an effective game strategy has been carried out. …”
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Developing an Integrative Data Intelligence Model for Construction Cost Estimation by Zainab Hasan Ali, Abbas M. Burhan, Murizah Kassim, Zainab Al-Khafaji

“…The comparison results revealed that all AI models showed good prediction performance when applied to datasets affected by more than two parameters. …”
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Risk assessment of water inrush from coal floor based on enhanced samples with class distribution by Shiwei Liu, Jiaxin Zhao, Hao Yu, Jiaqi Chen

“…This method was used to generate virtual samples and enhance the measured database. A prediction model of the water inrush risk for the coal seam floor was established using a coupled algorithm of extreme learning machines, self-adaptive differential evolution, and CDMTD (PCA-CDMTD-SaDE-ELM) and was used to evaluate the water inrush risk in the 19,105 working face of the Yunjialing Mine. …”
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DMRIntTk: Integrating different DMR sets based on density peak clustering. by Wenjin Zhang, Wenlong Jie, Wanxin Cui, Guihua Duan, You Zou, Xiaoqing Peng

“…However, due to the different strategies adopted, different DMR sets will be predicted on the same dataset, which poses a challenge in selecting a reliable and comprehensive DMR set for downstream analysis.…”
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Defining disease heterogeneity to guide the empirical treatment of febrile illness in resource poor settings. by Lisa J White, Paul N Newton, Richard J Maude, Wirichada Pan-ngum, Jessica R Fried, Mayfong Mayxay, Rapeephan R Maude, Nicholas P J Day

“…<h4>Findings</h4>The model predicted a negative correlation between number of appropriate treatments and the level of spatial heterogeneity. …”
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Artificial Neural Network Modeling of Drying Kinetics and Color Changes of Ginkgo Biloba Seeds during Microwave Drying Process by Jun-Wen Bai, Hong-Wei Xiao, Hai-Le Ma, Cun-Shan Zhou

“…Artificial neural network (ANN) modeling was employed to predict the moisture ratio and color parameters (L⁎, a⁎, and b⁎). …”
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G-RCenterNet: Reinforced CenterNet for Robotic Arm Grasp Detection by Jimeng Bai, Guohua Cao

“…Finally, ResNet50 is selected as the backbone network, and a custom loss function is designed specifically for grasp detection tasks, which significantly enhances the model’s ability to predict feasible grasp boxes. The proposed G-RCenterNet algorithm is embedded into a robotic grasping system, where a structured light depth camera captures target images, and the grasp detection network predicts the optimal grasp box. …”
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Programmable friction control in 3D printed patterned multi-materials: a flexible design strategy by Xinle Yao, Yuxiong Guo, Mingyang Wang, Yaozhong Lu, Zhibin Lu, Xin Jia, Yu Gao, Xiaolong Wang

“…Accurate prediction and control of friction are vital for conserving energy, driving demand for intelligent tribological systems with adaptive control. …”
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Exploring the typhoon intensity forecasting through integrating AI weather forecasting with regional numerical weather model by Hongxiong Xu, Yang Zhao, Zhao Dajun, Yihong Duan, Xiangde Xu

“…Abstract Recent advancements in artificial intelligence (AI) have notably enhanced global weather forecasting, yet accurately predicting typhoon intensity remains challenging. This is largely due to constraints inherent in regression algorithm properties including deep neural networks and inability of coarse resolution to capture the finer-scale weather processes. …”
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