Hyperspectral Estimation of Tea Leaf Chlorophyll Content Based on Stacking Models by Jinfeng Guo, Dong Cui, Jinxing Guo, Umut Hasan, Fengqi Lv, Zixing Li

“…In this study, derivative transformations were first applied to preprocess the tea hyperspectral data, followed by the use of the Stable Competitive Adaptive Reweighted Sampling (SCARS) algorithm for feature variable selection. Finally, multiple individual machine learning models and stacking models were constructed to estimate tea LCC based on hyperspectral data, with a particular emphasis on analyzing how the selection of base models and meta-models affects the predictive performance of the stacking models. …”
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Machine learning developed immune-related exosome signature for prognosis and immunotherapy benefit in bladder cancer by Xiaoting Luo, Yi Luo

“…To investigate the performance of IES in predicting the immunotherapy benefit, three immunotherapy datasets (GSE91061, GSE78220 and IMvigor210) and several predicting scores were used. …”
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Enhancing Laser-Induced Breakdown Spectroscopy Quantification Through Minimum Redundancy and Maximum Relevance-Based Feature Selection by Manping Wang, Yang Lu, Man Liu, Fuhui Cui, Rongke Gao, Feifei Wang, Xiaozhe Chen, Liandong Yu

“…This study validates the effectiveness of the mRMR algorithm for LIBS feature extraction and highlights the potential of feature selection techniques to enhance predictive accuracy. …”
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Dynamic Characteristics of a Cylindrical Roller Bearing with Cage Cracks by Yang Yang, Xiaoye Qi, Yongjie Wang, Meiling Wang, Baogang Wen, Jingyu Zhai

“…The derived dynamic differential equations of cylindrical roller bearings were solved by means of the modified Newton–Raphson iterative algorithm and the BDF predictive correction algorithm with automatic variable order and step length. …”
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A Computationally Efficient Learning-Based Control of a Three-Phase AC/DC Converter for DC Microgrids by Ran Li, Wendong Feng, Tianhao Qie, Yulin Liu, Tyrone Fernando, Herbert HoChing Iu, Xinan Zhang

“…This paper presents a novel learning-based control algorithm for three-phase AC/DC converters, which are key components in DC microgrids, for reliable power conversion. …”
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Artificial Neural Network Approach to Study Imprecisely Defined Nonlinear Systems With Case Studies by Lakshmi Durga Pathipati, Sukanta Nayak

“…A feed-forward neural network (FFNN) is used to generate outputs based on initial guesses for the field variables, and the ANN-LM algorithm optimizes the solution by minimizing the error between predicted and target values. …”
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Cooperative UAV Scheduling for Power Grid Deicing Using Fuzzy Learning and Evolutionary Optimization by Yu-Jun Zheng, Zhi-Yuan Zhang, Jia-Yu Yan, Wei-Guo Sheng

“…The algorithm is fully parallelizable and therefore can solve the problem very efficiently based on GPU parallel acceleration. …”
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An analysis of the relationship of triglyceride glucose index with diffuse large B-cell lymphoma prognosis: a retrospective study by QingQing Luo, Zhixiang Lei, Haizhou Miao, Ting Huang, Li Yu

“…Calibration curves showed good agreement between the nomogram predictions and actual outcomes, and DCA highlighted the high clinical utility of the model.ConclusionThe TyG index is an independent prognostic factor in DLBCL patients, and the TyG-based nomogram model provides enhanced predictive accuracy compared to the IPI. …”
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Gestational diabetes mellitus and obesity: effects on offspring by O. V. Rozhkova, O. V. Remneva, N. I. Fadeeva, Yu. V. Korenovskiy, S. D. Yavorskaya

“…CHAID method (Chi Squared Automatic Interaction Detection) was used to create an algorithm for predicting adverse perinatal outcomes in GDМ. …”
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A simulated annealing with graph-based search for the social-distancing problem in enclosed areas during pandemics. by Bayram Dundar

“…A greedy random-based algorithm is presented to determine efficiently an initial feasible solution. …”
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Applicability of machine learning technique in the screening of patients with mild traumatic brain injury. by Miriam Leiko Terabe, Miyoko Massago, Pedro Henrique Iora, Thiago Augusto Hernandes Rocha, João Vitor Perez de Souza, Lily Huo, Mamoru Massago, Dalton Makoto Senda, Elisabete Mitiko Kobayashi, João Ricardo Vissoci, Catherine Ann Staton, Luciano de Andrade

“…Among the tested models, he linear extreme gradient boosting was the best algorithm, with the highest sensitivity (0.70 ± 0.06). …”
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Arctic Heatwaves Could Significantly Influence the Isoprene Emissions From Shrubs by Hui Wang, Allison Welch, Sanjeevi Nagalingam, Christopher Leong, Pitchayawee Kittitananuvong, Kelley C. Barsanti, Rebecca J. Sheesley, Claudia I. Czimczik, Alex B. Guenther

“…With a modified algorithm from this study, MEGAN predicts 66% higher isoprene emissions for Arctic willows during an Arctic heatwave. …”
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Investigation of Vessel Manoeuvring Abilities in Shallow Depths by Applying Neural Networks by Lúcia Moreira, C. Guedes Soares

“…The outcomes achieved with the proposed system have shown excellent accuracy and ability in predicting ship manoeuvring with varying depths of shallow water.…”
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Systematic, computational discovery of multicomponent and one-pot reactions by Rafał Roszak, Louis Gadina, Agnieszka Wołos, Ahmad Makkawi, Barbara Mikulak-Klucznik, Yasemin Bilgi, Karol Molga, Patrycja Gołębiowska, Oskar Popik, Tomasz Klucznik, Sara Szymkuć, Martyna Moskal, Sebastian Baś, Rafał Frydrych, Jacek Mlynarski, Olena Vakuliuk, Daniel T. Gryko, Bartosz A. Grzybowski

“…Moreover, when supplemented by models to approximate kinetic rates, the algorithm can predict reaction yields and identify reactions that have potential for organocatalysis. …”
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Using Machine Learning to Shorten and Adapt Fall Risk Assessments for Older Adults by Lilyana Khatib, Adi Toledano-Shubi, Hilla Sarig Bahat, Hagit Hel-Or

“…The adaptive approach reduces task sequences by over 50% while maintaining high predictive accuracy. It also enables remote testing, predicting performance on complex tasks using as few as 2–3 simpler, accessible tasks. …”
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Adaptively Receding Galerkin Optimal Control for a Nonlinear Boiler-Turbine Unit by Gang Zhao, Zhi-gang Su, Jun Zhan, Hongxia Zhu, Ming Zhao

“…With the help of a mathematical predictive model, optimal control law is then obtained based on a Galerkin optimization algorithm. …”
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Neural network training to support decision making ON FOREX MARKET by V. A. Rybak, H. M. Sulaiman

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Exploration for the physical origin and impact of chemical short-range order in high-entropy alloys: Machine learning-assisted study by Panhua Shi, Zhen Xie, Jiaxuan Si, Jianqiao Yu, Xiaoyong Wu, Yaojun Li, Qiu Xu, Yuexia Wang

“…In this study, we introduced a set of interpretable ML workflows and determined the best algorithm (kernel ridge regression (KRR)) for predicting the atomic stress in HEAs, which can deepen the understanding of the formation mechanism of CSRO. …”
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Identification method of roof rock interface based on response characteristics of drilling parameters by LI Dianshang, LIU Cancan, WANG Chuanbing, REN Bo, REN Shuai, KANG Zhipeng

“…On-site tests yielded 0.04m of average error in predicting the position of the coal rock interface. …”
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Measurement Error Estimation Method of Field Service Electricity Energy Meters under the Condition of Big Data by DAI Yan-jie, DONG Xian-guang, LIU Ya-qi, LIANG Ya-jie, LIU Xiao, QI Jia, SUN Yong-quan

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