Optimal Thermal Output of an Absorption Heat Pump with Steam Heating Integrated in a PT-60/70-130/13 Steam Turbine by Oleksandr L. Shubenko, Viktoriia O. Tarasova, Mykola Yu. Babak, Oleksii Yu. Boiarshynov

“…AHP was heated by steam from the production selection of the turbine after the steam screw machine installed for energy saving. The general optimization problem with the objective function of total changing the monthly fuel consumption after the integration of AHP, based on the average monthly outdoor air temperature in the heating season in Ukraine, was divided into 6 auxiliary optimization problems. …”

Constitutive model of metal rubber material considering plastic accumulation behavior by FENG Zhipeng, YANG Fang, FU Hailong, AI Shigang, WANG Yue, YUAN Liangyang

“…;In terms of theoretical modeling, this research innovatively integrates micro-unit spring theory with the Ludwik plasticity model to establish a constitutive model capable of precisely characterizing the nonlinear mechanical behavior of metal rubber. …”
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Research on early warning model of coal spontaneous combustion based on interpretability by Huimin Zhao, Xu Zhou, Jingjing Han, Yixuan Liu, Zhe Liu, Shishuo Wang

“…Compared with the traditional machine learning model, the model has better prediction accuracy and generalization ability. …”
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Establishment of Hyperspectral Prediction Model of Water Content in Anshan-Type Magnetite by Xiaoxiao XIE, Yang BAI, Jiuling ZHANG, Yuna JIA

“…In order to further improve the prediction ability of the model, the competitive adaptive reweighting method (CARS) was used to optimize the characteristic band, and a prediction model was established by combining random forest regression (RFR), least squares support vector regression (LSSVR) and particle swarm optimization least squares support vector regression (PSO-LSSVR). …”
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Non-invasive liver fibrosis screening on CT images using radiomics by Jay J. Yoo, Khashayar Namdar, Sean Carey, Sandra E. Fischer, Chris McIntosh, Farzad Khalvati, Patrik Rogalla

“…A development cohort, which was split further into training and validation cohorts across 100 trials, was used to determine the optimal combinations of contrast, normalization, machine learning model, and radiomic features for liver fibrosis detection based on their Area Under the Receiver Operating Characteristic curve (AUC) on the validation cohort. …”
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Humatch - fast, gene-specific joint humanisation of antibody heavy and light chains by Lewis Chinery, Jeliazko R. Jeliazkov, Charlotte M. Deane

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Artificial intelligence-optimized shield parameters for soft ground tunneling in urban environment: A case study of Bangkok MRT Blue Line by Sahatsawat Wainiphithapong, Chana Phutthananon, Sompote Youwai, Pitthaya Jamsawang, Phattarawan Malaisree, Ochok Duangsano, Pornkasem Jongpradist

“…This paper presents a study on multi-objective optimization (MOO) of shield operational parameters (SOPs) for soft ground tunneling using a tunnel boring machine (TBM) in an urban environment, focusing on the case study of the MRT Blue Line in Bangkok. …”
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An Experimental Comparison of Self-Adaptive Differential Evolution Algorithms to Induce Oblique Decision Trees by Rafael Rivera-López, Efrén Mezura-Montes, Juana Canul-Reich, Marco-Antonio Cruz-Chávez

“…Although traditional decision tree induction methods create explainable models, they often fail to achieve optimal classification accuracy. …”
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On the relationship of Poisson’s ratio with geophysical characteristics of rocks by D. V. Shustov, Yu. A. Kashnikov, A. E. Kukhtinskii, A. A. Efimov

“…The obtained results can be used for more precise modeling and forecasting of oil field development processes, contributing to increased efficiency in hydrocarbon extraction and optimization of production processes in the oil industry.…”
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Evaluating the Diagnostic Potential of Biomarker Panels in Breast Cancer and Prostate Adenocarcinoma by Kldiashvili Ekaterina, Iordanishvili Saba, Adamia Sophia, Abiatari Ivane, Zarnadze Maia

“…Statistical analyses, including the Mann–Whitney U test and machine learning models (random forest), were employed to assess the predictive accuracy of these biomarkers in distinguishing between cancerous and healthy states. …”
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Indonesian Government Revenue Prediction Using Long Short-Term Memory by Mahmud, Windu Gata, Hafifah Bella Novitasari, Sigit Kurniawan, Dedi Dwi Saputra

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A Hybrid GRA-TOPSIS-RFR Optimization Approach for Minimizing Burrs in Micro-Milling of Ti-6Al-4V Alloys by Rongkai Tan, Abhilash Puthanveettil Madathil, Qi Liu, Jian Cheng, Fengtao Lin

“…Moreover, the GRA-TOPSIS-RFR method significantly outperforms existing optimization and prediction models, with the integration of the RFR model enhancing prediction accuracy by 42.6% compared to traditional linear regression approaches. …”
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FOCUS-HTS: a new stellarator coil design code for three-dimensional high-temperature superconducting magnets by Xianyi Nie, Jianlin Peng, Yidong Xie, Guodong Yu, Ke Liu, Caoxiang Zhu

“…To address these challenges, we developed a new code, FOCUS-HTS, built on its predecessor, FOCUS. FOCUS-HTS can model coils as either filaments or finite-build shapes using the Fourier representation or cubic B-splines. …”
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Development and Validation of a Radiomics Nomogram Based on Magnetic Resonance Imaging and Clinicoradiological Factors to Predict HCC TACE Refractoriness by Dong Y, Hu J, Meng X, Yang B, Peng C, Zhao W

“…The optimal model was presented as a nomogram and verified through calibration and decision curve analyses.Results: In evaluating radiomics models for predicting TACE refractoriness in HCC, the LR-developed portal venous phase (VP) model achieved optimal single-sequence performance (training AUC: 0.896, 95% CI: 0.843– 0.941; validation: 0.853, 0.727– 0.965). …”
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Quantum-Classical Autoencoder Architectures for End-to-End Radio Communication by Zsolt I. Tabi, Bence Bako, Daniel T. R. Nagy, Peter Vaderna, Zsofia Kallus, Peter Haga, Zoltan Zimboras

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Preoperative DBT-based radiomics for predicting axillary lymph node metastasis in breast cancer: a multi-center study by Shuyan He, Biao Deng, Jiaqi Chen, Jiamin Li, Xuefeng Wang, Guanxing Li, Siyu Long, Jian Wan, Yan Zhang

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Artificial intelligence-based multi-expression programming prediction of magnetized radiative nanofluid flow between coaxial deformable tubes by Bilal Ahmed, Dong Liu, Bouthaina Dammak, Naeem Ullah, Afraz Hussain Majeed, Hafedh Mahmoud Zayani, Binjuan Zhao

“…In this research novel artificial intelligence based multi expression programming approach is employed to develop a predictive model for optimizing the thermal characteristics of the fluid using numerical simulation data. …”
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Evaluating the Effectiveness of Traffic Metering Strategies in Reducing Congestion: A Case Study of Amman by Qeethara Al-Shayea, Huthaifa Aljawazneh

“…To address this challenge, we have implemented a simulation model powered by machine learning techniques to effectively and accurately manage traffic flow on Amman's streets. …”
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Machine learning technique-based four-autoantibody test for early detection of esophageal squamous cell carcinoma: a multicenter, retrospective study with a nested case–control stu... by Yi-Wei Xu, Yu-Hui Peng, Can-Tong Liu, Hao Chen, Ling-Yu Chu, Hai-Lu Chen, Zhi-Yong Wu, Wen-Qiang Wei, Li-Yan Xu, Fang-Cai Wu, En-Min Li

“…In present study, we aimed to identify a novel optimized autoantibody panel with high diagnostic accuracy for clinical and preclinical esophageal squamous cell carcinoma (ESCC) using machine learning (ML) algorithms. …”
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LatentDE: latent-based directed evolution for protein sequence design by Thanh V T Tran, Nhat Khang Ngo, Viet Thanh Duy Nguyen, Truong-Son Hy

“…To mitigate this extensive procedure, recent advancements in machine learning-guided methodologies center around the establishment of a surrogate sequence-function model. …”
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