Leveraging Machine Learning Regression Algorithms to Predict Mechanical Properties of Evaporitic Rocks From Their Physical Attributes by Ayham Zaitouny, Hasan Arman, Anusuya Krishnan, Alaa Ahmed, Ahmed Gad

“…In this study, machine learning (ML) regression algorithms were applied to predict four key mechanical parameters, namely, uniaxial compressive strength (UCS), point load index (PLI), indirect tensile strength (ITS), and Schmidt hardness value (SHV), based on the physical attributes of evaporitic rocks. …”
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The construction of HMME-PDT efficacy prediction model for port-wine stain based on machine learning algorithms by Hongxia Yan, Yixin Tan, Fan Qiao, Zhuotong Zeng, Yaqian Shi, Xueqin Zhang, Lu Li, Ting Zeng, Yi Zhan, Ruixuan You, Xinglan He, Rong Xiao, Xiangning Qiu

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Model-Free Predictive Control Based on RLS Algorithm for Grid-Forming Inverters With Virtual Synchronous Generator by Min Huang, Huiying Zhang, Kangan Wang, Zhilei Yao, Weimin Wu

“…Building on this, the improvement schemes of algorithmic parameter initialization, delay compensation and current limiting capability are further investigated. …”
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Rainfall Prediction in Khorasan Razavi Stations Using a Hybrid Neural Network and Genetic Algorithm Approach by Mahdi Naseri, Mahsa Mardani

Subjects: “…genetic algorithm…”
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Predicting Metabolite-Disease Associations Based on Linear Neighborhood Similarity with Improved Bipartite Network Projection Algorithm by Xiujuan Lei, Cheng Zhang

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Utilizing an Innovative Gaussian Process Regression Machine Learning Algorithm for Estimating Unconfined Compressive Strength Predictions by Hazel Abraham

“…This article offers an advanced argument in using a Machine Learning algorithm known as Gaussian Process Regression to predict the UCS for mixtures of soils. …”
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Prediction of COVID-19 Effect on Patients during Six Month After Recovery, by Using AI Algorithm by hanan aldabagh, Ghaydaa Al-Talib

“…The GSO algorithm was used for feature selection, and for hyper-parameter tuning for the Random Forest (RF) algorithm used in the prediction process in order to make predictions to identify the effects that may accrue on recoveries persons. …”
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Prediction of Mechanical Properties of Cotton Fibers by a BP Neural Network Model Optimized by Genetic Algorithm by Junyang Wang, Limin Zhang, Xiang Liu, Jinchan Zhang, Wanxin Wang, Hong Xu

“…In this experiment, a general purpose BP neural network (BP) based on genetic algorithm (GA) was developed for predicting fiber properties. …”
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Construction and validation of a predictive model for meningoencephalitis in pediatric scrub typhus based on machine learning algorithms by Yonghan Luo, Wenrui Ding, Xiaotao Yang, Houxi Bai, Feng Jiao, Yan Guo, Ting Zhang, Xiu Zou, Yanchun Wang

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Algorithm for link prediction in self-regulating network with adaptive topology based on graph theory and machine learning by Evgeny Y. Pavlenko

“…On the basis of the developed model of network functioning with adaptive topology, a graph algorithm for link prediction is proposed, which is extended to the case of peer-to-peer networks. …”
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Improved Quantum Artificial Bee Colony Algorithm-Optimized Artificial Intelligence Models for Suspended Sediment Load Predicting by Peng Wei, Wang Yu

“…To evaluate the predictive capability, the models are compared with quantum bee colony algorithm-optimized AI models (QABC-SVR and QABC-ANN), genetic algorithm-optimized AI models (GA-SVR and GA-ANN) and traditional AI models (SVR and ANN). …”
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A Cluster Head Selection Algorithm for Extending Last Node Lifetime in Wireless Sensor Networks by Marcin Lewandowski, Bartłomiej Płaczek

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Machine learning-based coalbed methane well production prediction and fracturing parameter optimization by HU Qiujia, LIU Chunchun, ZHANG Jianguo, CUI Xinrui, WANG Qian, WANG Qi, LI Jun, HE Shan

Subjects: “…|coalbed methane|random forest algorithm|multi-task learning|particle swarm optimization algorithm|production prediction|fracturing parameter optimization…”
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Efficient Fault Diagnosis of Elevator Cabin Door Drives Using Machine Learning with Data Reduction for Reliable Transmission by Jakub Gęca, Dariusz Czerwiński, Bartosz Drzymała, Krzysztof Kolano

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Q-learning based handoff algorithm for satellite system with ancillary terrestrial component by Dan-ni XIONG, Yi LI

“…,mobile satellite system with ancillary terres-trial component (MSS-ATC),the long transmission delay of satellite link was a huge challenge which may lead to high handoff dropping probability.In order to address this problem,a novel handoff decision strategy was proposed based on the predictive RSS and Q-learning algorithm.Extensive simulation results demonstrate that the proposed scheme can de-crease the handoff dropping probability,reduce the unnecessary handoff times and maximize the network reward.In ad-dition,the proposed scheme can also adapt to the situation of high-speed movement very well.…”
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Diversity is key: fantasy football dream teams under budget constraints by Josef Gullholm, Jil Klünder, Julie Rowlett, Jonathan Stålberg

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Optimizing Assembly Error Reduction in Wind Turbine Gearboxes Using Parallel Assembly Sequence Planning and Hybrid Particle Swarm-Bacteria Foraging Optimization Algorithm by Sydney Mutale, Yong Wang, De Tian

“…Specifically, the PSBFO algorithm reduced errors from an initial value of 50 to a final value of 5 across 20 iterations, with components such as the low-speed shaft and planetary gear system showing the most substantial reductions. …”
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Identifying the Latitude and Longitude of ATMs in ATM Networks by Niloofar Haghjoo, Mohammad rahmati, Ali Zare Mirakabad

Subjects: “…atm location prediction algorithm…”
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Mitigating Algorithmic Bias in AI-Driven Cardiovascular Imaging for Fairer Diagnostics by Md Abu Sufian, Lujain Alsadder, Wahiba Hamzi, Sadia Zaman, A. S. M. Sharifuzzaman Sagar, Boumediene Hamzi

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Predicting Insomnia Response to Acupuncture With the Development of Innovative Machine Learning by Qingyun Wan, Kai Liu, Yuyang Bo, Xiya Yuan, Mufeng Li, Xiaoqiu Wang, Chuang Chen, Lanying Liu, Wenzhong Wu

“…To address this, an innovative machine learning algorithm, Relief-NDPGWO-WSVM, is developed to predict insomnia response to acupuncture. …”
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