Device-Driven Service Allocation in Mobile Edge Computing with Location Prediction by Qian Zeng, Xiaobo Li, Yixuan Chen, Minghao Yang, Xingbang Liu, Yuetian Liu, Shiwei Xiu

“…To validate the effectiveness of the proposed methods, we conduct multiple controlled experiments focusing on both location prediction models and service allocation algorithms. …”
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Prediction of Transformer Residual Flux Based on J-A Hysteresis Theory by Qi Long, Xu Yang, Keru Jiang, Changhong Zhang, Mingchun Hou, Yu Xin, Dehua Xiong, Xiongying Duan

“…Then, based on the J-A model, residual flux prediction of the transformer is carried out, and a transformer no-load energization experimental platform is built. …”
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Prediction of Work-relatedness of Shoulder Musculoskeletal Disorders as by Using Machine Learning by Saemi Jung, Bogeum Kim, Yoon-Ji Kim, Eun-Soo Lee, Dongmug Kang, Youngki Kim

“…Background: This study aimed to develop prediction models for the work-relatedness of shoulder diseases through machine learning algorithms. …”
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Risk prediction and effect evaluation of complicated appendicitis based on XGBoost modeling by Sunmeng Chen, Jianfu Xia, Beibei Xu, Yi Huang, Miaomiao Teng, Juyi Pan

“…An integrated learning algorithm, Extreme Gradient Boosting (XGBoost), was introduced to predict the risk of CAP and compared with Support Vector Machine (SVM), Random Forest (RF), and Decision Tree (CART) algorithms. …”
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Application of Artificial Intelligent Approach to Predict the Normal Boiling Point of Refrigerants by Bo Liu, Maryam Karimi Nouroddin

“…To this end, a total of 334 data points of Tb are gathered to prepare and test ELM and EDT boosted algorithms. The visual and mathematical comparisons of model outputs and real Tb express that proposed models have great potential to predict Tb of refrigerant. …”
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A Local–Global Graph KAN for Multi‐Class Prediction of PPI by Minghui Liu, Ying Qu

“…Therefore, using machine learning to treat multiple PPI predictions as binary classifications has become an alternative, but there is a problem of data imbalance. …”
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Machine Learning Techniques to Model and Predict Airflow Requirements in Underground Mining by Maria Karagianni, Andreas Benardos

“…With this twin model, several scenarios are developed and evaluated and more importantly data are gathered, allowing for the training of the ML algorithms used to assess and predict the required ventilation airflow, taking into account air quality data, the number of workers, and machine fleet.…”
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Accurate and robust prediction of genetic relationship from whole-genome sequences. by Hong Li, Gustavo Glusman, Chad Huff, Juan Caballero, Jared C Roach

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Enhanced Neutrosophic Set and Machine Learning Approach for Breast Cancer Prediction by Ashika T, Hannah Grace, Nivetha Martin, Florentin Smarandache

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Predicting Protein Complexes in Weighted Dynamic PPI Networks Based on ICSC by Jie Zhao, Xiujuan Lei, Fang-Xiang Wu

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Unsupervised Clustering Successfully Predicts Prognosis in NSCLC Brain Metastasis Cohorts by Emre Uysal, Gorkem Durak, Ayse Kotek Sedef, Ulas Bagci, Tanju Berber, Necla Gurdal, Berna Akkus Yildirim

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Integrating Bioengineering and Machine Learning: A Multi-Algorithm Approach to Enhance Agricultural Sustainability and Resource Efficiency by Senthil G.A., Prabha R., Asha R.M., Suganthi S.U., Sridevi S.

“…Findings have indicated that the multi-algorithm approach not only promotes increased predictive capabilities and resource optimization but also raises food safety with the increased threats in agriculture.…”
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Prediction of ball-on-plate friction and wear by ANN with data-driven optimization by Alexander Kovalev, Yu Tian, Yonggang Meng

“…After the training procedure, the ANN is capable to predict the contact and hydrodynamic pressure by adapting the output data according to the tribological condition implemented in the optimization algorithm.…”
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Rail Transit Prediction Based on Multi-View Graph Attention Networks by Li Wang, Xin Wang, Jiao Wang

“…With the historical dataset of Beijing rail transit, the experiment proves that the prediction accuracy of the model is generally better than the baseline traffic prediction algorithms.…”
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Comparing Different Machine Learning Techniques in Predicting Diabetes on Early Stage by Shweta Yadu, Rashmi Chandra, Vivek Kumar Sinha

“…The possibility of this disease has been predicted using a variety of methods. To forecast diabetes at an early stage, adequate and clear data on diabetic individuals are needed. …”
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A Symbol Conditional Entropy-Based Method for Incipient Cavitation Prediction in Hydraulic Turbines by Mengge Lv, Feng Li, Yi Wang, Tianzhen Wang, Demba Diallo, Xiaohang Wang

“…The comparison results with different prediction algorithms show that the proposed SCE has excellent trend prediction performance and high precision.…”
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Impact of measurement error on predicting population-based inpatient glucose control by George E Saulnier, Janna C Castro, Curtiss B Cook

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Optimized Ensemble Model to Predict the Compatibility of Automobiles With Hybrid Electric Vehicles by Rohit Bajaj, Deepika Sharma, Ruchika Gupta, Shonak Bansal, Payal Patial, Krishna Prakash

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In silico metabolism and toxicity prediction using a knowledge-based approach by Emilio Mateev, Maya Georgieva, Alexandrina Mateeva, Alexander Zlatkov

“…In this study, knowledge-based algorithms were utilized to predict the metabolism and toxicity of a previously identified dual-acting pyrrole-based compound using in silico methods. …”
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EmRep: Energy management relying on state‐of‐charge extrema prediction by Lars Hanschke, Christian Renner

“…Considering multiple user‐defined utility profiles, the benefits of EmRep in combination with a variety of prediction algorithms, time resolutions, and energy storage sizes are showcased. …”
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