Dissolved Oxygen Prediction Based on SOA-SVM and SOA-BP Models by ZHANG Xuekun

“…To improve the accuracy of dissolved oxygen prediction,this paper researches and proposes a prediction method that combines seagull optimization algorithm (SOA) with support vector machine (SVM) and BP neural network,prepares four prediction schemes based on the monthly dissolved oxygen monitoring data of the Jinghong Power Station in Xishuangbanna,a national important water supply source in Yunnan Province,from January 2009 to September 2020,optimizes the key parameters of SVM and weight threshold of BP neural network by SOA to construct SOA-SVM and SOA-BP models,predicts the dissolved oxygen of Jinghong Power Station based on the models,and compares the prediction results with those of SVM and BP models.The results show that:The absolute values of the average relative errors of the SOA-SVM and SOA-BP models for the 4 schemes of dissolved oxygen prediction are between 4.07%~4.98% and 3.85%~4.83%,and that of the average absolute errors are 0.309~0.374 mg/L and 0.294~0.371 mg/L,respectively.With better prediction accuracy than SVM and BP models,they have good prediction accuracy and generalization ability.SOA can effectively optimize the key parameters of SVM and weight threshold of BP neural network.SOA-SVM and SOA-BP models are feasible for dissolved oxygen prediction,which can provide references for related prediction research.…”
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Using machine learning models to predict post-revascularization thrombosis in PAD by Samir Ghandour, Adriana A. Rodriguez Alvarez, Isabella F. Cieri, Shiv Patel, Mounika Boya, Rahul Chaudhary, Rahul Chaudhary, Rahul Chaudhary, Anna Poucey, Anahita Dua

“…The Synthetic Minority Oversampling Technique (SMOTE) was employed to address the class imbalance between the primary outcomes (ATE vs. no ATE). Model performance was assessed by area under the curve (AUC), accuracy, sensitivity, specificity, negative predictive value, and positive predictive value.ResultsOf the 308 patients analyzed, 66% were male, 84% were White, and 18.3% experienced an ATE during the one-year post-revascularization follow-up period. …”
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Analysis of the Influence of Different Turbulence Models on the Prediction of Vehicle Aerodynamic Performance by Luwei Wang, Xingjun Hu, Peng Guo, Zirui Wang, Jingyu Wang, Yuqi Wang, Yan Ma, Ying Li, Jing Zhao, Xu Yang, Ruixing Ma, Yinan Zhu, Jianjiao Deng

“…The k-ε model best predicts the steady-state drag coefficient (Cd) (error 0.0009). …”
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Identification of Risk Factors and Predictive Indicators for Tigecycline‐Associated Hypofibrinogenemia by Xiaohui Liu, Xuefeng Yuan, Long Wen, Xin Tan, Qian Sui, Jiheng Liu

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Methods and Algorithms for Predictive Analytics of Time Series in Energy Consumption by Aleksandr Karmanov

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Integrated Optimization of Production Scheduling and Explicit Model Predictive Control for Batch Process Based on SEN Framework by Yue WANG, Xiaohui GUO, Yuting JIN, Xin JIN

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Psychological distress in biliary tract malignancy patients: influencing factors and development of a predictive nomogram model by Zhennan Gou, Yuhua Liu, Wenjie Tang, Changming Zhou, Zhenqi Lu, Lu Wang, Wei Feng, Weiqi Xu, Jun Wang

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Development and validation of a risk assessment model for predicting the failure of early medical abortions: A clinical prediction model study based on a systematic review and meta-analysis. by An-Hao Liu, Bin Xu, Xiu-Wen Li, Yue-Wen Yu, Hui-Xin Guan, Xiao-Lu Sun, Yan-Zhen Lin, Li-Li Zhang, Xian-Di Zhuo, Jia Li, Wen-Qun Chen, Wen-Feng Hu, Ming-Zhu Ye, Xiu-Min Huang, Xun Chen

“…<h4>Objective</h4>As the first model in predicting the failure of early medical abortion (EMA) was inefficient, this study aims to develop and validate a risk assessment model for predicting the failure of EMAs more accurately in a clinical setting.…”
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Impacts of Predicted Liquid Fraction and Multiple Ice‐Phase Categories on the Simulation of Hail in the Predicted Particle Properties (P3) Microphysics Scheme by Jason A. Milbrandt, Hugh Morrison, Mélissa Cholette

“…In this study, the impacts of some new capabilities of P3 on the simulation of hail amounts and sizes are examined in the context of idealized, high‐resolution (200‐m isotropic grid spacing) hailstorm simulations using a cloud‐resolving model. Sensitivity tests are conducted to examine the impacts of (a) the predicted liquid fraction, and (b) the number of generic ice‐phase categories (varied between one and four). …”
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A Fast SOC Balancing Method for MMC-BESS Based on Nonlinear Model-Predictive Control by Xiaofan Ji, Fengxiang Xie, Yuantang Qi, Yongdong Ji, Decun Niu, Qizhong Yan

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Comparison of SES method and SARIMA model in predicting the number of admissions in the department of neurology by Wanjun Yang, Liping Ding, Aonan Su

Subjects: “…SES model…”
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Establishment and validation of risk prediction model to predict intravenous immunoglobulin-resistance in Kawasaki disease based on meta-analysis of 15 cohorts by Shuhui Wang, Na Sun, PanPan Liu, Weiguo Qian, Qiuqin Xu, DaoPing Yang, Mingyang Zhang, Miao Hou, Ye Chen, Guanghui Qian, Chunmei Gao, Ling Sun, Haitao Lv

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Predicting purulent meningitis in very preterm infants: a novel clinical model by Xiaowei Sun, Rui Jing, Yang Li

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Evaluation of Statistical Models of NDVI and Agronomic Variables in a Protected Agriculture System by Edgar Vladimir Gutiérrez-Castorena, Joseph Alejandro Silva-Núñez, Francia Deyanira Gaytán-Martínez, Vicente Vidal Encinia-Uribe, Gustavo Andrés Ramírez-Gómez, Emilio Olivares-Sáenz

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Study on prediction model and influencing factors of progression-free survival in colorectal cancer by CHEN Jiaying, CHU Yimin, PENG Haixia

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Precision prognostic model for uveal melanoma: nomogram prediction and comparison with AJCC system by Wentao Wu, Jingjing Zhu, Yuzhu Wu, Daning Li, Rong Liu, Yuchen Zheng, Qiuqiong Deng, Yiqiang Yuan

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BUILDING PREDICTIVE MODELS TO ASSESS DEGRADATION OF SOIL ORGANIC MATTER OVER TIME USING REMOTE SENSING DATA by Abdulsalam Aljumaily, Ammar Kashmolaa

Subjects: “…predictive models,,…”
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Spatial Variables and Land Use Change Models: A Study on Conditioning Patterns of Natural Vegetation Suppression and Persistence by Macleidi Varnier, Eliseu José Weber

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Enhanced Helicopter Vibration Prediction With Hybrid Sampling and Cost Mining Techniques by Jeonghun Kim, Keunho Choi, Donghee Yoo

“…To address these challenges, this study develops a machine learning-based prediction model using vibration test data from the cockpit of a Korean utility helicopter. …”
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Predicting individual hemoglobin abnormalities using longitudinal data in clinical practice by Maliheh Namazkhan, Karel Jan van Tuijn, Maurits Kaptein, Remco van Horssen

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