Cognitive Abilities Predict Safety Performance: A Study Examining High-Speed Railway Dispatchers by Shi Lei, Zizheng Guo, Xi Tan, Xi Chen, Chengen Li, Jiaming Zou, Shi Cao, Guo Feng

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The 2023 Mw 7.8–7.7 Kahramanmaraş earthquakes were loosely slip-predictable by Ellis Vavra, Yuri Fialko, Fatih Bulut, Aslı Garagon, Sefa Yalvaç, Cenk Yaltırak

“…We find that the coseismic slip equaled to or exceeded the accumulated slip deficit, suggesting that the slip-predictable recurrence model applies as a lower bound on strain release during the Kahramanmaraş earthquakes.…”
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Predictable Behavior of GFRP-Reinforced Bridge Decks: Formulation of a Strain-Based Capacity Model by Young Hoon Kim, Yeesock Kim, Yeonho Park

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Broad Learning-Based Optimization and Prediction of Questionnaire Survey: Application to Mind Status of College Students by Lin Yu, Shejiao Ding

“…Only with the accurate prediction, the corresponding actions can be conducted to prevent the situation from going worse. …”
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Hydrologic response and prediction of future water level changes in Qinghai Lake of Tibet Plateau, China by Haibin Wang, Jiahong Liu, Zhuoran Luo, Sana Nazli, Lu Shi

“…The future water level trends of Qinghai Lake are predicted in this study using multiple regression model, allowing for the estimation of its future inundation area. …”
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Machine learning model and nomogram to predict the risk of heart failure hospitalization in peritoneal dialysis patients by Liping Xu, Fang Cao, Lian Wang, Weihua Liu, Meizhu Gao, Li Zhang, Fuyuan Hong, Miao Lin

“…The RF model (AUC = 0.853) was the best performing model for predicting HF, and the XGBoost model (AUC = 0.871) was the best model for predicting mortality. …”
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Intracranial aneurysm instability prediction model based on 4D-Flow MRI and HR-MRI by Fei Peng, Jiaxiang Xia, Fandong Zhang, Shiyu Lu, Hao Wang, Jiashu Li, Xinmin Liu, Yao Zhong, Jiahuan Guo, Yonghong Duan, Binbin Sui, Chuyang Ye, Yi Ju, Shuai Kang, Yizhou Yu, Xin Feng, Xingquan Zhao, Rui Li, Aihua Liu

“…The Hybrid model provided a promising prediction of aneurysm instability.…”
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A Machine Learning-Based Platform for Monitoring and Prediction of Hazardous Gases in Rural and Remote Areas by Edgar F. Ladeira, Bruno M. C. Silva

“…Without means to monitor or predict, healthcare and government stakeholders typically act too late when indoor incidents occur. …”
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Optimized Prediction of Weapon Effectiveness in BVR Air Combat Scenarios Using Enhanced Regression Models by Andre R. Kuroswiski, Annie S. Wu, Angelo Passaro

“…This study investigates high-performance models for predicting the Weapon Engagement Zone (WEZ) in beyond-visual-range (BVR) air combat scenarios. …”
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Application of Extreme Gradient Boosting Based on Grey Relation Analysis for Prediction of Compressive Strength of Concrete by Liyun Cui, Peiyuan Chen, Liang Wang, Jin Li, Hao Ling

“…This study presents a novel predictive system as follows: extreme gradient boosting (XGBoost) based on grey relation analysis (GRA) for predicting the compressive strength of concrete containing slag and metakaolin. …”
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Machine learning-based anomaly detection and prediction in commercial aircraft using autonomous surveillance data by Tian Xia, Lanju Zhou, Khalil Ahmad

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A Study on the Differences in Optimized Inputs of Various Data-Driven Methods for Battery Capacity Prediction by Kuo Xin, Fu Jia, Byoungik Choi, Geesoo Lee

“…Moreover, under the premise of obtaining more accurate prediction accuracy, different networks have different requirements for input data. …”
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Frailty risk prediction models for patients undergoing maintenance hemodialysis in China: a systematic review by Yu Zhong, Songmei Cao, Liangying Chen, Teng Li, Wei Ye

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Soybean Water Monitoring and Water Demand Prediction in Arid Region Based on UAV Multispectral Data by Shujie Jia, Mingyi Cui, Lei Chen, Shangyuan Guo, Hui Zhang, Zheyu Bai, Yaoyu Li, Linqiang Deng, Fuzhong Li, Wuping Zhang

“…Ten vegetation indices were constructed from multispectral data to explore statistical relationships between vegetation indices, surface soil moisture, canopy leaf water content, and deeper soil moisture. Predictive models were developed and evaluated. Results showed that the NDVI-based nonlinear regression model achieved the best performance for leaf water content (R² = 0.725), and a significant correlation was found between canopy leaf water content and 0–20 cm soil moisture (R² = 0.705), enabling predictions of deeper soil moisture. …”
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Prediction of Concrete Compressive Strength Based on the BP Neural Network Optimized by Random Forest and ISSA by Gang Chen, Donglin Zhu, Xiao Wang, Changjun Zhou, Xiangyu Chen

“…BP neural network (BPNN) tends to converge to different local minimum points, and the prediction accuracy is not high in the prediction of the compressive strength of concrete. …”
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Study on an Intelligent Prediction Method of Ticket Price in a Subway System with Public-Private Partnership by Shengmin Wang, Jun Fang, Lanjun Liu, Han Wu

“…The accurate and rapid prediction of ticket prices for a public-private partnership (PPP) subway system, which is an important research topic in the field of civil engineering management, is of critical importance to ensure its smooth operation. …”
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Multiorgan proteomic analysis of infected animal models predict potential host factors for chikungunya virus by Dongdong Lin, Cong Tang, Junbin Wang, Yun Yang, Hao Yang, Yanan Zhou, Wenhai Yu, Bai Li, Qing Huang, Haixuan Wang, Ran An, Xiaoming Liang, Yuhuan Yan, Longhai Yuan, Xuena Du, Yuxia Yuan, Yanwen Li, Shuaiyao Lu

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Data-knowledge hybrid driven intelligent prediction method of tunnel excavation profiles geometric deformation by Ya Hu, Jingyi Lu, Jun Zhu, Huixin Zhang, Ying Ren, Jianlin Wu, Jianbo Lai, Heng Zhang, Hongyue Zhao, Xiang Zeng

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Performance Evaluation of Two ANFIS Models for Predicting Water Quality Index of River Satluj (India) by Sharad Tiwari, Richa Babbar, Gagandeep Kaur

“…Novelty in the paper lies in the estimation of water quality index using two different clustering techniques: fuzzy C-means and subtractive clustering-based ANFIS and assessing their predictive accuracy. Each model was used to train, validate, and test the index that was obtained from seven water quality parameters including pH, conductivity, chlorides, nitrates, ammonia, and fecal coliforms. …”
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Human-Inspired Gait and Jumping Motion Generation for Bipedal Robots Using Model Predictive Control by Zhen Xu, Jianan Xie, Kenji Hashimoto

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