Attack scenarios reasoning,hypothesizing and predicting based on capability transition model by TIAN Zhi-hong1, ZHANG Wei-zhe1, ZHANG Yong-zheng2, ZHANG Hong-li 1, LI Yang2, JIANG Wei1

“…To construct attack scenarios and predict intrusion intents automatically,a real-time alert correlation approach based on capability transition model was proposed.By highly abstracting the reasoning evidences,the process complexity is effectively reduced.Experiment results on the DARPA2000 IDS test dataset indicate that the method is effective and efficient.…”
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Predicting online shopping addiction: a decision tree model analysis by Xueli Wan, Jie Zeng, Ling Zhang

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Attack scenarios reasoning,hypothesizing and predicting based on capability transition model by TIAN Zhi-hong1, ZHANG Wei-zhe1, ZHANG Yong-zheng2, ZHANG Hong-li 1, LI Yang2, JIANG Wei1

“…To construct attack scenarios and predict intrusion intents automatically,a real-time alert correlation approach based on capability transition model was proposed.By highly abstracting the reasoning evidences,the process complexity is effectively reduced.Experiment results on the DARPA2000 IDS test dataset indicate that the method is effective and efficient.…”
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Predicting the Time-dependent Mechanics of Concrete Based on a Multiscale Model by Shijun Wang, Changqing Du, Mingqing Gu, Chunlin Pan, Teng Tong

“…To accurately predict the time-dependent deformation of concrete, a multiscale model with its focus pinned on mesoscale is proposed here to break down the constitutive law of concrete to the mechanics of its different constituent phases. …”
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LSTM+MA: A Time-Series Model for Predicting Pavement IRI by Tianjie Zhang, Alex Smith, Huachun Zhai, Yang Lu

“…In this work, a long short-term memory (LSTM)-based model, LSTM+MA, is proposed to predict the IRI of pavements using the time-series data extracted from the long-term pavement performance (LTPP) dataset. …”
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Development of an autoregressive neural network model for predicting accidents in the Khabarovsk Territory by E. V. Shokhirev, P. P. Volodkin, V. A. Lazarev, A. V. Konstantinov

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BIMLP Model Based on Deep Learning for Predicting Electrical Load Demand by Somayeh Talebzadeh, Reza Radfar, Abbas Toloei Ashlaghi

“…To address this challenge, this research proposes a novel hybrid machine-learning approach for predicting electricity demand. In this research, first, different regression methods were investigated to solve the problem, the results showed that the multi-layer perceptron (MLP) regression model has the best performance in predicting electricity demand. …”
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Digital model for predicting the risk of developing acute decompensated heart failure by N. B. Lebedeva, A. P. Egle, Yu. A. Argunova, O. L. Barbarash

“…Development and external validation of a risk prediction model for acute decompensated heart failure (ADHF) in patients with low left ventricular ejection fraction.Material and methods. …”
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Method for Predicting the Outcome of Burn Injury Based on a Mathematical Model by E. A. Zhirkova, T. G. Spiridonova, O. G. Sinyakova, A. V. Sachkov, A. O. Medvedev, E. I. Eliseenkova, I. G. Borisov, M. L. Rogal, S. S. Petrikov

“…The choice of treatment tactics for a patient with burns should be based on individual prediction of injury outcome. Known models for predicting the outcome of burn injury are inaccurate and do not allow us to determine the probability of different outcomes for a particular patient.AIM OF THE STUDY. …”
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The Usefulness of The Capital Asset Pricing Model in Predicting Total Shareholder Return by Chnar Abdullah Rashid, Rizgar Abdullah Sabir Jaf

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The Utilization of a Naïve Bayes Model for Predicting the Energy Consumption of Buildings by Behnam Sadaghat, Ali Javadzade Khiavi, Babak Naeim, Erfan Khajavi, Hadi Sadaghat, Amir Reza Taghavi Khanghah

“…To gauge the predictive efficacy of the models, an array of performance metrics, including R2, RMSE, MSE, WAPE, and the NSE, were employed for assessment. …”
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A novel model for predicting immunotherapy response and prognosis in NSCLC patients by Ting Zang, Xiaorong Luo, Yangyu Mo, Jietao Lin, Weiguo Lu, Zhiling Li, Yingchun Zhou, Shulin Chen

“…The RF model demonstrated better predictive performance for immunotherapy responses than the Nomogram model. …”
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An Atmospheric Signal Lowering the Spring Predictability Barrier in Statistical ENSO Forecasts by Dmitry Mukhin, Andrey Gavrilov, Aleksei Seleznev, Maria Buyanova

“…Abstract The loss of autocorrelations of tropical sea surface temperatures (SST) during late spring, also called the spring predictability barrier (SPB), is a factor that strongly limits the predictability of El Nino Southern Oscillation (ENSO), and especially the statistical SST‐based ENSO forecasts starting from the winter‐spring season. …”
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Hybrid Deep Learning Approaches for Improved Genomic Prediction in Crop Breeding by Ran Li, Dongfeng Zhang, Yanyun Han, Zhongqiang Liu, Qiusi Zhang, Qi Zhang, Xiaofeng Wang, Shouhui Pan, Jiahao Sun, Kaiyi Wang

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Predicting Atmospheric Dispersion of Industrial Chemicals Using Machine Learning Approaches by Maria Valle, Jairo A. Cardona, Cesar Viloria-Nunez, Christian G. Quintero M.

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An elastic net regression model for predicting the risk of ICU admission and death for hospitalized patients with COVID-19 by Wei Zou, Xiujuan Yao, Yizhen Chen, Xiaoqin Li, Jiandong Huang, Yong Zhang, Lin Yu, Baosong Xie

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Hospital-wide, dynamic, individualized prediction of central line-associated bloodstream infections-development and temporal evaluation of six prediction models by Elena Albu, Shan Gao, Pieter Stijnen, Frank E. Rademakers, Christel Janssens, Veerle Cossey, Yves Debaveye, Laure Wynants, Ben Van Calster

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Prediction of 1-year post-operative mortality in elderly patients with fragility hip fractures in China: evaluation of risk prediction models by Qiyuan Lu, Mengmeng Chen, Houfu Ling

“…Model-derived mortality predictions and risk categorizations were computed. …”
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Development of Concentration-Prediction Models in Multiple Manufacturing Environments Using NIR Spectroscopy by Yusuke Hayashi, Saho Okazaki, Kazuya Tanabe, Takuya Nagato, Hirokazu Sugiyama

“…This work presents development of concentration-prediction models applicable to multiple work environments using near-infrared (NIR) spectroscopy. …”
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Construction and validation of risk prediction models for different subtypes of retinal vein occlusion by Chunlan Liang, Lian Liu, Wenjuan Yu, Qi Shi, Jiang Zheng, Jun Lyu, Jingxiang Zhong

“…Purpose: While prognostic models for retinal vein occlusion (RVO) exist, subtype-specific risk prediction tools for central retinal vein occlusion (CRVO) and branch retinal vein occlusion (BRVO) remain limited. …”
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