Learning predictive signatures of HLA type from T-cell repertoires. by María Ruiz Ortega, Mikhail V Pogorelyy, Anastasia A Minervina, Paul G Thomas, Thierry Mora, Aleksandra M Walczak

“…The resulting model shows good predictive performance, even for relatively rare HLA alleles.…”
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Adaptive Multihypothesis Prediction Algorithm for Distributed Compressive Video Sensing by Jinxiu Zhu, Ning Cao, Yu Meng

“…A novel adaptive multihypothesis (MH) prediction algorithm for distributed compressive video sensing (DCVS) is proposed in this paper. …”
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Prediction of Rooftop Photovoltaic Solar Potential Using Machine Learning by K. Mukilan, K. Thaiyalnayaki, Yagya Dutta Dwivedi, J. Samson Isaac, Amarjeet Poonia, Arvind Sharma, Essam A. Al-Ammar, Saikh Mohammad Wabaidur, B. B. Subramanian, Adane Kassa

“…The results of simulation are conducted on R-package over various libraries to predict the rooftop solar potential. The results of simulation shows that the proposed method achieves higher rate of prediction accuracy than the other methods. …”
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Current Trends in Class Imbalance Learning for Software Defect Prediction by Somya R. Goyal

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Modeling and Predicting Stochastic Merging Behaviors at Freeway On-Ramp Bottlenecks by Jian Sun, Kang Zuo, Shun Jiang, Zuduo Zheng

“…This way could make the full use of multi-rejected gaps and accepted gaps and reduce the sample bias, thus estimating the critical gap accurately; finally, considering multi-rejected gaps, it created logistic regression models to predict merging behavior. These models were tested using field data, and satisfactory performances were obtained.…”
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The Burden of Cost in Bronchiolitis Obliterans Syndrome: Predictions for the Next Decade by Christopher A. Jones, David G. Chapman, Peter Weimersheimer, Luca Fernandez, Oscar Alejandro Mesa, Christian Peters, Bart M. Vanaudenaerde, Mitchell C. Norotsky, Robin Vos

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Prediction of Concrete Compressive Strength by Evolutionary Artificial Neural Networks by Mehdi Nikoo, Farshid Torabian Moghadam, Łukasz Sadowski

“…Compressive strength of concrete has been predicted using evolutionary artificial neural networks (EANNs) as a combination of artificial neural network (ANN) and evolutionary search procedures, such as genetic algorithms (GA). …”
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Prominence of Microbiota to Predict Fibrous Stenosis in Crohn’s Disease by Yang X, Pan Y, Gao CP, Li H, Zhang YH, Huang CL, Cao L, Xiao SY, Zhou Z

“…We identified specific microbiota and assessed their predictive accuracy for intestinal fibrous stenosis. …”
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A Performance Analysis of Business Intelligence Techniques on Crime Prediction by Ivan, Niyonzima, Emmanuel Ahishakiye, Elisha Opiyo Omulo, Ruth Wario

Subjects: “…Law Enforcement Agencies; crime prediction; Business Intelligence; WEKA; Performance Analysis…”
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High prediction skill of decadal tropical cyclone variability in the North Atlantic and East Pacific in the met office decadal prediction system DePreSys4 by Paul-Arthur Monerie, Xiangbo Feng, Kevin Hodges, Ralf Toumi

“…Abstract The UK Met Office decadal prediction system DePreSys4 shows skill in predicting the number of tropical cyclones (TCs) and TC track density over the eastern Pacific and tropical Atlantic Ocean on the decadal timescale (up to ACC = 0.93 and ACC = 0.83, respectively, as measured by the anomaly correlation coefficient—ACC). …”
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Marine ecological information prediction by using adjacent location spatiotemporal deep learning model with ensemble learning techniques by Yue-Shan Chang, Shu-Ting Huang, Basanta Haobijam, Satheesh Abimannan, Takayuki Kushida

Subjects: “…Sea surface temperature prediction…”
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Predictive Modeling of Juvenile Smalltooth Sawfish Habitats: Challenges and Opportunities for Conservation by Andrea M. Kroetz, Simon Dedman, John K. Carlson

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Driver Route Planning Method Based on Accident Risk Cost Prediction by Xiaoleng Liao, Tong Zhou, Xu Wang, Rongjian Dai, Xuehui Chen, Xiangmin Zhu

“…The results show that the accident risk cost prediction model based on historical accident data can be used to quantify driving risk. …”
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Anisotropic Elastoplastic Damage Mechanics Method to Predict Fatigue Life of the Structure by Hualiang Wan, Qizhi Wang, Zheng Zhang

“…New damage mechanics method is proposed to predict the low-cycle fatigue life of metallic structures under multiaxial loading. …”
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A Prediction Method of Tensile Young's Modulus of Concrete at Early Age by Isamu Yoshitake, Farshad Rajabipour, Yoichi Mimura, Andrew Scanlon

“…To enable a direct estimation of the tensile modulus of concrete, a simple three-phase composite model is developed based on random distributions of coarse aggregate, mortar, and air void phases. The model predictions show good agreement with experimental measurements of tensile modulus at early age.…”
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Plasma biomarkers for predicting heart failure in patients with acute myocardial infarction by Guihong Rong, Xiao Wang, Xinling Qin, Yanxia Wang, Meilian Quan, Chunfeng Xi

“…Subsequently, we performed t-tests to assess the predictive value of these biomarkers for post-AMI HF. …”
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Dynamic Prediction for Accuracy Maintaining Reliability of Superprecision Rolling Bearing in Service by Liang Ye, Xintao Xia, Zhen Chang

“…A dynamic prediction method for accuracy maintaining reliability (AMR) of superprecision rolling bearings (SPRBs) in service is proposed by effectively fusing chaos theory and grey system theory and applying stochastic processes. …”
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Strength Prediction Model for Cohesive Soil–Rock Mixture with Rock Content by Yang Sun, Jianyong Xin, Junchao He, Junping Yu, Haibin Ding, Yifan Hu

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Unveiling diabetes onset: Optimized XGBoost with Bayesian optimization for enhanced prediction. by Muhammad Rizwan Khurshid, Sadaf Manzoor, Touseef Sadiq, Lal Hussain, Mohammed Shahbaz Khan, Ashit Kumar Dutta

“…Traditional prediction models, often limited by default parameters, have been superseded by more sophisticated approaches. …”
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Improving the Accuracy for Analyzing Heart Diseases Prediction Based on the Ensemble Method by Xiao-Yan Gao, Abdelmegeid Amin Ali, Hassan Shaban Hassan, Eman M. Anwar

“…In this paper, ensemble learning methods are used to enhance the performance of predicting heart disease. Two features of extraction methods: linear discriminant analysis (LDA) and principal component analysis (PCA), are used to select essential features from the dataset. …”
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