Article
Computer Science, Interdisciplinary Applications
Yuying Wei, Adrian Wing-Keung Law, Chun Yang
Summary: In this study, the data assimilation framework called Probabilistic Optimal Interpolation (POI) is further developed for handling nonstationary environments and missing data. The results show that POI implementation can reduce uncertainty, but its performance is affected by the accuracy limitation of machine learning models in nonstationary environments.
JOURNAL OF COMPUTATIONAL SCIENCE
(2023)
Article
Chemistry, Multidisciplinary
Yujuan Zou, Zhijian Wang
Summary: This study proposes an improved density peak clustering algorithm, ConDPC, which incorporates the idea of connectivity to enhance clustering accuracy and address the limitations of the original algorithm in certain scenarios. Experimental results validate the effectiveness of ConDPC.
APPLIED SCIENCES-BASEL
(2022)
Article
Meteorology & Atmospheric Sciences
Yohei Sawada
Summary: A new method called HOOPE-PF is introduced to estimate time-varying parameters in relatively low dimensional models. It outperforms the original SIRPF in synthetic and real-data experiments, and is not greatly affected by the size of perturbations added to ensemble members.
JOURNAL OF ADVANCES IN MODELING EARTH SYSTEMS
(2022)
Article
Computer Science, Information Systems
Han Liu, Xiaotong Zhang, Xianchao Zhang, Qimai Li, Xiao-Ming Wuc
Summary: This paper introduces a consistent clustering algorithm based on representative possible worlds, which effectively selects representative possible worlds and integrates a consistency learning process to improve efficiency and performance. The experimental results demonstrate that the proposed algorithm is more effective than existing algorithms and competitive in efficiency.
COMPUTER COMMUNICATIONS
(2021)
Article
Engineering, Environmental
Xiao Zhou, Shuyi Guo, Kunlun Xin, Weirong Xu, Tao Tao, Hexiang Yan
Summary: The upgrading of water supply services requires accurate and adaptive numerical models, and data assimilation methods can enhance the long-term accuracy and stability of the models by reducing uncertainties.
Article
Meteorology & Atmospheric Sciences
John Maclean, Erik S. Van Vleck
Summary: This study introduces a framework for data assimilation that divides data into multiple low-rank projections for state space. Algorithms are developed to assimilate these projected data, and the major application explored is PROJ-PF for highly informative but low-dimensional observations. The implementation is based on projections in the unstable subspace, aiming to mitigate the collapse of particle ensembles in high-dimensional DA problems.
QUARTERLY JOURNAL OF THE ROYAL METEOROLOGICAL SOCIETY
(2021)
Article
Biochemical Research Methods
Guanjin Qu, Zihui Yan, Huaming Wu
Summary: This paper proposes an efficient DNA clustering method, Clover, for DNA storage, which has linear computational complexity and low memory. Experimental results demonstrate that the method can accurately cluster a large number of DNA sequences in a short time.
BRIEFINGS IN BIOINFORMATICS
(2022)
Article
Energy & Fuels
Hosein Haddadpour, Mohammad Emami Niri
Summary: This study proposes a workflow based on distance-based clustering method for selecting representative models. It utilizes a two-stage selection algorithm to group similar models in terms of spatial distributions and patterns in the first stage, and defines dynamic parameters for reservoir performance uncertainty assessment in the second stage. By reducing the number of initial realizations prior to calculating the dynamic measure, the process becomes much faster.
JOURNAL OF PETROLEUM SCIENCE AND ENGINEERING
(2021)
Article
Energy & Fuels
Celio Maschio, Guilherme Daniel Avansi, Felipe Bruno Mesquita da Silva, Denis Jose Schiozer
Summary: In this study, a methodology combining lower-fidelity models and efficient data assimilation methods was proposed to achieve a balance between computational time and result quality. The results showed that the data assimilation process using lower-fidelity models reduced the computational time significantly while maintaining similar or even better results.
JOURNAL OF PETROLEUM SCIENCE AND ENGINEERING
(2022)
Article
Multidisciplinary Sciences
Tadeo Javier Cocucci, Manuel Pulido, Juan Pablo Aparicio, Juan Ruiz, Mario Ignacio Simoy, Santiago Rosa
Summary: This paper proposes the coupling of an epidemiological agent-based model with the ensemble Kalman filter to represent the complex individual interactions in the dynamics of disease spread informed by data. The statistical inference of disease propagation through ensemble-based data assimilation systems has been studied previously, but the existing models mainly focus on mean field evolution and cannot capture individual interactions. Agent-based models can describe contact networks at an individual level, but they have unknown parameters that are difficult to determine. To address this, the paper suggests using ensemble-based data assimilation techniques to calibrate an agent-based model using daily epidemiological data. The effectiveness of this methodology is evaluated using synthetic data and COVID-19 daily reports.
Article
Computer Science, Theory & Methods
Mohsen Rahmanian, Eghbal Mansoori
Summary: The use of feature selection methods is essential for improving data readability, reducing complexity of learning algorithms, and enhancing predictability, especially when dealing with a large number of features. Unsupervised feature selection techniques, particularly those based on information theory, have been extensively explored. However, existing methods based on bivariate measures fail to consider dependencies among more than two features. To address this, this research proposes a novel unsupervised feature selection method called Fuzzy Multivariate Symmetric Uncertainty-Feature Selection (FMSU-FS), which also eliminates the need for discretization of continuous features and the resulting information loss. Experimental results on benchmark datasets demonstrate the superiority of the proposed FMSU-FS method in measuring clustering performance.
FUZZY SETS AND SYSTEMS
(2022)
Article
Computer Science, Artificial Intelligence
Hamid Rezaei, Negin Daneshpour
Summary: This article focuses on the challenge of determining the degree of similarity measurement in mixed data clustering. It proposes a more efficient method by innovating in three important aspects of clustering. The method considers both distance and the number of similar features for assigning data objects to clusters, and it outperforms other algorithms in terms of accuracy on three datasets.
PATTERN RECOGNITION
(2023)
Review
Mathematics
Amir Ghorbani, Vahid Ghorbani, Morteza Nazari-Heris, Somayeh Asadi
Summary: This article reviews the use of data assimilation methods for agent-based models, focusing on pedestrians and passengers in transportation systems. It introduces advanced techniques and explains the underlying mathematical principles involved. The integration of machine learning with data assimilation methods is identified as a potential avenue for future research.
Article
Agronomy
Jingye Han, Liangsheng Shi, Qi Yang, Zhuowei Chen, Jin Yu, Yuanyuan Zha
Summary: This study proposes an image-driven data assimilation framework for smallholder farmers to estimate crop yield. By training a convolutional neural network to estimate the probability distribution of crop states from images, and assimilating the estimated probabilities into a crop growth model, the accuracy of yield estimation is significantly improved. The results demonstrate the feasibility of using easily available camera images to drive the crop growth model, and the probability distribution estimation method allows for quantifying observation errors.
FIELD CROPS RESEARCH
(2022)
Article
Computer Science, Artificial Intelligence
Cristina Tortora, Francesco Palumbo
Summary: This paper discusses a probabilistic distance clustering method adjusted for cluster size (PDQ) for handling mixed-type data, shows its advantages through a simulation design, and applies it to a real data set.
APPLIED SOFT COMPUTING
(2022)
Article
Energy & Fuels
Cello Maschio, Alessandra Davolio, Manuel Gomes Correia, Denis Jose Schiozer
JOURNAL OF PETROLEUM SCIENCE AND ENGINEERING
(2015)
Article
Energy & Fuels
Manuel Gomes Correia, Celio Maschio, Joao Carlos von Hohendorff Filho, Denis Jose Schiozer
JOURNAL OF PETROLEUM SCIENCE AND ENGINEERING
(2016)
Article
Engineering, Mechanical
Manuel Gomes Correia, Celio Maschio, Denis Jose Schiozer
JOURNAL OF THE BRAZILIAN SOCIETY OF MECHANICAL SCIENCES AND ENGINEERING
(2017)
Article
Energy & Fuels
V. E. Botechia, M. G. Correia, D. J. Schiozer
JOURNAL OF PETROLEUM SCIENCE AND ENGINEERING
(2017)
Article
Energy & Fuels
Luis Fernando Lamas, Vinicius Eduardo Botechia, Manuel Gomes Correia, Denis Jose Schiozer, Mojdeh Delshad
JOURNAL OF PETROLEUM SCIENCE AND ENGINEERING
(2018)
Article
Energy & Fuels
Manuel Gomes Correia, Lio Maschio, Denis Jose Schiozer
OIL & GAS SCIENCE AND TECHNOLOGY-REVUE D IFP ENERGIES NOUVELLES
(2018)
Article
Energy & Fuels
Seyed Kourosh Mahjour, Manuel Gomes Correia, Antonio Alberto de Souza dos Santos, Denis Jose Schiozer
JOURNAL OF ENERGY RESOURCES TECHNOLOGY-TRANSACTIONS OF THE ASME
(2020)
Article
Energy & Fuels
Manuel Gomes Correia, Joao Carlos von Hohendorff Filho, Denis Jose Schiozer
JOURNAL OF PETROLEUM SCIENCE AND ENGINEERING
(2019)
Article
Energy & Fuels
Seyed Kourosh Mahjour, Antonio Alberto Souza Santos, Manuel Gomes Correia, Denis Jose Schiozer
Summary: The study compared the effectiveness of the DCSMC method using static data and the metaheuristic algorithm using dynamic data in the scenario reduction process, with results indicating that static data is more reliable during the field development phase.
JOURNAL OF PETROLEUM EXPLORATION AND PRODUCTION TECHNOLOGY
(2021)
Article
Rehabilitation
Tiina Itkonen, Bryan Tomlin, Manuel G. Correia, Luis A. Sanchez, Tracie Schneider, Kellie Kooker
Summary: This research examined the relationship between Schaffer v. Weast (2005) and special education due process hearing decisions in California. The study found that the ruling significantly decreased the likelihood of favorable outcomes for students in special education due process hearings.
JOURNAL OF DISABILITY POLICY STUDIES
(2022)
Article
Geosciences, Multidisciplinary
Manuel Gomes Correia, Masoud Maleki, Felipe Bruno Mesquita da Silva, Alessandra Davolio Gomes, Denis Jose Schiozer
Summary: This work presents a workflow to integrate 4D seismic insights and calibrate simulation models using observed dynamic data. The methodology includes developing a geological model, generating geostatistical realizations, applying a combination of the Latin Hypercube sampling technique and geostatistics realizations, and validating the geological consistency and uncertainty quantification. The methodology is applied to a real turbiditic reservoir in the offshore Campos Basin, Brazil, and successfully generates prior simulation models that encompass the observed production data.
PETROLEUM GEOSCIENCE
(2023)
Article
Energy & Fuels
Manuel Gomes Correia, Joao Carlos von Hohendorff Filho, Denis Jose Schiozer
SPE RESERVOIR EVALUATION & ENGINEERING
(2020)
Article
Energy & Fuels
Seyed Kourosh Mahjour, Manuel Gomes Correia, Antonio Alberto de Souza dos Santos, Denis Jose Schiozer
OIL & GAS SCIENCE AND TECHNOLOGY-REVUE D IFP ENERGIES NOUVELLES
(2019)
Article
Energy & Fuels
Manuel Gomes Correia, Denis Jose Schiozer
SPE RESERVOIR EVALUATION & ENGINEERING
(2018)