Article
Mathematics
Yi Jin, Yulin He, Defa Huang
Summary: The paper proposed an improved variable KDE (IVKDE) method, which can determine the optimal bandwidth for each data point based on the integrated squared error (ISE) criterion. Compared with fixed KDE (FKDE) and variable KDE (VKDE), IVKDE achieved lower estimation errors.
Article
Green & Sustainable Science & Technology
Fan Lin, Yao Zhang, Ke Wang, Jianxue Wang, Morun Zhu
Summary: This paper proposes a novel multi-step parametric method for intra-day probabilistic solar power forecasting and introduces two fat-tailed distributions to better model the conditional distribution of solar power output. It also utilizes a deep recurrent neural network model and a novel loss function for efficient model training. Numerical results show that the proposed method is effective in providing high-quality and reliable intra-day probabilistic solar power forecasting.
IEEE TRANSACTIONS ON SUSTAINABLE ENERGY
(2022)
Article
Computer Science, Hardware & Architecture
Suayb S. Arslan, Engin Zeydan
Summary: This article explores modeling disk failure trends in big data centers and proposes a method to calculate failure density through transformations and inverse transformations. The study suggests that, when dealing with heavy-tailed data, the complex Gaussian hypergeometric distribution and classical KDE approach can perform best in representing the data characteristics.
IEEE TRANSACTIONS ON RELIABILITY
(2021)
Article
Engineering, Civil
Chao Yin, Xihaier Luo, Ahsan Kareem
Summary: Stochastic dynamical systems play a significant role in various fields, with probabilistic features used to quantify uncertainties. Macro-scale and micro-scale methods each have limitations, while the meso-scale scheme combines advantages of both to provide a more effective solution.
Article
Automation & Control Systems
Qichun Zhang, Hong Wang
Summary: This article introduces a novel data-based approach to address the non-Gaussian stochastic distribution control problem, presenting a new probability density function transformation and two optimization algorithms.
IEEE TRANSACTIONS ON AUTOMATIC CONTROL
(2022)
Article
Computer Science, Artificial Intelligence
Patrik Puchert, Pedro Hermosilla, Tobias Ritschel, Timo Ropinski
Summary: The paper introduces a learned, data-driven deep density estimation method that can accurately and efficiently infer continuous probability density functions, independent of domain dimensionality or sample size. Training an unstructured convolutional neural network on synthetic PDFs allows for better generalization across a wide range of natural PDFs.
NEURAL COMPUTING & APPLICATIONS
(2021)
Article
Computer Science, Theory & Methods
Han Wang, Chuang Zheng
Summary: \
This paper focuses on a specific class of fuzzy numbers that can be uniquely identified by their membership functions. The authors construct a function space, denoted as Xh,p, by combining a set of nonlinear mappings h that represents subjective perception, and a set of probability density functions p that represent objective entities. Under their assumptions, they prove the existence of a class of h functions that can accurately predict the observed outcomes based on a given class of p functions. They also demonstrate that the commonly used triangular number can be interpreted using a function pair (h, p). They provide a numerical example in which h is the tangent function and p is the Gaussian kernel with a free variable μ, and show that Xh,p exhibits linear algebra properties under their defined operations.
FUZZY SETS AND SYSTEMS
(2023)
Article
Ecology
Antonio Proenca-Ferreira, Luis Borda-de-Agua, Miguel Porto, Antonio Mira, Francisco Moreira, Ricardo Pita
Summary: Organism dispersal is a widespread phenomenon with significant implications across various scales and levels of organization. The dispfit package, introduced in this article, is an R software application that provides intuitive and comprehensive tools to estimate and describe dispersal distances. It includes 9 commonly used distributions, computes goodness-of-fit and model selection statistics, and estimates distribution parameters and moments. We believe that dispfit will greatly contribute to improving the modeling of species' dispersal distances and enhancing our understanding of ecological and evolutionary processes involving dispersal movement.
ECOLOGICAL INFORMATICS
(2023)
Article
Computer Science, Information Systems
Lu Kang, Wenzhou Wu, Bin He, Vincent Lyne, Fenzhen Su
Summary: This paper constructed global daily vessel routes using AIS point data for 2014 and 2018, and applied the kernel density estimation method to analyze the density distribution. An accessibility model was proposed and applied to assess the global sea area accessibility in 2014 and 2018. The study revealed temporal and spatial variations in maritime traffic accessibility, which can guide resource allocation, species protection, and spatial planning.
Article
Engineering, Electrical & Electronic
Magda Amiridi, Nikos Kargas, Nicholas D. Sidiropoulos
Summary: This paper proposes a novel approach based on tensor factorization for non-parametric density estimation in high-dimensional multivariate data analysis. By using a tensor model of the characteristic function, the density can be accurately estimated and the curse of dimensionality can be overcome.
IEEE TRANSACTIONS ON SIGNAL PROCESSING
(2022)
Article
Mathematics
Lev B. B. Klebanov, Yulia V. V. Kuvaeva-Gudoshnikova, Svetlozar T. T. Rachev
Summary: This paragraph provides two examples of heavy-tailed distributions in social sciences applications, including the laws of Pareto and Lotka and some new ones. The examples are illustrated through the construction of suitable toy models.
Article
Statistics & Probability
Abouzar Bazyari
Summary: This paper investigates the inequality problem of ruin probabilities in insurance surplus models. In the presence of certain restrictions, statistical and mathematical approaches are used to derive inequalities related to the probability, which depend on the initial reserve amount and the mathematical functions of the random variables.
COMMUNICATIONS IN STATISTICS-THEORY AND METHODS
(2023)
Article
Engineering, Multidisciplinary
Tianzeng Tao, Guozhong Zhao, Yang Yu, Bowei Huang, Hao Zheng
Summary: This paper proposes a fully adaptive method to estimate the probability density function (PDF) for stochastic structures under static and dynamic loads. The method uses a weighted kernel density estimation (weighted-KDE) approach to adaptively determine the smoothing parameter and the number of samples. A new iterative sampling strategy is also introduced. Four engineering examples validate the adaptive ability, efficiency, and accuracy of the proposed method.
COMPUTER METHODS IN APPLIED MECHANICS AND ENGINEERING
(2022)
Article
Computer Science, Information Systems
Yu-Lin He, Xuan Ye, De-Fa Huang, Joshua Zhexue Huang, Jun-Hai Zhai
Summary: This paper proposes a novel ensemble UCV based KDE (EUCV-KDE), which determines the expectation of an estimated PDF using an ensemble of data-block based UCVs. A novel objective function is designed for EUCV-KDE by considering the empirical and structural risk of KDE together. The experimental results show that EUCV-KDE is more stable and performs better than classical UCV-KDE and RCV-KDE.
INFORMATION SCIENCES
(2021)
Article
Medicine, General & Internal
Theodora Chatzimichail, Aristides T. Hatjimihail
Summary: Medical diagnosis is crucial for treatment and management decisions in healthcare. This study developed a computational tool based on Bayesian inference to calculate the posterior probability of disease diagnosis and compare different distribution models.
Article
Agronomy
Do Kyoung Lee, Ezra Aberle, Eric K. Anderson, William Anderson, Brian S. Baldwin, David Baltensperger, Michael Barrett, Jurg Blumenthal, Stacy Bonos, Joe Bouton, David I. Bransby, Charlie Brummer, Pane S. Burks, Chengci Chen, Christopher Daly, Josh Egenolf, Rodney L. Farris, John H. Fike, Roch Gaussoin, John R. Gill, Kenneth Gravois, Michael D. Halbleib, Anna Hale, Wayne Hanna, Keith Harmoney, Emily A. Heaton, Ron W. Heiniger, Lindsey Hoffman, Chang O. Hong, Gopal Kakani, Robert Kallenbach, Bisoondat Macoon, James C. Medley, Ali Missaoui, Robert Mitchell, Ken J. Moore, Jesse I. Morrison, Gary N. Odvody, Jonathan D. Richwine, Richard Ogoshi, Jimmy Ray Parrish, Lauren Quinn, Ed Richard, William L. Rooney, J. Brett Rushing, Ronnie Schnell, Matt Sousek, Scott A. Staggenborg, Thomas Tew, Goro Uehara, Donald R. Viands, Thomas Voigt, David Williams, Linda Williams, Lloyd Ted Wilson, Andrew Wycislo, Yubin Yang, Vance Owens
GLOBAL CHANGE BIOLOGY BIOENERGY
(2018)
Article
Agronomy
Jose L. Gonzalez-Andujar, Maria J. Aguilera, Adam S. Davis, Luis Navarrete
FIELD CROPS RESEARCH
(2019)
Article
Agriculture, Multidisciplinary
Wyatt McAllister, Denis Osipychev, Adam Davis, Girish Chowdhary
COMPUTERS AND ELECTRONICS IN AGRICULTURE
(2019)
Article
Agronomy
Seth A. Strom, Aaron G. Hager, Nicholas J. Seiter, Adam S. Davis, Dean E. Riechers
PEST MANAGEMENT SCIENCE
(2020)
Article
Agronomy
Valle Egea-Cobrero, Kevin Bradley, Isabel M. Calha, Adam S. Davis, Jose Dorado, Frank Forcella, John L. Lindquist, Christy L. Sprague, Jose L. Gonzalez-Andujar
Article
Plant Sciences
Paul-Camilo Zalamea, Carolina Sarmiento, A. Elizabeth Arnold, Adam S. Davis, Astrid Ferrer, James W. Dalling
Summary: The field study showed that the composition of seed-associated fungal communities in co-occurring pioneer tree species is primarily influenced by plant species identity, with little impact from burial location and seed viability. Phylogenetic relatedness of fungi mainly reflects differences between Jacaranda and Cecropia.
JOURNAL OF ECOLOGY
(2021)
Article
Agronomy
Christopher A. Landau, Aaron G. Hager, Patrick J. Tranel, Adam S. Davis, Nicolas F. Martin, Martin M. Williams
Summary: This study revealed that adequate rainfall within the first 15 days after PRE herbicide application is crucial for effective weed control. Herbicide combinations require less rainfall to maximize the probability of effective control and are more successful in controlling weeds compared to herbicides applied individually.
PEST MANAGEMENT SCIENCE
(2021)
Article
Plant Sciences
Seth A. Strom, Aaron G. Hager, Jeanaflor Crystal T. Concepcion, Nicholas J. Seiter, Adam S. Davis, James A. Morris, Shiv S. Kaundun, Dean E. Riechers
Summary: The resistance of waterhemp to the herbicide S-metolachlor involves a combination of Phase I and Phase II metabolic activities, specifically the O-demethylation reaction conferring resistance. Greater activities of GSTs and P450s were observed in resistant populations compared to sensitive populations, leading to increased metabolism of S-metolachlor and the formation of resistant metabolites.
PLANT AND CELL PHYSIOLOGY
(2021)
Article
Agronomy
Charles M. Geddes, Adam S. Davis
Summary: The proliferation of herbicide-resistant weeds underscores the need to re-evaluate fundamental weed control objectives, with a focus on limiting weed seed return to prevent further resistance. The Critical Period for Weed Seed Control (CPWSC) targets specific phenological stages to minimize weed seed production, offering a strategic framework for effective weed management. This concept is exemplified using Bassia scoparia as a model species and provides a foundation for future research in this area.
Article
Agronomy
Brendan C. S. Alexander, Adam S. Davis
Summary: P values, binary hypothesis tests, and statistical significance are often misused or overused in pest management reports. These statistical results are not the focus; the biological interpretation of the data is the key aspect of the analysis.
PEST MANAGEMENT SCIENCE
(2022)
Article
Agronomy
Lauren M. Schwartz-Lazaro, Lovreet S. Shergill, Jeffrey A. Evans, Muthukumar Bagavathiannan, Shawn C. Beam, Mandy D. Bish, Jason A. Bond, Kevin W. Bradley, William S. Curran, Adam S. Davis, Wesley J. Everman, Michael L. Flessner, Steven C. Haring, Nicholas R. Jordan, Nicholas E. Korres, John L. Lindquist, Jason K. Norsworthy, Tameka L. Sanders, Larry E. Steckel, Mark J. VanGessel, Blake Young, Steven B. Mirsky
Summary: Weather conditions do not have a consistent impact on weed seed shatter, while individual weed plant biomass is positively correlated with seed-shattering rates. Harvest weed seed control has the potential to reduce inputs from plants that have escaped early management, but individuals that shatter seeds early pose a risk of escaping control measures.
Article
Agronomy
Seth A. Strom, Kip E. Jacobs, Nicholas J. Seiter, Adam S. Davis, Dean E. Riechers, Aaron G. Hager
Summary: VLCFA-inhibiting herbicides have been widely used for controlling waterhemp, but they are not effective against herbicide-resistant populations. Proper herbicide stewardship and integrated weed management practices should be implemented to maintain efficacy in the future.
Article
Food Science & Technology
Nicole M. Lee, Lav R. Varshney, Hope C. Michelson, Peter Goldsmith, Adam Davis
Summary: Blockchain technology has the potential to address trust and equity issues in smallholder agricultural development, with applications like BanQu providing verified financial identities for smallholders. However, blockchain alone is not the sole solution to all the challenges faced by the smallholder farming sector.
GLOBAL FOOD SECURITY-AGRICULTURE POLICY ECONOMICS AND ENVIRONMENT
(2022)
Article
Plant Sciences
Carolyn J. Lowry, David P. Matlaga, Natalie M. West, Martin M. Williams, Adam S. Davis
Summary: Research shows that eradicating feral Miscanthus populations is costly, especially in old field sites, and labor is the major cost component. The predicted total economic cost of eradicating reported Miscanthus populations ranges from $10 to $37 million.
INVASIVE PLANT SCIENCE AND MANAGEMENT
(2022)
Article
Microbiology
Alison H. Harrington, Carolina Sarmiento, Paul-Camilo Zalamea, James W. Dalling, Adam S. Davis, A. Elizabeth Arnold
Summary: In this study, a new species of Acrogenospora, Acrogenospora terricola sp. nov., is described, and it is confirmed that the genus has a pantropical distribution. The observation of Acrogenospora infecting seeds in a terrestrial environment is different from previously described species in the genus. This study highlights the taxonomic value of collections derived from ecological studies of fungal communities and demonstrates how rich sequence databases can provide insights into the identity, distributions, and diversity of cryptic microfungi.
INTERNATIONAL JOURNAL OF SYSTEMATIC AND EVOLUTIONARY MICROBIOLOGY
(2022)