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61. Estimation of sparse directed acyclic graphs for multivariate counts data

Author:
Han, Sung Won; Zhong, Hua
Source:
Biometrics 2016 v.72 no.3 pp. 791-803
ISSN:
0006-341X
Subject:
normal distribution,   etc   ; algorithms; animal ovaries; biometry; gene regulatory networks; high-throughput nucleotide sequencing; lognormal distribution; ovarian neoplasms; variance;     Show all 9 Subjects
Abstract:
... The next‐generation sequencing data, called high‐throughput sequencing data, are recorded as count data, which are generally far from normal distribution. Under the assumption that the count data follow the Poisson log‐normal distribution, this article provides an L1‐penalized likelihood framework and an efficient search algorithm to estimate the structure of sparse directed acyclic graphs (DAGs) ...
DOI:
10.1111/biom.12467
PubMed:
26849781
PubMed Central:
PMC4975686

62. Optimization of wind turbine layout position in a wind farm using a newly-developed two-dimensional wake model

Author:
Gao, Xiaoxia; Yang, Hongxing; Lu, Lin
Source:
Applied energy 2016 v.174 pp. 192-200
ISSN:
0306-2619
Subject:
normal distribution,   etc   ; algorithms; models; power generation; turbulent flow; wind direction; wind farms; wind power; wind speed; wind tunnels; wind turbines;     Show all 11 Subjects
Abstract:
... The development and validation of a 2D analytical wind turbine wake model based on Jensen’s wake model using Gaussian function is presented in this paper. The velocity deficit predicted by the newly-developed Jensen–Gaussian wake model is compared with wind tunnel experimental measured data in literatures and results show that, the velocity deficit predicted by the model fits well with the measure ...
DOI:
10.1016/j.apenergy.2016.04.098

63. Weed detection using image processing under different illumination for site-specific areas spraying

Author:
Tang, Jing-Lei; Chen, Xiao-Qian; Miao, Rong-Hui; Wang, Dong
Source:
Computers and electronics in agriculture 2016 v.122 pp. 103-111
ISSN:
0168-1699
Subject:
normal distribution,   etc   ; algorithms; color; food quality; herbicides; image analysis; labor; lighting; models; pollution; spraying; sustainable development; wastes; weeds;     Show all 14 Subjects
Abstract:
... Large area bold type spraying of chemical herbicide is not only a waste of herbicides and labor, but also leads to environmental pollution and food quality problems. Traditional methods have the problems of high light and sample quality etc requirements. Therefore, accurately identifying weeds and precisely spraying are important strategies for promoting agricultural sustainable development. To av ...
DOI:
10.1016/j.compag.2015.12.016

64. A computational framework for uncertainty integration in stochastic unit commitment with intermittent renewable energy sources

Author:
Quan, Hao; Srinivasan, Dipti; Khambadkone, Ashwin M.; Khosravi, Abbas
Source:
Applied energy 2015 v.152 pp. 71-82
ISSN:
0306-2619
Subject:
normal distribution,   etc   ; algorithms; case studies; prediction; risk; solar energy; stochastic processes; uncertainty; wind; wind farms;     Show all 10 Subjects
Abstract:
... The penetration of intermittent renewable energy sources (IRESs) into power grids has increased in the last decade. Integration of wind farms and solar systems as the major IRESs have significantly boosted the level of uncertainty in operation of power systems. This paper proposes a comprehensive computational framework for quantification and integration of uncertainties in distributed power syste ...
DOI:
10.1016/j.apenergy.2015.04.103

65. Configurational entropy theory for streamflow forecasting

Author:
Cui, Huijuan; Singh, Vijay P.
Source:
Journal of hydrology 2015 v.521 pp. 1-17
ISSN:
0022-1694
Subject:
normal distribution,   etc   ; algorithms; autocorrelation; drainage; entropy; spectral analysis; stream flow; watersheds;     Show all 8 Subjects
Abstract:
... This study develops configurational entropy theory (CET) for monthly streamflow forecasting. The theory is comprised of three main parts: (1) determination of spectral density (2) determination of parameters by cepstrum analysis, and (3) extension of autocorrelation function. Comparison with the Burg entropy theory (BET) shows that CET yields higher resolution spectral density with more accurate l ...
DOI:
10.1016/j.jhydrol.2014.11.065

66. Imputation of missing data in time series for air pollutants

Author:
Junger, W.L.; Ponce de Leon, A.
Source:
Atmospheric environment 2015 v.102 pp. 96-104
ISSN:
1352-2310
Subject:
normal distribution,   etc   ; air; air pollution; algorithms; atmospheric chemistry; computer software; epidemiological studies; pollutants; time series analysis;     Show all 9 Subjects
Abstract:
... Missing data are major concerns in epidemiological studies of the health effects of environmental air pollutants. This article presents an imputation-based method that is suitable for multivariate time series data, which uses the EM algorithm under the assumption of normal distribution. Different approaches are considered for filtering the temporal component. A simulation study was performed to as ...
DOI:
10.1016/j.atmosenv.2014.11.049

67. A decompositional stand structure analysis for exploring stand dynamics of multiple attributes of a mixed-species forest

Author:
Lin, Chinsu; Tsogt, Khongor; Zandraabal, Tsogt
Source:
Forest ecology and management 2016 v.378 pp. 111-121
ISSN:
0378-1127
Subject:
normal distribution,   etc   ; Larix sibirica; Picea obovata; Weibull statistics; algorithms; boreal forests; ecotones; forest canopy; forest stands; growth models; mixed forests; mortality; overstory; stand structure; trees; Mongolia;     Show all 16 Subjects
Abstract:
... Forest dynamics is a particularly important issue as it describes changes in forest structure over time. Forest structure can be presented from using the attributes of age, diameter, height, abundance, density, etc. During the last few decades, most research has focused on these attributes separately while rarely investigating the dynamics of multiple attributes. This was due to the lack of an app ...
DOI:
10.1016/j.foreco.2016.07.022

68. Evaluating the predictive power of sun-induced chlorophyll fluorescence to estimate net photosynthesis of vegetation canopies: A SCOPE modeling study

Author:
Verrelst, Jochem; van der Tol, Christiaan; Magnani, Federico; Sabater, Neus; Rivera, Juan Pablo; Mohammed, Gina; Moreno, Jose
Source:
Remote sensing of environment 2016 v.176 pp. 139-151
ISSN:
0034-4257
Subject:
normal distribution,   etc   ; algorithms; canopy; chlorophyll; fluorescence; image analysis; leaf area index; leaves; models; photosynthesis; regression analysis; remote sensing; spectroscopy; superoxide anion; vegetation; water vapor;     Show all 16 Subjects
Abstract:
... Progress in imaging spectroscopy technology and data processing can enable derivation of the complete sun-induced chlorophyll fluorescence (SIF) emission spectrum. This opens up opportunities to fully exploit the use of the SIF spectrum as an indicator of photosynthetic activity. Simulations performed with the coupled fluorescence–photosynthesis model SCOPE were used to determine how strongly cano ...
DOI:
10.1016/j.rse.2016.01.018

69. Evaluation of Dynamically Dimensioned Search Algorithm for Optimizing SWAT by Altering Sampling Distributions and Searching Range

Author:
Yen, Haw; Jeong, Jaehak; Smith, Douglas R.
Source:
JAWRA Journal of the American Water Resources Association 2016 v.52 no.2 pp. 443-455
ISSN:
1093-474X
Subject:
normal distribution,   etc   ; Soil and Water Assessment Tool model; agricultural watersheds; algorithms; calibration; guidelines; prediction; sampling; simulation models; variance; water quality; Texas;     Show all 12 Subjects
Abstract:
... The primary advantage of Dynamically Dimensioned Search algorithm (DDS) is that it outperforms many other optimization techniques in both convergence speed and the ability in searching for parameter sets that satisfy statistical guidelines while requiring only one algorithm parameter (perturbation factor) in the optimization process. Conventionally, a default value of 0.2 is used as perturbation f ...
Handle:
10113/62883
DOI:
10.1111/1752-1688.12394
CHORUS:
10.1111/1752-1688.12394

70. Quantifying predictive uncertainty of streamflow forecasts based on a Bayesian joint probability model

Author:
Zhao, Tongtiegang; Wang, Q.J.; Bennett, James C.; Robertson, David E.; Shao, Quanxi; Zhao, Jianshi
Source:
Journal of hydrology 2015 v.528 pp. 329-340
ISSN:
0022-1694
Subject:
normal distribution,   etc   ; Bayesian theory; Markov chain; algorithms; case studies; heteroskedasticity; hydrologic data; models; prediction; stream flow; uncertainty; water management; China;     Show all 13 Subjects
Abstract:
... Uncertainty is inherent in streamflow forecasts and is an important determinant of the utility of forecasts for water resources management. However, predictions by deterministic models provide only single values without uncertainty attached. This study presents a method for using a Bayesian joint probability (BJP) model to post-process deterministic streamflow forecasts by quantifying predictive u ...
DOI:
10.1016/j.jhydrol.2015.06.043

71. A general procedure to generate models for urban environmental-noise pollution using feature selection and machine learning methods

Author:
Torija, Antonio J.; Ruiz, Diego P.
Source:
The Science of the total environment 2015 v.505 pp. 680-693
ISSN:
0048-9697
Subject:
normal distribution,   etc   ; algorithms; artificial intelligence; cities; data collection; environmental models; pollution; prediction; regression analysis; spatial variation; urban areas;     Show all 11 Subjects
Abstract:
... The prediction of environmental noise in urban environments requires the solution of a complex and non-linear problem, since there are complex relationships among the multitude of variables involved in the characterization and modelling of environmental noise and environmental-noise magnitudes. Moreover, the inclusion of the great spatial heterogeneity characteristic of urban environments seems to ...
DOI:
10.1016/j.scitotenv.2014.08.060

72. About the limit of detection in X-ray fluorescence analysis

Author:
Borkhodoev, V. Ya.
Source:
Journal of analytical chemistry 2014 v.69 no.11 pp. 1041-1046
ISSN:
1061-9348
Subject:
normal distribution,   etc   ; X-radiation; algorithms; confidence interval; detection limit; equations; fluorescence;     Show all 7 Subjects
Abstract:
... Blank experiment in X-ray fluorescence analysis is actually a measurement of the background at the analytical line of an element to be determined. Numerous factors affecting the appearance and registration of the background signal are responsible for its normal distribution. In this work, the possibility of using real samples with low analyte concentrations as blank samples is substantiated. A cri ...
DOI:
10.1134/S1061934814110021

73. Bayesian binary regression with exponential power link

Author:
Naranjo, L.; Martín, J.; Pérez, C.J.
Source:
Computational statistics & data analysis 2014 v.71 pp. 464-476
ISSN:
0167-9473
Subject:
normal distribution,   etc   ; Bayesian theory; algorithms; cumulative distribution; linear models; regression analysis;     Show all 6 Subjects
Abstract:
... A flexible Bayesian approach to a generalized linear model is proposed to describe the dependence of binary data on explanatory variables. The inverse of the exponential power cumulative distribution function is used as the link to the binary regression model. The exponential power family provides distributions with both lighter and heavier tails compared to the normal distribution, and includes t ...
DOI:
10.1016/j.csda.2012.07.022

74. A novel method for estimation of aerosol radiance and its extrapolation in the atmospheric correction of satellite data over optically complex oceanic waters

Author:
Singh, Rakesh Kumar; Shanmugam, Palanisamy
Source:
Remote sensing of environment 2014 v.142 pp. 188-206
ISSN:
0034-4257
Subject:
normal distribution,   etc   ; aerosols; algal blooms; algorithms; chlorophyll; coasts; color; methodology; remote sensing; satellites; suspended sediment; India;     Show all 12 Subjects
Abstract:
... Atmospheric correction of satellite ocean color imagery in sediment-laden and algal bloom waters remains to be a challenging task because of the inefficiency of present methods to accurately assess aerosol radiances in the near-infrared (NIR) bands and extrapolate these into the visible spectrum. This study presents a novel method for estimation and extrapolation of aerosol radiances in MODIS–Aqua ...
DOI:
10.1016/j.rse.2013.12.001

75. Bayesian Peak Picking for NMR Spectra

Author:
Cheng, Yichen; Gao, Xin; Liang, Faming
Source:
Genomics, proteomics & bioinformatics 2014 v.12 pp. 39-47
ISSN:
1672-0229
Subject:
normal distribution,   etc   ; Bayesian theory; algorithms; genomics; nuclear magnetic resonance spectroscopy; people; protein structure; protein-protein interactions;     Show all 8 Subjects
Abstract:
... Protein structure determination is a very important topic in structural genomics, which helps people to understand varieties of biological functions such as protein-protein interactions, protein–DNA interactions and so on. Nowadays, nuclear magnetic resonance (NMR) has often been used to determine the three-dimensional structures of protein in vivo. This study aims to automate the peak picking ste ...
DOI:
10.1016/j.gpb.2013.07.003
PubMed:
24184964
PubMed Central:
PMC4411369

76. Intelligent segmentation of jacquard warp-knitted fabric using a multiresolution Markov random field with adaptive weighting in the wavelet domain

Author:
Zhang, Yang; Jiang, Gaoming; Yao, Junzhou; Tong, Youcheng
ISSN:
1746-7748
Subject:
normal distribution,   etc   ; Bayesian theory; algorithms; fabrics; humans; probabilistic models; scanners; textile fibers; texture; wavelet;     Show all 10 Subjects
Abstract:
... In this paper, we propose a new approach to intelligently segment jacquard warp-knitted fabric images by combining wavelet texture decomposition, multiresolution Markov random field (MRF) modeling and Bayesian parameter estimation. Firstly, we use a flat scanner to capture eight-bit grayscale images of jacquard fabrics and adopt the Gaussian low-pass filter to decrease pixel variation due to disco ...
DOI:
10.1177/0040517513485629

77. Classification of dates varieties and effect of motion blurring on standardized moment features

Author:
Thomas, Gabriel; Manickavasagan, A.; Al-Yahyai, R.
Source:
Journal of food measurement & characterization 2012 v.6 no.1-4 pp. 21-26
ISSN:
2193-4126
Subject:
normal distribution,   etc   ; algorithms; computer vision; foods; industry; monitoring; neural networks;     Show all 7 Subjects
Abstract:
... Computer vision technology has been used as a successful non-destructive quality assessment tool for various food products. In general, several features are extracted from the images of interest, and used for the classification models. Furthermore, in most of the studies, static images have been used in the calibration and evaluation models. Classification models with a reduced number of features, ...
DOI:
10.1007/s11694-012-9129-9

78. Binary models for marginal independence Series B Statistical methodology

Author:
Drton, Mathias; Richardson, Thomas S.
Source:
Journal of the Royal Statistical Society 2008 v.70 no.2 pp. 287-309
ISSN:
1369-7412
Subject:
normal distribution,   etc   ; algorithms; linear models;     Show all 3 Subjects
Abstract:
... Log-linear models are a classical tool for the analysis of contingency tables. In particular, the subclass of graphical log-linear models provides a general framework for modelling conditional independences. However, with the exception of special structures, marginal independence hypotheses cannot be accommodated by these traditional models. Focusing on binary variables, we present a model class t ...
DOI:
10.1111/j.1467-9868.2007.00636.x

79. Burned forest characterization at single-tree level with airborne laser scanning for assessing wildlife habitat

Author:
Casas, Ángeles; García, Mariano; Siegel, Rodney B.; Koltunov, Alexander; Ramírez, Carlos; Ustin, Susan
Source:
Remote sensing of environment 2016 v.175 pp. 231-241
ISSN:
0034-4257
Subject:
normal distribution,   etc   ; snags; trees; watersheds; remote sensing; woodpeckers; coniferous forests; wildlife habitats; woodlands; conifers; Picoides; equations; models; biodiversity; algorithms; wildlife; meadows; hardwood; allometry; regression analysis; environmental health; forest management; stand basal area; Sierra Nevada (California);     Show all 24 Subjects
Abstract:
... Abundance, size, and spatial distribution of standing dead trees (snags), are key indicators of forest biodiversity and ecosystem health. These metrics represent critical habitat components for various wildlife species of conservation concern, including the Black-backed Woodpecker (Picoides arcticus), which is strongly associated with recently burned conifer forest. We assessed the potential of Ai ...
DOI:
10.1016/j.rse.2015.12.044
Chorus Open Access:
10.1016/j.rse.2015.12.044

80. Experimental Sentinel-2 LAI estimation using parametric, non-parametric and physical retrieval methods – A comparison

Author:
Verrelst, Jochem; Rivera, Juan Pablo; Veroustraete, Frank; Muñoz-Marí, Jordi; Clevers, Jan G.P.W.; Camps-Valls, Gustau; Moreno, José
Source:
ISPRS Journal of Photogrammetry and Remote Sensing 2015 v.108 pp. 260-272
ISSN:
0924-2716
Subject:
normal distribution,   etc   ; algorithms; artificial intelligence; data collection; field experimentation; heteroskedasticity; image analysis; leaf area index; models; radiative transfer; regression analysis; uncertainty; vegetation; Spain;     Show all 14 Subjects
Abstract:
... Given the forthcoming availability of Sentinel-2 (S2) images, this paper provides a systematic comparison of retrieval accuracy and processing speed of a multitude of parametric, non-parametric and physically-based retrieval methods using simulated S2 data. An experimental field dataset (SPARC), collected at the agricultural site of Barrax (Spain), was used to evaluate different retrieval methods ...
DOI:
10.1016/j.isprsjprs.2015.04.013