Assessing predictability of environmental time series with statistical and machine learning models
Sign Up to like & getrecommendations! Published in 2024 at "Environmetrics"
DOI: 10.1002/env.2864
Abstract: The ever increasing popularity of machine learning methods in virtually all areas of science, engineering and beyond is poised to put established statistical modeling approaches into question. Environmental statistics is no exception, as popular constructs… read more here.
Keywords: time series; machine; statistical machine; machine learning ... See more keywords
Statistical and Machine Learning Approaches for Electrical Energy Forecasting
Sign Up to like & getrecommendations! Published in 2025 at "Wiley Interdisciplinary Reviews: Data Mining and Knowledge Discovery"
DOI: 10.1002/widm.70033
Abstract: With renewable energy being aggressively integrated into the grid, energy supplies are becoming vulnerable to weather and the environment, and are often incapable of meeting population demands at a large scale if not accurately predicted… read more here.
Keywords: energy; machine learning; prediction; energy prediction ... See more keywords
Statistical machine translation of Indian languages: a survey
Sign Up to like & getrecommendations! Published in 2017 at "Neural Computing and Applications"
DOI: 10.1007/s00521-017-3206-2
Abstract: In this study, performance analysis of a state-of-art phrase-based statistical machine translation (SMT) system is presented on eight Indian languages. State of the art in SMT on different Indian languages to English language has also… read more here.
Keywords: machine translation; indian languages; statistical machine; study ... See more keywords
Extreme Learning Machine for Huge Hypotheses Re-ranking in Statistical Machine Translation
Sign Up to like & getrecommendations! Published in 2017 at "Cognitive Computation"
DOI: 10.1007/s12559-017-9452-x
Abstract: In statistical machine translation (SMT), a possibly infinite number of translation hypotheses can be decoded from a source sentence, among which re-ranking is applied to sort out the best translation result. Undoubtedly, re-ranking is an… read more here.
Keywords: machine; classification; statistical machine; extreme learning ... See more keywords
Comparing shallow landslide susceptibility maps in Northeastern Türkiye (Beşikdüzü, Trabzon): a multivariate statistical, machine learning, and physical data-based analysis
Sign Up to like & getrecommendations! Published in 2024 at "Environmental Earth Sciences"
DOI: 10.1007/s12665-024-11627-w
Abstract: This study endeavors to assess and compare the efficacy of various modeling approaches, including statistical, machine learning, and physical-based models, in the creation of shallow landslide susceptibility maps within the Besikduzu district of Trabzon province,… read more here.
Keywords: susceptibility maps; susceptibility; landslide susceptibility; shallow landslide ... See more keywords
Use statistical machine learning to detect nutrient thresholds in Microcystis blooms and microcystin management.
Sign Up to like & getrecommendations! Published in 2020 at "Harmful algae"
DOI: 10.1016/j.hal.2020.101807
Abstract: The frequency of toxin-producing cyanobacterial blooms has increased in recent decades due to nutrient enrichment and climate change. Because Microcystis blooms are related to different environmental conditions, identifying potential nutrient control targets can facilitate water… read more here.
Keywords: microcystis blooms; microcystis; use statistical; statistical machine ... See more keywords
Accuracy and explainability of statistical and machine learning xG models in football
Sign Up to like & getrecommendations! Published in 2024 at "Statistics"
DOI: 10.1080/02331888.2024.2445305
Abstract: This study aims to propose an original approach to the interpretability of the explanatory variables (features) in the well-known expected goals (xG) model for shot analysis in football. To do this, a new original sample… read more here.
Keywords: football; accuracy explainability; statistical machine; machine learning ... See more keywords
Analyzing adverse drug reaction using statistical and machine learning methods
Sign Up to like & getrecommendations! Published in 2022 at "Medicine"
DOI: 10.1097/md.0000000000029387
Abstract: Abstract Background: Adverse drug reactions (ADRs) are unintended negative drug-induced responses. Determining the association between drugs and ADRs is crucial, and several methods have been proposed to demonstrate this association. This systematic review aimed to… read more here.
Keywords: machine; machine learning; statistical machine; adverse drug ... See more keywords
Statistical Machine Learning Model for Stochastic Optimal Planning of Distribution Networks Considering a Dynamic Correlation and Dimension Reduction
Sign Up to like & getrecommendations! Published in 2020 at "IEEE Transactions on Smart Grid"
DOI: 10.1109/tsg.2020.2974021
Abstract: Distributed generation and reactive power resource allocation will affect the economy and security of distribution networks. Deterministic scenario planning cannot solve the problem of network uncertainties, which are introduced by intermittent renewable generators and a… read more here.
Keywords: optimal planning; statistical machine; distribution networks; model ... See more keywords
Statistical and machine learning methods for spatially resolved transcriptomics data analysis
Sign Up to like & getrecommendations! Published in 2022 at "Genome Biology"
DOI: 10.1186/s13059-022-02653-7
Abstract: The recent advancement in spatial transcriptomics technology has enabled multiplexed profiling of cellular transcriptomes and spatial locations. As the capacity and efficiency of the experimental technologies continue to improve, there is an emerging need for… read more here.
Keywords: spatially resolved; methods spatially; machine learning; learning methods ... See more keywords
Predicting cow milk quality traits from routinely available milk spectra using statistical machine learning methods.
Sign Up to like & getrecommendations! Published in 2021 at "Journal of dairy science"
DOI: 10.3168/jds.2020-19576
Abstract: Numerous statistical machine learning methods suitable for application to highly correlated features, as those that exist for spectral data, could potentially improve prediction performance over the commonly used partial least squares approach. Milk samples from… read more here.
Keywords: milk; machine learning; statistical machine; regression ... See more keywords