A multi-objective hybrid machine learning approach-based optimization for enhanced biomass and bioactive phycobiliproteins production in Nostoc sp. CCC-403.
Sign Up to like & getrecommendations! Published in 2021 at "Bioresource technology"
DOI: 10.1016/j.biortech.2021.124908
Abstract: The cyanobacterial phycobiliproteins (PBPs) are an important natural colorant for nutraceutical industries. Here, a multi-objective hybrid machine learning-based optimization approach was used for enhanced cell biomass and PBPs production simultaneously in Nostoc sp. CCC-403. A… read more here.
Keywords: machine learning; production; optimization; approach ... See more keywords
Flocculation-dewatering prediction of fine mineral tailings using a hybrid machine learning approach.
Sign Up to like & getrecommendations! Published in 2019 at "Chemosphere"
DOI: 10.1016/j.chemosphere.2019.125450
Abstract: Polymer-assisted flocculation-dewatering of mineral processing tailings (MPT) is crucial for its environmental disposal. To reduce the number of laboratory experiments, this study proposes a novel and hybrid machine learning (ML) method for the prediction of… read more here.
Keywords: hybrid machine; machine learning; flocculation dewatering; prediction ... See more keywords
Hybrid machine intelligent SVR variants for wind forecasting and ramp events
Sign Up to like & getrecommendations! Published in 2019 at "Renewable and Sustainable Energy Reviews"
DOI: 10.1016/j.rser.2019.04.002
Abstract: Abstract Wind speed and power forecast is an essential component to ensure grid stability and reliability. The traditional forecasting methods fail to address the non-linearity in the wind speed time-series, thus paving way for machine… read more here.
Keywords: machine; svr; machine intelligent; ramp events ... See more keywords
Food Product Design: A Hybrid Machine Learning and Mechanistic Modeling Approach
Sign Up to like & getrecommendations! Published in 2019 at "Industrial & Engineering Chemistry Research"
DOI: 10.1021/acs.iecr.9b02462
Abstract: At present, food products are designed by trial and error and the sensorial ratings are determined by a tasting panel. To expedite the development of new food products, a hybrid machine learning and mechanistic modeling… read more here.
Keywords: machine learning; approach; hybrid machine; food ... See more keywords
A Hybrid Machine Learning Approach for Structure Stability Prediction in Molecular Co-crystal Screenings
Sign Up to like & getrecommendations! Published in 2022 at "Journal of Chemical Theory and Computation"
DOI: 10.1021/acs.jctc.2c00343
Abstract: Co-crystals are a highly interesting material class as varying their components and stoichiometry in principle allows tuning supramolecular assemblies toward desired physical properties. The in silico prediction of co-crystal structures represents a daunting task, however,… read more here.
Keywords: hybrid machine; structure; prediction; stability ... See more keywords
Projecting Large Fires in the Western US With an Interpretable and Accurate Hybrid Machine Learning Method
Sign Up to like & getrecommendations! Published in 2024 at "Earth's Future"
DOI: 10.1029/2024ef004588
Abstract: More frequent and widespread large fires are occurring in the western United States (US), yet reliable methods for predicting these fires, particularly with extended lead times and a high spatial resolution, remain challenging. In this… read more here.
Keywords: accurate hybrid; large fires; interpretable accurate; model ... See more keywords
Exploring Optimal Complexity for Water Stress Representation in Terrestrial Carbon Models: A Hybrid‐Machine Learning Model Approach
Sign Up to like & getrecommendations! Published in 2024 at "Journal of Advances in Modeling Earth Systems"
DOI: 10.1029/2024ms004308
Abstract: Terrestrial biosphere models offer a comprehensive view of the global carbon cycle by integrating ecological processes across scales, yet they introduce significant uncertainties in climate and biogeochemical projections due to diverse process representations and parameter… read more here.
Keywords: carbon; water; machine learning; model ... See more keywords
Uncovering of intraspecies macular heterogeneity in cynomolgus monkeys using hybrid machine learning optical coherence tomography image segmentation
Sign Up to like & getrecommendations! Published in 2021 at "Scientific Reports"
DOI: 10.1038/s41598-021-99704-z
Abstract: The fovea is a depression in the center of the macula and is the site of the highest visual acuity. Optical coherence tomography (OCT) has contributed considerably in elucidating the pathologic changes in the fovea… read more here.
Keywords: optical coherence; image; machine learning; cynomolgus monkeys ... See more keywords
A hybrid machine learning approach for congestion prediction and warning
Sign Up to like & getrecommendations! Published in 2024 at "Transportation Planning and Technology"
DOI: 10.1080/03081060.2024.2367751
Abstract: ABSTRACT Global traffic management encounters a significant challenge in traffic congestion. This paper presents a hybrid machine learning method for predicting traffic congestion. It leverages Convolutional Neural Network-Gated Recurrent Unit (CNN-GRU) network for parameter prediction… read more here.
Keywords: congestion; machine learning; prediction; hybrid machine ... See more keywords
Hybrid Machine Learning Scheme for Classification of BECTS and TLE Patients Using EEG Brain Signals
Sign Up to like & getrecommendations! Published in 2020 at "IEEE Access"
DOI: 10.1109/access.2020.3038948
Abstract: Approximately 50 million people have epilepsy worldwide. Prognosis may vary among patients depending on their seizure semiology, age of onset, seizure onset location, and features of electroencephalogram (EEG). Several researchers have focused on EEG patterns… read more here.
Keywords: machine; classification; model; hybrid machine ... See more keywords
A Cylindrical Linear Permanent Magnet Vernier Hybrid Machine for Wave Energy
Sign Up to like & getrecommendations! Published in 2019 at "IEEE Transactions on Energy Conversion"
DOI: 10.1109/tec.2018.2879405
Abstract: In some wave energy converters, there is a need for linear electrical machines where all the active parts are mounted on the stator. For this reason the linear Vernier hybrid machine has been investigated. In… read more here.
Keywords: hybrid machine; wave energy; vernier hybrid;