Validation of linear, nonlinear, and hybrid models for predicting particulate matter concentration in Tehran, Iran
Sign Up to like & getrecommendations! Published in 2020 at "Theoretical and Applied Climatology"
DOI: 10.1007/s00704-020-03115-5
Abstract: Information on particulate matter forecast is significant as it allows residents to manage its undesirable effects. For the purpose of predicting PM 10 concentration in the air of Tehran, various models were used, including (i)… read more here.
Keywords: linear nonlinear; hybrid models; tehran; concentration ... See more keywords
Comparison of three hybrid models to simulate land use changes: a case study in Qeshm Island, Iran
Sign Up to like & getrecommendations! Published in 2020 at "Environmental Monitoring and Assessment"
DOI: 10.1007/s10661-020-08274-6
Abstract: Land use change simulation is an important issue for its role in predicting future trends and providing implications for sustainable land management. Hybrid models have become a recognized strategy to inform decision-makers, but further attempts… read more here.
Keywords: hybrid models; simulate land; land; island ... See more keywords
Sequence in Hybridization of Statistical and Intelligent Models in Time Series Forecasting
Sign Up to like & getrecommendations! Published in 2020 at "Neural Processing Letters"
DOI: 10.1007/s11063-020-10294-9
Abstract: With the importance of forecasting with a high degree of accuracy, the increasing attention has been evolved to combine individual models, especially statistical and intelligent ones. The main aim of such that hybrid models is… read more here.
Keywords: time series; series forecasting; hybrid models; series ... See more keywords
Specific chemical exergy prediction for biological molecules using hybrid models
Sign Up to like & getrecommendations! Published in 2021 at "Chemical Engineering Science"
DOI: 10.1016/j.ces.2021.116462
Abstract: Abstract In this study, hybrid models for specific chemical exergy prediction were proposed for pure organic compounds. The models were designed from the relation between the compounds standard molar chemical exergy and the reaction Gibbs… read more here.
Keywords: hybrid models; exergy prediction; exergy; chemical exergy ... See more keywords
Artificial intelligence-based single and hybrid models for prediction of water quality in rivers: A review
Sign Up to like & getrecommendations! Published in 2020 at "Chemometrics and Intelligent Laboratory Systems"
DOI: 10.1016/j.chemolab.2020.103978
Abstract: Abstract The need for accurate predictions of water quality in rivers has encouraged researchers to develop new methods and to improve the predictive ability of conventional models. In recent years, artificial intelligence (AI)-based methods have… read more here.
Keywords: hybrid models; water; single hybrid; water quality ... See more keywords
A less data demanding ecophysiological niche modeling approach for mammals with comparison to conventional correlative niche modeling
Sign Up to like & getrecommendations! Published in 2021 at "Ecological Modelling"
DOI: 10.1016/j.ecolmodel.2021.109687
Abstract: Abstract Ecophysiological models are more data demanding and, consequently, less used than correlative ecological niche models to predict species’ distribution under climate change, especially for endotherms. Hybrid models that integrate both approaches are even less… read more here.
Keywords: hybrid models; approach; niche modeling; data demanding ... See more keywords
A theorem on a product of lognormal variables and hybrid models for children's exposure to soil contaminants.
Sign Up to like & getrecommendations! Published in 2020 at "Environmental pollution"
DOI: 10.1016/j.envpol.2020.114393
Abstract: This study developed hybrid Bayesian models to investigate the modeling process for children's exposure to soil contaminants, which involves the intrinsic uncertainty of the exposure model, people's judgments regarding random variables, and limited data resources.… read more here.
Keywords: hybrid models; exposure soil; hybrid bayesian; children exposure ... See more keywords
Quantifying the Optimal Structure of the Autism Phenotype: A Comprehensive Comparison of Dimensional, Categorical, and Hybrid Models.
Sign Up to like & getrecommendations! Published in 2018 at "Journal of the American Academy of Child and Adolescent Psychiatry"
DOI: 10.1016/j.jaac.2018.09.431
Abstract: OBJECTIVE The two primary - seemingly contradictory - strategies for classifying child psychiatric syndromes are categorical and dimensional; conceptual ambiguities appear to be greatest for polythetic syndromes such as autism spectrum disorder (ASD). Recently, a… read more here.
Keywords: quantifying optimal; optimal structure; hybrid models; categorical dimensional ... See more keywords
Accuracy Assessment of Single and Hybrid Models for Predicting Shale Gas Production
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DOI: 10.1021/acs.energyfuels.0c04135
Abstract: The accuracy of a predictive tool determines the levels of trust in the model and its attraction for commercial usage. The study examined the single and hybrid model approach for shale gas producti... read more here.
Keywords: hybrid models; shale gas; assessment single; single hybrid ... See more keywords
Hybrid models for global solar radiation prediction: a case study
Sign Up to like & getrecommendations! Published in 2020 at "International Journal of Ambient Energy"
DOI: 10.1080/01430750.2018.1443498
Abstract: ABSTRACT This paper presents a comparison between different prediction models for solar radiation application. The present study assessed the performance of multi-layer perceptron (MLP) as well as boosted decision tree, and used a new combinition… read more here.
Keywords: hybrid models; global solar; solar radiation; study ... See more keywords
A training strategy for hybrid models to break the curse of dimensionality
Sign Up to like & getrecommendations! Published in 2022 at "PLoS ONE"
DOI: 10.1371/journal.pone.0274569
Abstract: Mechanistic/data-driven hybrid modeling is a key approach when the mechanistic details of the processes at hand are not sufficiently well understood, but also inferring a model purely from data is too complex. By the integration… read more here.
Keywords: training strategy; hybrid models; strategy hybrid; strategy ... See more keywords