Results 51 to 60 of about 12,139 (206)
Energies, 2018 Thermal load and indoor comfort level are two important building performance indicators, rapid predictions of which can help significantly reduce the computation time during design optimization. In this paper, a three-step approach is used to develop and
Yaolin Lin +4 more
doaj +1 more source
Learning Graphical Models Using Multiplicative Weights
, 2017 We give a simple, multiplicative-weight update algorithm for learning undirected graphical models or Markov random fields (MRFs). The approach is new, and for the well-studied case of Ising models or Boltzmann machines, we obtain an algorithm that uses a
Klivans, Adam, Meka, Raghu
core +1 more source
Modeling Properties with Artificial Neural Networks and Multilinear Least-Squares Regression: Advantages and Drawbacks of the Two Methods [PDF]
Applied Sciences, 2018 The mean molecular connectivity indices (MMCI) proposed in previous studies are used in conjunction with well-known molecular connectivity indices (MCI) to model eleven properties of organic solvents. The MMCI and MCI descriptors selected by the stepwise multilinear least-squares (MLS) procedure were used to perform artificial neural network (ANN ...
Jesus Vicente De Julián-Ortiz +2 more
openaire +4 more sources
Journal of Chemical Technology &Biotechnology, EarlyView.Abstract BACKGROUND Parabens, including butylparaben (BP), are widely used as antimicrobial preservatives in food, cosmetics, and pharmaceuticals, yet are poorly removed by conventional water treatment processes and pose potential risks to aquatic life and human health.
Lorena Maihury Santos Tsubouchi +8 more
wiley +1 more source
Predicting Slope Stability Failure through Machine Learning Paradigms
ISPRS International Journal of Geo-Information, 2019 In this study, we employed various machine learning-based techniques in predicting factor of safety against slope failures. Different regression methods namely, multi-layer perceptron (MLP), Gaussian process regression (GPR), multiple linear regression ...
Dieu Tien Bui +4 more
doaj +1 more source
Estimation of the recharging rate of groundwater using random forest technique
Applied Water Science, 2020 Accurate knowledge of the recharging rate is essential for several groundwater-related studies and projects mainly in the water scarcity regions. In this study, a comparison between different methods of soft computing-based models was obtained in order ...
Parveen Sihag +2 more
doaj +1 more source
Calibration and Validation of a Measurements-Independent Model for Road Traffic Noise Assessment
Applied Sciences, 2023 The assessment of road traffic noise is very important for the health of people living in urban areas. Noise is usually assessed by field measurements, and predictive models play an important role when experimental data are not available.
Domenico Rossi +2 more
doaj +1 more source
Self-Learning Determinantal Quantum Monte Carlo Method [PDF]
, 2016 Self-learning Monte Carlo method [arXiv:1610.03137, 1611.09364] is a powerful general-purpose numerical method recently introduced to simulate many-body systems. In this work, we implement this method in the framework of determinantal quantum Monte Carlo
Fu, Liang +4 more
core +3 more sources
Movement Disorders, EarlyView.Abstract Background Blood–brain barrier disruption is increasingly recognized in synucleinopathies, but the role of the endothelial glycocalyx (GLX) in Parkinson's disease (PD) and multiple system atrophy (MSA) remains unclear. Objectives The aim was to determine whether plasma GLX markers differ between PD, MSA, and healthy controls (HC), relate to ...
Jonas Folke +15 more
wiley +1 more source
Discussion on common errors in analyzing sea level accelerations, solar trends and global warming
, 2013 Errors in applying regression models and wavelet filters used to analyze geophysical signals are discussed: (1) multidecadal natural oscillations (e.g.
Scafetta, Nicola
core +1 more source