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In this study, we have developed Support Vector Machine (SVM) based models for prediction of drug-like molecules using SVMlight software package.
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In this study, an artificial neural network (ANN) based model for prediction of solar energy potential in Nigeria (lat. 4 14°N, log. 2 15°E) was developed.
Mycielski algorithm is a novel and effective approach alternative to statistical or artificial intelligence based models for wind speed prediction.
This points to the utility of constraint based models for making detailed functional predictions based on genome content, as well as the importance of correct genome annotation.
We present an Artificial Neural Network based model for the prediction of cold rolling textures of steels.
An analytical semi-laminar based model for strength prediction of NCF composite laminates loaded in compression is then suggested.
This paper presents a feasibility study for the development of a Neural Network (NN) based model for the prediction of South African GPS derived TEC.
This paper presents part of a feasibility study for the development of a Neural Network (NN) based model for the prediction of South African GPS derived TEC.
This paper presents a feasibility study into the development of a NN based model for the prediction of the probability of occurrence of spread-F over selected equatorial stations within the Brazilian sector.
Starting from this consideration, we propose here to transform this latter model into a robust physically based model for the prediction of the stiffness modulus for a wide range of temperatures and frequencies/strain rates.
CE contributed towards the general framework of the proposed prediction based model for image compression.
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Justyna Jupowicz-Kozak
CEO of Professional Science Editing for Scientists @ prosciediting.com