The selection of the correct model may pose substantial challenges as there may be a large number of candidate kinetic model structures. In this work, a model selection approach is presented where an Artificial Neural Network classifier is trained for recognising appropriate kinetic model structures ...
the Philosophical Background of Artificial Intelligence 1:01:35 国际基础科学大会-An Effective and Adequate Theory of Real Computation, with Applications 1:04:07 国际基础科学大会-Unbroken Center Symmetry Implies Quark Confinement: A Rigorous Proof 1:00:00 国际基础科学大会-Quantum advantage in scientific...
The study dealt with an evaluating kinetic aspect of removal of Basic Red (BR) 46 by walnut husk (WH). Artificial neural network (ANN), gene expression programming (GEP), logistic, and pseudo-second-order kinetic models were constructed to predict the removal efficiency of BR 46 on WH. ...
built tourist complex to improve energy efficiency and indoor thermal comfort, the two design goals of greatest interest to the project's designers. Some variables, such as the shape of the building's eaves, were optimized using an artificial neural network model designed to reduce calculation ...
damocles: An Erlang library for generating adversarial network conditions for QAing distributed applications/systems on a single Linux box. 🟊 eunit - This module is the main EUnit user interface. ponos: Ponos is a simple yet powerful erlang application used to generate load at configurable freq...
Blastocyst selection is primarily based on morphological scoring systems and morphokinetic data. These methods involve subjective grading and time-consuming techniques. Artificial intelligence allows for objective and quick blastocyst selection. In this study, 608 blastocysts were selected for transfer using ...
Future work would consider other machine learning and neural network models. For instance, we want to work with different types of machine learning algorithms: Support Vector Machine12, Logistic Regression21, K-Nearest Neighbor18, and neural networks models: Artificial Neural Network15, Feedforward Ne...
Artificial Intelligence for Intelligent Networked Things Front Matter Pages 1-1 Download chapterPDF Application of Improved ResNet18 Based Neural Network for Non-invasive Blood Glucose Testing Ding Wang, Yingnian Wu, Hao Tan, Meiqi Sheng, Rui Yang, Rongmin Cao et al. ...
In particular, the lever movement was estimated using a combination of principal components analysis and an artificial neural network. The researchers found that rats could still control the lever to receive their reward. Animals soon learned that actual forelimb movement was not needed and stopped ...
LED spectrum resulted in faster biomass growth as compared to binary-coded GA. Interestingly, anArtificial Neural Network(ANN) with one hidden layer composed of three neurons with tangent activation function has been applied to improve the higher heating value prediction of biomass based on carbon, ...