In this paper, vapor pressure for pure compounds is estimated using the Artificial Neural Networks and a simple Group Contribution Method (ANN–GCM). For model comprehensiveness, materials were chosen from various families. Most of materials are from 12 families. Vapor pressure data of 100 compounds is used to train, validate and test the ANN-GCM model. Va...

Leaf area index (LAI) is an important biophysical parameter and the retrieval of LAI from remote sensing data is the only feasible method for generating LAI products at regional and global scales. However, most LAI retrieval methods use satellite observations at a specific time to retrieve LAI. Because of the impacts of clouds and aerosols, the LAI products generated by these methods are spatia...

Many recent studies have used artificial neural network algorithms to model how the brain might process information. However, back-propagation learning, the method that is generally used to train these networks, is distinctly "unbiological." We describe here a more biologically plausible learning rule, using reinforcement learning, which we have applied to the problem of how area 7a in the post...

In view of the substation fire early warning using a single information sensor monitoring, it is easy to make mistakes and omissions. Taking cable in as research object, multi-information fusion prediction model based on back propagation neural network (BPNN) fuzzy set theory proposed. Firstly, BPNN trained by existing data. Secondly, artificial fish swarm algorithm (AFSA) used optimize BPNN, w...

The potential of visible and near infrared (Vis/NIR) spectroscopy was investigated for discriminating the varieties of Nanfeng mandarin fruit nondestructively. The spectra were collected by a spectrophotometer in the wavelength range of 600–1040 nm. Relationship between the spectra and Nafeng mandarin varieties was established using principal component analysis (PCA), supervised independent mod...

In its first part, this contribution reviews shortly the application of neural network methods to medical problems and characterizes its advantages and problems in the context of the medical background. Various research shows that diagnostic capabilities of human are worse than the neural network strategy to diagnose any pattern. Then paradigm of neural networks is introduced and the main probl...