To improve prediction accuracy of top-coal drawing capability in steep seams, principal component analysis (PCA) and the general regression neural network (GRNN) are combined (PCA–GRNN model) to predict seams. Nine commonly used influencing factors selected establish a predictive index system for The PCA is eliminate correlation reduce dimensions various indices, thus obtaining three linearly u...

In this brief, a new neural network model called generalized adaptive resonance theory (GART) is introduced. GART is a hybrid model that comprises a modified Gaussian adaptive resonance theory (MGA) and the generalized regression neural network (GRNN). It is an enhanced version of the GRNN, which preserves the online learning properties of adaptive resonance theory (ART). A series of empirical ...

Agricultural sector area plays major role in Indian economy. This paper shows research comparison in between MLP Feed Forward Neural Network, Generalized Regression Neural Network and Radial-Basis Function Neural Network in the field of Wheat yield prediction using Z-score Normalization method. The outcome represents that GRNN present better prediction results as compared to FFNN and RBNN. Eigh...

This paper presents the application of neural networks in software quality estimation using objectoriented metrics. In this paper, two kinds of investigation are performed. The first on predicting the number of defects in a class and the second on predicting the number of lines changed per class. Two neural network models are used, they are Ward neural network and General Regression neural netw...

We propose a new passive system for indoor localization of mobile nodes. After the setup, our system only relies on arbitrary wireless communication from the nodes, whereby neither the mobile nodes nor the communication needs to be under our control. The presented system is composed of three Artificial Neural Networks (ANN) using a radiomap approach and the Received Signal Strength (RSS) for lo...

Light-emitting Diode (LED) lamps have been widely used due to versatility and energy efficiency. However, LEDs are nonlinear loads, the massive usage will inject harmonics into lighting system, which has influenced power quality. Total Harmonic Distortion (THD) is an important parameter evaluate quality, but prediction of THD for a challenging task. This paper addresses this issue by designing ...

The ratio between nitrogen and phosphorus (N/P) in plant leaves has been widely used to assess the availability of nutrients. However, it is challenging rapidly accurately estimate leaf N/P ratio, especially for mixed forest. In this study, we collected 301 samples from nine typical karst areas Guangxi Province during growing season 2018 2020. We then utilized five models (partial least squares...

Nowadays, observing, recording, and modeling the dynamics of atmospheric pollutants represent actual study areas given effects pollution on population ecosystems. The existence aberrant values may influence reports air quality when they are based average over a period. This also models, which further used in forecasting. Therefore, correct data collection analysis is necessary before modeling. ...

This paper presents an investigation into the challenges in implementing a hard real-time optimal nonstationary system using General Regression Neural Network (GRNN). This includes investigation into the dynamics of the problem domain, discretisation of the problem domain to reduce the computational complexity, parameters selection of the optimization algorithm, convergence guarantee for real-t...