QSPR Studies for Solubility Parameter by Means of Genetic Algorithm-Based Multivariate Linear Regression and Generalized Regression Neural Network

Objectives: At present, quality education has gradually been recognized by the whole society, and a consensus has been reached on its importance, which has put forward stricter requirements for the distribution of faculty in universities. Methods: In this paper, based on neuropsychology, the distribution of teaching staff in colleges and universities was studied, and the model of talent evaluation and distribution was constructed. Results: Firstly, the generalized regression neural network was optimized by genetic algorithm. Then, the genetic algorithm’s generalized regression neural network calculation process was designed. Conclusion: Finally, with the example of teacher resources in a university, the algorithm in this paper was tested. The results show that the results of the generalized regression neural network optimized by genetic algorithm can match the actual situation very well, and the method is feasible with certain advantages.

Download Full-text

Study on State Identifying of Rotary Machine Torsional Oscillation Based on Wavelet Neural Network

Applied Mechanics and Materials ◽

10.4028/www.scientific.net/amm.26-28.211 ◽

2010 ◽

Vol 26-28 ◽

pp. 211-217

Author(s):

Zong Meng ◽

Feng Jie Fan ◽

Bin Liu

Keyword(s):

Neural Network ◽

Genetic Algorithm ◽

Linear Regression ◽

Regression Model ◽

Linear Regression Model ◽

Torsional Oscillation ◽

Wavelet Neural Network ◽

Multivariate Linear Regression ◽

Multivariate Linear Regression Model ◽

Rotary Machine

This article established a new combining hierarchy genetic algorithm and multivariate linear regression model of WNN (wavelet neural network) for identify the feature of rotary machine. The effection on the question of nonlinear approximation is verified through the simulation and optimization. The test datas of a tandem mill are inputted into the model. After trained, the model has automatic ability of obtained the inspect information and the ability of adapt the changing of worked condition. The self-adaptive study and diagnosis of torsional oscillation state on different work condition are realized. The results verify the combining hierarchy genetic algorithm and multivariate linear regression model has the reliability.

Download Full-text

Optimization of optical lens-controlled scanning electron microscopic resolution using generalized regression neural network and genetic algorithm

Expert Systems with Applications ◽

10.1016/j.eswa.2009.05.007 ◽

2010 ◽

Vol 37 (1) ◽

pp. 182-186 ◽

Cited By ~ 12

Author(s):

Byungwhan Kim ◽

Sanghee Kwon ◽

Dong Hwan Kim

Keyword(s):

Neural Network ◽

Genetic Algorithm ◽

Generalized Regression Neural Network ◽

Electron Microscopic ◽

Optical Lens ◽

Scanning Electron Microscopic ◽

Generalized Regression ◽

Scanning Electron

Download Full-text

An approach to carbon emissions prediction using generalized regression neural network improved by genetic algorithm

Electrical Science & Engineering ◽

10.30564/ese.v2i1.1772 ◽

2020 ◽

Vol 2 (1) ◽

Author(s):

Zhida Guo ◽

Jingyuan Fu

Keyword(s):

Neural Network ◽

Carbon Dioxide ◽

Genetic Algorithm ◽

Carbon Emissions ◽

Carbon Dioxide Emissions ◽

Total Carbon ◽

Generalized Regression Neural Network ◽

Improved Method ◽

Target Values ◽

Generalized Regression

The study on scientific analysis and prediction of China’s future carbon emissions is conducive to balancing the relationship between economic development and carbon emissions in the new era, and actively responding to climate change policy. Through the analysis of the application of the generalized regression neural network (GRNN) in prediction, this paper improved the prediction method of GRNN. Genetic algorithm (GA) was adopted to search the optimal smooth factor as the only factor of GRNN, which was then used for prediction in GRNN. During the prediction of carbon dioxide emissions using the improved method, the increments of data were taken into account. The target values were obtained after the calculation of the predicted results. Finally, compared with the results of GRNN, the improved method realized higher prediction accuracy. It thus offers a new way of predicting total carbon dioxide emissions, and the prediction results can provide macroscopic guidance and decision-making reference for China’s environmental protection and trading of carbon emissions.

Download Full-text