Comprehensive Evaluation Model for Academic Quality of Food Journals Based on Rough Set and Neural Networ

Abstract

In order to evaluate food journals efficiently and reasonably, this study puts forward a comprehensive evaluation model for academic quality of food journals based on rough set and neural network. Firstly, we reduce evaluation indicators of journals based on discernibility matrix in rough set theory, removing the miscellaneous indicators and form the core evaluation indicator system, so as to have a more effective training for BP neural network. Then, we use methods defined in our study to generate enough training samples for the neural network modeling based on the core evaluation system. Lastly, with the help of BP neural network algorithm to rank journals, thereby we establish a comprehensive evaluation model for academic quality of journal. Instance analysis of food journals shows that the principle of generating the sample is feasible and effective and the modeling process is reliable and reasonable. What' more, the model established can be used for comprehensive evaluation for academic quality of food journals.

Optimization of Online Teaching Quality Evaluation Model Based on Hierarchical PSO-BP Neural Network

“…Quality on the Line evaluation criteria based on Internet distance learning: the evaluation standard includes seven first-level indicators, namely, architecture, curriculum development, teaching and learning, curriculum structure, student support system, teacher support system, and evaluation and evaluation system [8,9]. In addition, the first-level indexes are divided into two parts: the necessary indexes for each online course evaluation and the optional indexes that can be independently selected and expressed according to different evaluation needs, which are further refined into 24 second-level necessary indexes and 21 second-level optional indexes [10,11], so as to make the evaluation standard more flexible and instructive. At the same time, it also provides a case study report on the evaluation of online courses in six schools using this evaluation standard.…”