Artificial Neural Network Method Based on Expert Knowledge and Its Application to Quantitative Identification of Potential Seismic Sources

In this paper,an approach is developed to optimize the quality of the training samples in the conventional Artificial Neural Network(ANN)by incorporating expert knowledge in the means of constructing expert-rule samples from rules in an expert system,and through training by using these samples,an ANN based on expert-knowledge is further developed.The method is introduced into the field of quantitative identification of potential seismic sources on the basis of the rules in an expert system.Then it is applied to the quantitative identification of the potential seismic sources in Beijing and its adjacent area.The result indicates that the expert rule based on ANN method can well incorporate and represent the expert knowledge in the rules in an expert system,and the quality of the samples and the efficiency of training and the accuracy of the result are optimized.

A Statistical Analysis of Protein-Protein Interaction with Knowledge-Based Potential at Residue Level

Protein protein recognition is an important step in biological processes, which still largely remains elusive. The inter residue contact potential, CP ij , describes the propensity of contact between two types of residue. In this study, several different CP ij variants were examined with the objective of discriminating the binding potential of surface pairs. Using solvent mediated inter molecule contact potential (SM IMCP ij ), an evaluation model was deduced and tested. Using the evaluation model it was found that the SM IMCP ij gives a better performance than either residue mediated IMCP ij (RM IMCP ij ) or folding residue contact potential (FCP ij ). The results suggest that the evaluation model provides a fast, effective, and discriminative method for the evaluation of proposed binding interfaces.

Research on identification of potential knowledge growth points in information science

The scientific system’s complexity makes it impossible to solve social problems by a single discipline independently,and interdisciplinary knowledge cooperation and innovation become an indispensable research mode of modern science.Identifying the potential interdisciplinary knowledge association is the key to promoting interdisciplinary cooperation.In this paper,based on analyzing the growth points of science,"knowledge growth point"is defined as the growth point of science that produces new knowledge,and its fundamental attributes and evaluation indexes have been analyzed.In contrast,the"interdisciplinary knowledge growth point"is defined as the introduction of related interdisciplinary concepts,theories,techniques,and methods,to conduct integrated research of key knowledge points of active disciplines,to generate growth point of innovative knowledge,and analyze its related research status.The identification of"potential interdisciplinary knowledge growth points"is helpful to promote knowledge innovation.Therefore,it is intended to analyze the identification methods of the generation of key knowledge nodes of the element of disciplines and interdisciplinary related knowledge,and explore quantitative and qualitative consultation to identify potential interdisciplinary knowledge growth points.