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Research On Knowledge Sublimation In The Marine Drug R&D Based On Knowledge Mining

Posted on:2011-08-03Degree:MasterType:Thesis
Country:ChinaCandidate:Y Y PanFull Text:PDF
GTID:2189330332464566Subject:Management Science and Engineering
Abstract/Summary:PDF Full Text Request
With the reduction of land resources, marine economy has become a new growth point of world economic. Marine drug discovery is paid more and more attention. And competition has intensified. China must accelerate the development of new products to catch up with international level of marine drug R&D.Marine drug R&D is knowledge-intensive industry. It can explore new knowledge relying on knowledge management, and use appropriate means to stimulate generating more important and higher level knowledge during the R&D process. Completing knowledge sublimation accelerates the speed of new product R&D.This thesis integrates theories of knowledge management, marine bio-pharmaceutical, evolutionary algorithms and artificial neural network, and then does the research on knowledge sublimation in the process of marine drug R&D on the basis of existing research results at home and abroad. First of all, through the survey on basic research of the lab in Ocean University of China, decompose the process of drug R&D according to an instance, analyze the transformation of knowledge in R&D, summarize the model of knowledge sublimation, and analyze the factors which leads to knowledge sublimation. According to the theory of knowledge evolution, explore knowledge mining method for specific issues in marine drug R&D, and then determine the real-coded genetic algorithm. For unresolved issues,propose using artificial neural networks and genetic algorithms for knowledge mining.Through the establishment of BP network, write genetic algorithm programs to do empirical analysis to the fermentation of the marine drug R&D,guiding the knowledge sublimation. Finally, analyze and prospect the knowledge sublimation of marine drug R&D, summarize knowledge mining methods, and propose the strategies and recommendations on controlling knowledge sublimation.Through research, this thesis obtains the following findings and conclusions:(1)From the perspective of knowledge transfer for the first time,and using the theories of knowledge management, marine bio-pharmaceutics and evolutionary algorithms, knowledge sublimation in the marine drug R&D is deeply studied and research ideas on exchange of multi-disciplinary and complementary of multi-disciplinary is developed.(2) Combined with an example of marine drug R&D,based on the related theories of knowledge management and marine bio-pharmacy, the process of knowledge transferring is cleared, the concept of knowledge sublimation is defined, and according the characteristics of knowledge sublimation, the factors affecting knowledge sublimation are determined, then knowledge sublimation bionic model and knowledge sublimation formula in marine drug R&D are built.(3)Using knowledge mining as a method, a large number of R&D knowledge is mined, rules and knowledge at a higher level is discovered, and knowledge sublimation is promoted.(4) With the evolutionary algorithm of knowledge and its own characteristics of knowledge sublimation in marine drug R&D,overcome the difficulties in knowledge sublimation, the GA combined with ANN as a method of knowledge mining is explored, and the general steps of knowledge mining are introduced.(5) Using MATLAB software simulating the method of knowledge mining, and using BP network combined with GA, the best composition ratio of the GSH fermentation medium is discovered successfully to verify the feasibility of the method.(6) Through the empirical study, knowledge mining applied to all aspects of marine drug R&D,the knowledge difficult to find in the R&D process can be found,the guidelines for the correct direction are developed, and the rate of knowledge sublimation is speeded up.It is beneficial to new marine drugs discovery.
Keywords/Search Tags:marine drug R&D, knowledge sublimation, knowledge mining, GA, ANN
PDF Full Text Request
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