MATHEMATICAL MODELING AND SIMULATION MECHANISM OF GENETICS BEHAVIOR TOGETHER WITH NEURAL FUZZY SYSTEM

摘要

Many studies have used different types of mathematical modeling and simulation in solving examination genetics behavior problem. The solutions of the genetics behavior are found to be efficient and reliable with neural fuzzy system. This paper provides a comprehensive study of genetics behavior problem. This study is frequently robust or even difficult to get accurate information regarding genetics behavior. Here, we exhibit a model of quantitative fuzzy rationale demonstrating approach that can adapt to obscure motor information and hence deliver applicable results despite the fact that dynamic information are fragmented or just dubiously characterized. Fuzzy Petri nets (FPNs) gives a graphically and scientific system that is good with ineffectively quantitative yet subjectively huge information. All of genes regulatory networks (GRNs) quests depend on fresh and parametric qualities, in spite of innate fuzzy nature of quality expression. In the proposed display, a quality expression profile is initially changed into a mapping structure and afterward the changed information are mapped into the fuzzy framework. The models of FNPN are characterized in view of creating tenets of information base and the FPN semantics depiction of legitimate principles are displayed. Since the relations are spoken to by fuzzy method, the invented strategy is powerful to uproarious and questionable data. FNPN to speak to the dynamic information on the base of learning representation with self-learning capacity.