CAJ | 학술논문

通过挖掘生物信息大数据,从生物信息大数据库中提取感兴趣的数据特征,分析生物信息大数据集的细节结构,提高对生物信息的采集、处理、存储、传播,分析能力.传统的生物信息大数据挖掘模型采用基于小波多窗谱提取的生物信息挖掘算法,由于生物特征的属性权重需求各异,数据挖掘精度不高,提出一种基于梯度采样局部收敛的生物信息大数据挖掘模型.首先构建生物信息大数据库模型和生物信息特征挖掘实体模型,采用提取采样局部收敛方法实现对数据挖掘模型的改进,通过求解最优输入控制序列以及索引系统最优目标函数,实现系统的控制输入和预测,使用梯度采样局部收敛的方法进行生物信息大数据挖掘检测,得到生物信息大数据的梯度采样局部收敛属性集合.仿真结果表明,能实时准确地实现对生物信息的储存、检索和分析,提高数据挖掘能力,收敛精度较高.
통과알굴생물신식대수거,종생물신식대수거고중제취감흥취적수거특정,분석생물신식대수거집적세절결구,제고대생물신식적채집、처리、존저、전파,분석능력.전통적생물신식대수거알굴모형채용기우소파다창보제취적생물신식알굴산법,유우생물특정적속성권중수구각이,수거알굴정도불고,제출일충기우제도채양국부수렴적생물신식대수거알굴모형.수선구건생물신식대수거고모형화생물신식특정알굴실체모형,채용제취채양국부수렴방법실현대수거알굴모형적개진,통과구해최우수입공제서렬이급색인계통최우목표함수,실현계통적공제수입화예측,사용제도채양국부수렴적방법진행생물신식대수거알굴검측,득도생물신식대수거적제도채양국부수렴속성집합.방진결과표명,능실시준학지실현대생물신식적저존、검색화분석,제고수거알굴능력,수렴정도교고.
Through mining large data of biological information, data and to extract the features of interest from large databas-es of biological information in detail, data mining accuracy is not high, this paper brings forward a mining model of biologi-cal information high data sampling based on gradient local convergence. The first construction of biological information and biological information of large database model feature mining entity model, using sampling local convergence method to re-alize the improvement of the data mining model, by solving the optimal control input sequence and the optimal target index system function, realization of control input and prediction system and method using gradient sampling the local conver-gence of data mining large biological information detection get a large gradient of biological information, data sampling lo-cal convergence property collection. The simulation results show that, real timely and accurately realize the analysis of bio-logical information storage, retrieval and data mining, improve ability, it has high precision.