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支持偏好调控的线性递归查询的数学建模

Mathematical Modeling of Linear Recursive Query for Supporting Preference Regulation
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摘要 为了解决传统查询的数学建模方法,由于忽视支持偏好对调控能力的影响程度,令模型的渐进正态性不佳,导致查询模型的反馈效果较差的问题,提出支持偏好调控的线性递归查询的数学建模方法。方法根据直觉模糊集、直接模糊数与线性函数相结合的原理,通过改进相似性算法,预测支持偏好对调控指标的影响程度;识别最优递归阈值,依据偏好递归曲线量化调控指标;利用线性函数度量模型渐近性质,改进查询数学模型的渐进正态性;设置连续性、间歇性的查询机制,构建多样化反馈的查询数学模型。实验测试表明,与传统方法构建的模型相比,所提出方法构建的模型渐进正态性更好、反馈性能更强。由此可见,该建模方法满足查询数学模型的建模要求。 Traditionally,some query modeling methods ignore the influence of support preference on the regula-tion ability,leading to the poor asymptotic normality and feedback effect.Therefore,a mathematical modeling meth-od of linear recursive query supporting preference regulation was put forward.This method was based on the principle of combination of intuitionistic fuzzy sets,intuitionistic fuzzy number and linear function.Firstly,the method used the improved similarity algorithm to predict the influence of support preference on regulation indexes.Secondly,our method identified the optimal recursive threshold.Thirdly,this method used the preference recursion curve to quanti-fy control indexes.Moreover,the linear function was used to measure the asymptotic property of model,and then the asymptotic normality of the query mathematical model was improved.Finally,the query mechanism with continuity and intermittence was established.Thus,a query mathematical model with diversified feedback was constructed.Simulation results show that the designed model has better asymptotic normality and stronger feedback performance.This modeling method meets the modeling requirements of query mathematical model.
作者 尧雪莉 梁海峰 YAO Xue-li;LIANG Hai-feng(Institute of Technology,East China Jiao Tong University,Nanchang Jiangxi 330100,China)
出处 《计算机仿真》 北大核心 2020年第12期469-473,共5页 Computer Simulation
基金 江西省教育厅科技项目(GJJ171487) 江西省高校人文社会科学研究项目(JY18241)。
关键词 偏好调控 线性递归 查询机制 数学建模 Preference regulation Linear recursion Query mechanism Mathematical modeling
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