基于多种函数拟合的技术预见模型

Technical Foresight Model Based on Multiple Function Fitting

[目的/意义]为了解决函数拟合在技术预见应用中存在的龙格与过拟合问题,提高文献数据利用率和拟合程度,尝试在多种非线性函数的基础上,结合验证集与预测评价概念实现更科学、更有效和更完善的拟合与预见效果。[方法/过程]基于多种函数拟合的技术预见模型分为三部分:感知过滤器模型,技术主题分析模型,技术主题趋势探测模型。[结果/结论]以VOC领域为例进行实证研究,最终发现正弦函数、高斯函数、四次函数对词趋势拟合效果最佳。根据预测得出的热点主题词预见了VOC领域的三个研究方向:检测、排放与治理,并对此进行分析与探讨。

[Purpose/significance]In order to solve the Runge Phenomenon and over-fitting problems of function fitting in the application of Technology Foresight, and to improve the utilization of literature data and the degree of fitting.We try to combine the concept of the validation set and predictive evaluation on the basis of various nonlinear functions, to achieve a more scientific, effective and perfect result of fitting and foreseeing.[Method/process] The technology foresight model based on multiple function fitting is divided into three parts, the perceptual filter model, the technology theme analysis model, and the technology theme trend detection model.[Result/conclusion]Empirical research is conducted in the VOC filed, and it is found that the sine function, Gaussian function, and quadratic function have the best effect on the word trend fit.Based on the hot topic words derived from the predictions, the VOC field can be divided into three areas: detection, emission and management, and finally analyzed and discussed in these three areas.