研究结论:(1)提出重载铁路跨区间无缝线路管理信息系统(简称HRC-MIS , Heavy-haul Regional Continuously Welded Rail Management Information System)的总体架构和功能模块;(2)研究了数据的具体种类、管理范围、观测周期以及记录方法，提出带修正的实际锁定轨温计算方法及基于运量汇聚回推的区段通过总重算法实现关键数据的获取;(3)研究了各种数据的内在关联性以及对线路状态的影响，提出综合时间和空间的纵横向关联统计分析方法;(4)提出基于广义动态模糊神经网络的实际锁定轨温预测方法以及定时和实时超限报警、预测预警机制，并自动生成作业项目指导和作业建议指导对养护维修作业提供辅助决策;(5)本文提出的HRC-MIS系统架构和关键技术的解决方案可为其他重载铁路跨区间无缝线路的智能化管理提供有益的借鉴，对重载铁路无缝线路发展规律、状态评价等研究工作也具有一定的参考意义。

Research conclusions:(1)The framework and functional modules of HRC-MIS are presented according to the theory of design and maintenance of heavy-haul regional CWR. ( 2)By studying the type，management scope，observation cycle and record method of the data，the calculating method with correction factor for actual neutral temperature and the algorithm for track section load which is based on aggregated traffic pushback are presented.(3)By deeply discussing about the internal correlations among all kinds of data and their influence on the status of the railway，the methods for statistical comparison analysis considering both space and time are proposed.(4)A prediction algorithm for actual neutral temperature by using the General Dynamic Fuzzy Neural Network is presented. And the assistant decision methods including regular and real-time over-limit alarming，early warning and maintenance instruction are proposed. (5)The results of this paper are worth popularizing in other regional CWR on heavy-haul railway and have reference value for the research on the variation law and status evaluation of CWR.