摘要
针对用户喜好多样化、旅游线路个性化、旅游成本优减化等问题,本文提出了基于约束满足与连续型Hopfield神经网络二者相结合的旅游线路模型。首先利用回溯算法和启发式分支算法求出基础解,然后运用连续型Hopfield神经网络优化基础解,最后使用Matlab进行仿真实验。实验结果表明该模型能够有效地解决旅游线路规划问题,具有一定应用价值。
In order to solve the problems of user preferences,travel routes and travel cost reduction,this paper constructed atravel route model based on constraint satisfaction and continuous Hopfield neural network.Firstly,it uses the backtracking algorithm and heuristic branch algorithm to obtain the basic solution,then it applies the continuous Hopfield neural network to optimizing the basic solution.Finally,this paperusesMatlab to simulate the experiment.In a word,the experimental results show that the model can effectively solve the problem of travel route planning,and it has a certain application value.
出处
《内蒙古工业大学学报（自然科学版）》
2016年第1期24-30,共7页
Journal of Inner Mongolia University of Technology：Natural Science Edition
基金
国家自然科学基金资助项目(61363052)
内蒙古自治区高等学校科学研究项目(X201522)
