资源列表
Dissertation-ARIMA_SVR-prediction-master
- 基于时间序列分析ARIMA和SVR组合模型的预测(Prediction of ARIMA and SVR combined models based on time series analysis)
H-ELM
- 可用作数据分类和拟合，深度极限学习机拥有深度学习的优势和自身计算速度快的优势(It can be used to classify and fit data. The deep extrme learning machine has the advantages of depth learning and fast computing speed.)
基于博弈论的全双工系统无线资源分配
- 由于自干扰和用户间干扰，全双工系统上下行链路之间的功率冲突问题问题被耦合在上行链路和下行链路信道之间，并且可以被表示为联合的上行链路和下行链路的和速率最大化。由于该问题是非凸的，因此将此问题建模为上下行信道之间的非合作博弈，提出了一种基于博弈论的迭代算法。(Due to the self-interference and interuser interference, the problem is coupled between uplink and downlink channels, an
连续隐马尔可夫离散隐马尔科夫模型的MATLAB实现
- 隐马尔可夫连续和离散情况下的MATLAB实现(MATLAB Realization of Hidden Markov Continuous and Discrete Conditions)
18-33粒子群优化灰色预测
- 用粒子群算法优化灰色预测模型，程序可以运行，自己编写的，如有问题，可以联系我沟通(Using particle swarm optimization to optimize the grey prediction model, the program can run, write by oneself, if there are problems, you can contact me to communicate.)
gcn-master
- 图卷积神经网络实现代码， python实现了图卷积神经网络的功能。(the code for gcn use python the paper is COVARIANT COMPOSITIONAL NETWORKS FOR LEARNING GRAPHS)
二维Euler方程C++
- 该程序是用C++语言编写的，用来求解二维欧拉方程，采用的计算案例是二维翼型，采用中心差分格式进行离散和求解。
典型的多目标粒子群算法
- 典型的多目标粒子群算法，用于求解多目标优化问题(Typical multi-objective particle swarm optimization algorithm for solving multi-objective optimization problems)
排课
- 实现基于改进的遗传算法的课表编排功能，适用于新高考走班制背景下的课表编排。移植性高。(It realizes the function of timetable arrangement based on improved genetic algorithm, which is suitable for the timetable arrangement under the background of the new college entrance examination shift syste
Dstar动态路径规划算法
- 用于动态路径寻优的D*算法，可以运行出完整的路径，具有一定的参考价值(D* algorithm for dynamic path optimization, can run)
DMD
- 快照数据的动态模态分解，获得基模态和对应的特征值，包括频率和增长率，以及数据后处理。(Dynamic modal decomposition of snapshot data to obtain basic modes and corresponding eigenvalues, including frequency and growth rate, and data post-processing.)
DEGWO
- 一种差分进化与灰狼算法结合的混合算法，可以运行。(A hybrid algorithm combining differential evolution and gray Wolf algorithm.)