- Screen-Shot gambar grafik tugas kuliah
- Mir2-Client 韩国传奇客户端源代码 很有研究价值
- user-guide-a4 monitoring application execution directly within the development environment. The tight integration with the toolchain improves development workflow and provides each developer with access to runtime analysis that is easy
- yuce 可以实现依据时间序列对数据进行预测
- vienna matlab simulink 用于学习VIENNA整流器 只用 仅供参考学习(matlab simulink For reference only)
- 通信电路研究学习模板 对于通信电路学习有很大帮助
资源列表
69
- 含有DG配电网重构，基于小波神经网络优化电网损耗并且考虑了电压降落和电压偏移多目标-DG containing distribution network reconfiguration, optimize network losses wavelet neural network and considering the voltage drop and voltage offset multi-target
cloud_GA
- 云遗传算法用于解决多模项目调度问题，仿真文章的代码，大家共享，欢迎交流-cloud genetic alogrithm for multi-mode project schedule problems
mnist.pkl
- mnist数据集，手写体识别，可以应用于深度学习的测试数据-mnist dataset, used for handwriting recognize
cover_PSO
- 在MATLAB环境下，构建GUI模型，用粒子群算法实现对传感器覆盖问题的求解-in MATLAB environment, the sensor cover problem is solved by the intelligent tool.
RBF_control
- 以卫星编队动力学模型为对象，利用RBF神经网络算法进行控制，包括卫星轨道控制和姿态控制-Satellite fleet dynamics model as an object, use RBF neural network algorithm control, including satellite orbit control and attitude control
siliconpredictNARXwith-pca-VS-kpca
- 用PCA加动态神经网络（DNN）与KPCA加动态神经网络（DNN）做铁水含硅量预测，适用于多种时间序列预测。-the prediction of silicon content with NARX model based on PCA and DNN Vs the prediction of silicon content with NARX model based on KPCA and DNN .This method also can use to the other time serie
Gaussian-process-regression
- 高斯过程回归及分类的代码，内容全，有实例，注释清晰。包括分类系列和预测回归系列，值得感兴趣的同学学习借鉴。-Gaussian process regression and classification code, content, there are instances, comments clear.Including classification and forecasting return series, is worthy of reference for anyone interest
IRWLS-SVR-code
- IRWLS-SVR即基于迭代加权最小二乘的支持向量机回归-IRWLS-SVR，Support vectors based on iteratively reweighted least squares
模糊控制Simulink和模糊规则fis
- 单容水箱模糊控制的Simulink模型和模糊规则，测试过，可以用！！
Neural-network-kalman-filter-
- 自己写的改进的BP神经网络辅助组合导航卡尔曼滤波，运行成功，可供参考。-Write their own improved BP neural network aided integrated navigation kalman filter, run successfully, for reference.
code_1
- 在机器学习中利用欧氏距离设计一个KNN分类器，实现五折交叉验证，并用PCA进行降维-Develop a k-NN classifier with Euclidean distance and simple voting.Perform 5-fold cross validation, find out which k performs the best (in terms of accuracy)。Use PCA to reduce the dimensionality to 6, then p
code_3
- 根据用户的电影收视率来预测用户的性别和年龄并且使用10折交叉验证。-predict the gender and age of users based on their ratings on movies.perform 10-fold cross validation. In each fold, users.datx(x=0,…,9) is used for test, and all other users. datxare used for training. You can use m