MPC

netlogo文献主要是英文文献主要是用于帮助理解多agent建模，适合初学者入门(Netlogo literature is mainly English literature to help understand multi-agent modeling, suitable for beginners to get started.)

说明：  灰度关联预测模型MATLAB源代码实现灰度关联预测模型方法。(Realization of Gray Level Association Prediction Model by MATLAB)

本程序能快速扫描内网IP，选择IP开始和结束段就可以使用啦，本程序内涵源码，逻辑简单，不需要其它控件，delphi 2010开发(This program can scan intranet IP quickly.)

这是用c++写的一个模拟单服务台排队问题的一个程序，是在学过数据结构之后做的课程设计， 基本实现了计算平均队长，平均等待时间，最大队长，最大等待时间，平均服务时间

Samreen Amir写的Kinect Controlled UGV；Electronic Engineering Department, Dawood University of Engineering and Technology(Samreen Amir write toKinect Controlled UGV Electronic Engineering Department, Dawood University of Engineering and Technology)

说明：  圆孔夫琅禾费衍射仿真，利用MATLAB进行夫琅禾费衍射仿真(Simulation of Fraunhofer diffraction in a circular hole)

springboot 所需要的jar包，可以不用maven搭建(springboot need .jar)

Python codes for community detection

Addressbook using double-linked list. This example shows the use of a double-linked list by implementing an addressbook for the console. It has features like inserting, searching(linear), sorting(bubble sort), deleting and load/save to a file. I wrote this during my study of Applied Computer Science so it s intended mainly for students who want to know about some advanced programming techniques in C. The Code was compiled with MSVC++ 6.0 but it should compile with any ANSI-compliant compiler.

协同区间偏最小二乘 siPLS算法是 N rgaard等对其提出 的 iPLS方法的改进, 其基本算法步骤如下:(1)对原始谱图进行 预处理;(2)在全谱范围内建立全局偏最小二乘模型, 即上节的 模型;(3)在整个光谱区间采用 iPLS建立多个等窗口宽度的子 区间, 假设为 n个;(4)在每个子区间上建立偏最小二乘法模型, 即可得到 n个局部模型;(5)以交叉验证时的均方根误差 RMSE 值为各模型的精度衡量标准, 比较全光谱模型和各局部模型的 精度;(6)组合精度最高的局部子区间为新的回归区间;再在新 的回归区间建立 siPLS模型(Cooperative interval partial least squares (siPLS) algorithm is proposed by N rgaard et al. The improvements of the iPLS method are as follows: (1) the original spectrogram is performed. Preprocessing; (2) establishing a global partial least squares model in the full spectrum, that is, the upper part of the model. Model; (3) use iPLS to establish multiple equal window widths in the whole spectral interval. The interval is assumed to be n; (4) a partial least squares model is established on each sub interval. N local models can be obtained; (5) the root mean square error of cross validation is RMSE The values are the accuracy criteria of each model, and the comparison between the full spectral model and the local models is made. (6) the local interval with the highest combined precision is a new regression interval; and then new. The establishment of siPLS model in the regression interval)