survey

说明：   导航地图数据模型研究现状与趋势(Navigation Map Data Model Status and Trends)

documents to read on developement issues.

利用静基座下惯性导航系统的误差方程，用matlab/simulink建立了惯导误差仿真模型(The use of static base under the inertial navigation system error equation, using matlab/simulink simulation model established the INS error)

需求侧响应文章，了解国内外需求响应发展现状，未来趋势，把握行业动态。(Demand response)

2017年行业状况及预测之后的发展，现在遇到的瓶颈，当前这方面比较好的公司，以及计算机视觉有关的领域(In 2017, the industry situation and the development after prediction, and now faced with bottlenecks, the current relatively good companies, as well as areas related to computer vision.)

小木虫最新科研精华贴，对硕博生有很多的作用，很不错的资料哦(Wooden stick insect essence of the latest research on the role of Shuobo students have a lot of very good information Oh)

memetic algorthium in the distributed generation enivorment

：介绍了独立成分分析(ICA)的基本模型及其假设、含混性、非高斯性度量和通用求解过程。讨论了目前ICA 的几个研究方向的发展现状和面临的问题，分析了ICA 基本模型和几种扩展模型的求解算法，包括盲反卷积、卷积混和的盲分离、非线性瞬时混合的盲分离。提出了ICA 未来理论和应用研究中的开放课题。(: Introduce the independent component analysis (ICA) the basic model and its assumptions, vague, non-Gaussian measurement and GM solving process. Discussion of the current ICA several research directions of the development of the current situation and the problems faced by an analysis of the basic ICA model and several extended model algorithm, including the blind deconvolution, convolution mixture of blind source separation, nonlinear transient mixed Blind Source Separation. Proposed ICA future theoretical and applied research topics in the open.)

Duda Hart Tool Box Use manual

针对传统煤矿节能减排优化模型选取的目标函数比较单一的问题,构建了涵盖经济效益、能源消耗、污染物排放量等目标函数的煤矿节能减排多目标优化模型,并应用基于改进的蝙蝠算法寻找3个目标函数之间的优化解,实现了经济效益最大化、能源消耗最低化、污染物排放量最少化的优化结果。仿真结果表明,相比于PSO-E、NSGA-II算法,改进的蝙蝠算法能够在较短的迭代步数内获取较高的个体适应度,且能够实现较佳的多目标优化结果,符合节能规划的目标需求。(Aiming at the problem that the objective function of the traditional coal mine energy saving and emission reduction optimization model is relatively simple, the multi-objective optimization model of coal mine energy saving and emission reduction is constructed, which covers economic benefit, energy consumption and pollutant emission. And the optimized solution is used to find the 3 target functions based on the improved bat algorithm, and the economy is realized. The optimization results of maximizing efficiency, minimizing energy consumption and minimizing pollutant emissions are achieved. The simulation results show that, compared with the PSO-E and NSGA-II algorithms, the improved bat algorithm can obtain higher individual fitness within a shorter iteration step, and can achieve better multi-objective optimization results, which is in line with the target demand of energy saving planning.)