dxw2314

dxw2314's Stars

• CyC2018/CS-Notes

  :books: 技术面试必备基础知识、Leetcode、计算机操作系统、计算机网络、系统设计

  178k5.3k59551.2k

• alibaba/druid

  阿里云计算平台DataWorks(https://help.aliyun.com/document_detail/137663.html) 团队出品，为监控而生的数据库连接池

  Language:Java28k1.7k4.5k8.6k

• lenve/vhr

  微人事是一个前后端分离的人力资源管理系统，项目采用SpringBoot+Vue开发。

  Language:Java27.5k87625410.3k

• judasn/IntelliJ-IDEA-Tutorial

  IntelliJ IDEA 简体中文专题教程

  21.9k1.8k07.3k

• yudaocode/SpringBoot-Labs

  一个涵盖六个专栏：Spring Boot 2.X、Spring Cloud、Spring Cloud Alibaba、Dubbo、分布式消息队列、分布式事务的仓库。希望胖友小手一抖，右上角来个 Star，感恩 1024

  Language:Java19.3k809446k

• blue-yonder/tsfresh

  Automatic extraction of relevant features from time series:

  Language:Jupyter Notebook8.5k1725321.2k

• 2dust/clashN

  A clash client for Windows, support Mihomo

  Language:C#4.9k32337605

• saysky/ForestBlog

  一个简单漂亮的SSM(Spring+SpringMVC+Mybatis)博客系统

  Language:Java4.6k70501.6k

• anyoptimization/pymoo

  NSGA2, NSGA3, R-NSGA3, MOEAD, Genetic Algorithms (GA), Differential Evolution (DE), CMAES, PSO

  Language:Python2.4k29430404

• FuZhucheng/SSM

  J2EE项目系列（四）–SSM框架构建积分系统和基本商品检索系统（Spring+SpringMVC+MyBatis+Lucene+Redis+MAVEN）

  Language:Java1.2k587466

• jindongwang/activityrecognition

  Resources about activity recognition-行为识别资料

  Language:MATLAB9215211350

• dmbee/seglearn

  Python module for machine learning time series:

  Language:Python574262963

• dyfcalid/STM32-car-MPU6050-Bluetooth-Ultrasonic

  以STM32F103为主控芯片，载有MPU6050的六轴加速度传感器、HC-05蓝牙模块、HC-SR04超声波模块、LCD触摸屏、直流电机、舵机等模块的多功能智能小车

  Language:C27810149

• ShiSanChuan/GeneticAlgorithm

  这是用C++写的遗传算法，参考《智能算法 30案例分析 第2版》一书，包含TSP、LQR控制器、结合量子算法、多目标优化、粒子群等，由于原作为matlab程序，综合自己思路通过C++写出来，算是练习和开个大坑

  Language:C++1963248

• Grootzz/GA-BP

  基于遗传算法的BP网络设计，应用背景为交通流量的预测

  Language:MATLAB1627652

• SajadAHMAD1/Chaotic-GSA-for-Engineering-Design-Problems

  All nature-inspired algorithms involve two processes namely exploration and exploitation. For getting optimal performance, there should be a proper balance between these processes. Further, the majority of the optimization algorithms suffer from local minima entrapment problem and slow convergence speed. To alleviate these problems, researchers are now using chaotic maps. The Chaotic Gravitational Search Algorithm (CGSA) is a physics-based heuristic algorithm inspired by Newton's gravity principle and laws of motion. It uses 10 chaotic maps for global search and fast convergence speed. Basically, in GSA gravitational constant (G) is utilized for adaptive learning of the agents. For increasing the learning speed of the agents, chaotic maps are added to gravitational constant. The practical applicability of CGSA has been accessed through by applying it to nine Mechanical and Civil engineering design problems which include Welded Beam Design (WBD), Compression Spring Design (CSD), Pressure Vessel Design (PVD), Speed Reducer Design (SRD), Gear Train Design (GTD), Three Bar Truss (TBT), Stepped Cantilever Beam design (SCBD), Multiple Disc Clutch Brake Design (MDCBD), and Hydrodynamic Thrust Bearing Design (HTBD). The CGSA has been compared with seven state of the art stochastic algorithms particularly Constriction Coefficient based Particle Swarm Optimization and Gravitational Search Algorithm (CPSOGSA), Standard Gravitational Search Algorithm (GSA), Classical Particle Swarm Optimization (PSO), Biogeography Based Optimization (BBO), Continuous Genetic Algorithm (GA), Differential Evolution (DE), and Ant Colony Optimization (ACO). The experimental results indicate that CGSA shows efficient performance as compared to other seven participating algorithms.

  Language:MATLAB962126

• Ki-Seki/MOPSO-for-Distribution

  一个疫情背景下应急物资配送算法：用改进后的多目标粒子群优化（MOPSO）算法解决带有风险矩阵的多辆车配送旅行商问题（TSP）

  Language:MATLAB75127

• jullyjelly/Intelligent_Algorithm

  Optimization problem solving: genetic algorithm, ant colony algorithm, tabu search algorithm, simulated annealing algorithm, particle swarm optimization

  Language:MATLAB622010

• leijmin/StepDemo

  利用加速度传感器实现的，实时计步小demo！

  Language:Objective-C472018

• xyjigsaw/Dataset

  Dataset for all

  Language:MATLAB404042

• drenaw/pso-ga-hybrid

  A hybrid of Particle Swarm Optimisation and Genetic Algorithm applied to Flow Shop Scheduling

  Language:Matlab33402

• longbiscuit/CEC2017-8-

  CEC2017测试集测试了模拟退火（SA）算法、状态转移（STA）算法、实数编码遗传（RCGA）算法、差分进化（DE）算法、免疫（IA）算法、粒子群（PSO）算法、蚁群（ACO）算法和多种自适应策略粒子群（MAPSO）算法

  32200

• stavrosk7/Genetic_Algorithm_for_Scheduling

  Genetic Algorithm for Solving Software Project Scheduling Problems

  Language:Matlab31225

• JingweiToo/Whale-Optimization-Algorithm-for-Feature-Selection

  Application of Whale Optimization Algorithm (WOA) in the feature selection tasks.

  Language:MATLAB26106

• wenwu2han/Hybrid-flow-shop-scheduling

  Multi-objective evolutionary algorithms integrated with different heuristic decoding methods for hybrid flow shop scheduling problem with worker constraint

  Language:MATLAB23116

• anyangxaut/ThesisExperiment

  硕士毕业论文实验：基于多传感器的行为识别（主要研究特征优选） + 室内定位（加速度传感器，陀螺仪传感器，磁力计）

  Language:Java21517

• Shawn9927/Hybrid-Particle-Swarm-Optimization-Algorithm

  一种混合VNS（变邻域搜索算法）的PSO（粒子群优化算法）用以解决拦截对抗中的任务分配问题，新的算法能够有效地避免粒子群陷入局部收敛

  Language:MATLAB1110

• Ki-Seki/Genetic-Particle-Swarm-Optimization

  陈克明《动态多智能算法及其在物流配送系统中的应用研究》中的遗传-粒子群算法复现

  Language:MATLAB10102

• hzgz17/HGGVNS

  Hybrid genetic general variable neighborhood search

  Language:MATLAB511

• wongself/Optimization

  Single machine scheduling and flow shop

  Language:MATLAB2203