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network-optimization

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NetworkOptimizer

Self-hosted performance optimization and security audit tool for UniFi Networks. Includes Wi-Fi Optimizer for wireless health scoring and channel optimization, advanced DNS/VLAN/firewall security checks, config optimization suggestions, centralized WAN and LAN speed test server w/ Layer 2 tracing, U5G-Max modem stats, and more.​​​​​​​​​​​​​​​​

  • Updated Apr 18, 2026
  • C#
QECO

A QoE-Oriented Computation Offloading Algorithm based on Deep Reinforcement Learning (DRL) for Mobile Edge Computing (MEC) | This algorithm captures the dynamics of the MEC environment by integrating the Dueling Double Deep Q-Network (D3QN) model with Long Short-Term Memory (LSTM) networks.

  • Updated Apr 5, 2025
  • Python

This advanced and complex project implements an AI-powered optimization system for 5G Open RAN networks. Using machine learning and deep learning, the system optimizes network performance by detecting anomalies, predicting network traffic, and dynamically allocating resources.

  • Updated Apr 30, 2023
  • Python
Minecraft-Server-Optimizer-26

Minecraft Ultra Server Optimizer — High-Performance Tuning Suite for Paper, Purpur, and Forge. Advanced JVM Garbage Collection Tweaks, Asynchronous Chunk Processing, and Entity AI Optimization. Maximize TPS and reduce latency on high-player count servers for 2026.

  • Updated Mar 22, 2026
  • C++

一个全自动的 Cloudflare CDN 节点优选工具。通过 TCP 延迟测试、IP 可用性二次验证和真实带宽测速三重筛选,从海量公开 IP 中智能提取当前网络下最优节点。支持全局/分国家优选、前置国家过滤、自定义并发与重试策略,并可自动将结果批量更新至 Cloudflare DNS(多 IP 轮询)及同步至 GitHub 仓库。全程通过 WxPusher 微信通知实时反馈运行状态。全平台兼容(Windows / Linux),一键部署定时任务,轻松对接 EdgeTunnel 等代理工具。

  • Updated Apr 20, 2026
  • Python

Amaze Network is a high-performance system utility written in C#, designed for deep optimization of the Windows network stack and CPU resource management in real-time. It is specifically engineered for gamers and power users looking to minimize latency (ping) and maximize system responsiveness.

  • Updated Jan 28, 2026
  • HTML

A production-ready, end-to-end system for spare parts inventory management. This project combines advanced forecasting (TSB, Prophet, SARIMAX), mathematical optimization (CPLEX), and supply chain simulation (anyLogistix) to achieve 98.9% forecast accuracy and a 39% ROI improvement.

  • Updated Jul 12, 2025
  • Jupyter Notebook

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