My next project

本文分享了一个游戏项目的设计过程,重点介绍了四个关卡的特点:Level Run Cool,从无帮助开始,非常容易完成;Dirt,充满泥土的关卡,简单易过;Wood,木制关卡,对于玩过Mini World的玩家来说不难;Rock,岩石关卡,虽然长度较长,但通过努力可以到达顶点。

On my next project, (which I have explain in the last diary) is good looking, because is a cool run, and I called it level run cool, because it first start with no help, It’s very very very easy, if you can get to the end, you’re no help.
The second one is dirt, dirt is easy, and then wood, wood is easy too, if you have played mini world, and the forth one is rock, rock is normal, but rock is always long, but it’s possible to get to the top, even you only have the two caricature first, and then…

PS D:\lump\neo4jproject\neo4j_vue\my-project> npm run serve > my-project@0.1.0 serve > vue-cli-service serve INFO Starting development server... ERROR Failed to compile with 2 errors 15:52:56 [eslint] Invalid Options: - Unknown options: extensions - 'extensions' has been removed. You may use special comments to disable some warnings. Use // eslint-disable-next-line to ignore the next line. Use /* eslint-disable */ to ignore all warnings in a file. Error: Child compilation failed: [eslint] Invalid Options: - Unknown options: extensions - 'extensions' has been removed. - child-compiler.js:169 [my-project]/[html-webpack-plugin]/lib/child-compiler.js:169:18 - Compiler.js:629 finalCallback [my-project]/[webpack]/lib/Compiler.js:629:5 - Compiler.js:664 [my-project]/[webpack]/lib/Compiler.js:664:11 - Compiler.js:1350 [my-project]/[webpack]/lib/Compiler.js:1350:17 - task_queues:105 processTicksAndRejections node:internal/process/task_queues:105:5 - task_queues:69 runNextTicks node:internal/process/task_queues:69:3 - timers:459 process.processImmediate node:internal/timers:459:9 ERROR in [eslint] Invalid Options: - Unknown options: extensions - 'extensions' has been removed. ERROR in Error: Child compilation failed: [eslint] Invalid Options: - Unknown options: extensions - 'extensions' has been removed. - child-compiler.js:169 [my-project]/[html-webpack-plugin]/lib/child-compiler.js:169:18 - Compiler.js:629 finalCallback [my-project]/[webpack]/lib/Compiler.js:629:5 - Compiler.js:664 [my-project]/[webpack]/lib/Compiler.js:664:11 - Compiler.js:1350 [my-project]/[webpack]/lib/Compiler.js:1350:17 - task_queues:105 processTicksAndRejections node:internal/process/task_queues:105:5 - task_queues:69 runNextTicks node:internal/process/task_queues:69:3 - timers:459 process.processImmediate
03-22
提供了基于BP(Back Propagation)神经网络结合PID(比例-积分-微分)控制策略的Simulink仿真模型。该模型旨在实现对杨艺所著论文《基于S函数的BP神经网络PID控制器及Simulink仿真》中的理论进行实践验证。在Matlab 2016b环境下开发,经过测试,确保能够正常运行,适合学习和研究神经网络在控制系统中的应用。 特点 集成BP神经网络:模型中集成了BP神经网络用于提升PID控制器的性能,使之能更好地适应复杂控制环境。 PID控制优化:利用神经网络的自学习能力,对传统的PID控制算法进行了智能调整,提高控制精度和稳定性。 S函数应用:展示了如何在Simulink中通过S函数嵌入MATLAB代码,实现BP神经网络的定制化逻辑。 兼容性说明:虽然开发于Matlab 2016b,但理论上兼容后续版本,可能会需要调整少量配置以适配不同版本的Matlab。 使用指南 环境要求:确保你的电脑上安装有Matlab 2016b或更高版本。 模型加载: 下载本仓库到本地。 在Matlab中打开.slx文件。 运行仿真: 调整模型参数前,请先熟悉各模块功能和输入输出设置。 运行整个模型,观察控制效果。 参数调整: 用户可以自由调节神经网络的层数、节点数以及PID控制器的参数,探索不同的控制性能。 学习和修改: 通过阅读模型中的注释和查阅相关文献,加深对BP神经网络与PID控制结合的理解。 如需修改S函数内的MATLAB代码,建议有一定的MATLAB编程基础。
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