Relational Database Index Design and the Optimizers

优化器可以优化几乎所有内容，例如光线、粒子系统、多重地形、渲染器、NavMesh 代理、脚本组件等等！ 只需将优化器添加到游戏对象中，然后选择要更改质量的组件即可。定义达到特定 LOD 等级时要更改的参数的距离和百分比数量，现在优化器已准备就绪！ 该系统使用 Unity 的 CullingGroups API 和其他智能技术，以最有效的方式保持优化逻辑。 借助易于使用的优化器的自定义检查器窗口，您可以设定细节级别设置，而无需了解很多优化知识。 另一方面，它可以被程序员用作创建自己的优化方法的框架，并可以将优化器用作系统来处理不同 LOD 级别的设置，处理剔除状态逻辑等。 （不要误解！资源包没有为网格生成较低的 LOD 级别，它通过更改组件的参数/禁用/启用以提供更多优化） 通过资源包的自动操作节省大量时间。有很多工具会自动为您或通过按特殊按钮为您做很多事情。当您需要几个 LOD 级别时，所有参数都会自动调整，如果需要更多自定义设置，则可以在此之后进行编辑。 将资源包组件应用于静态或动态对象。

Cull, deactivate or activate, adjust quality basing on distance or visibility. Do it on anything inside scenes of your project! Give your game more FPS and be able to arrange more details! Optimizers can optimize almost everything, things like Lights, Particle Systems, Multiple Terrains, Renderers, NavMesh Agents, Script Components and more! Just add optimizer to your game object, select components of which you want change quality. Define distances and percentage amount of parameters you want to change when reaching certain LOD levels, now your optimizer is ready! This system is using Unity’s CullingGroups API and other smart techniques to keep optimization logics in the most performent way. With easy to use Optimizers’ custom inspector window you will set up your Level Of Detail settings without need to know much about optimizing. In other hand it can be used by programmers as framework to create own optimization methods and use optimizers as system to handle settings for different LOD levels, handling culling states logics etc. (Don’t get it wrong! Package is not generating lower LOD levels for meshes or so, it’s changing parameters of components/disabling/enabling to give more optimization) Save a lot of time by package’s automatic operations. There is a lot of stuff going on doing many things for you automatically or by pressing special buttons. When you need to have few LOD Levels, all parameters are adjusted automatically and if you need more customization you can edit them after that. Apply package components to static or dynamic objects. Apply different settings when object is hidden behind wall, cull if behind wall and a bit further, you have a lot of possibilities to adjust optimization behaviors for your project. Manager is progressively and intelligently adapting it’s CPU usage to the project’s global performance. When you will use tons of dynamic optimizer objects it’s update rate will imperceptibly slow down to never take any FPS from your

20210217 Brief Review of BSC Farms and Yield Optimizers.pdf

凯拉斯·拉丹（Keras RAdam） [| ] 在和TensorFlow中非官方实施 。 安装 pip install keras-rectified-adam 外部链接 用法 import keras import numpy as np from keras_radam import RAdam # Build toy model with RAdam optimizer model = keras . models . Sequential () model . add ( keras . layers . Dense ( input_shape = ( 17 ,), units

优化器 使用Python和数值库的各种优化算法的实现。 该存储库可作为本文中使用的可视化和评估的来源。 任务清单 动量的随机梯度下降（ ） AdaGrad（ ） AdaDelta（ D.Zeiler ） RMSProp（ ） 亚当（亚当（ ） NAdam（多扎特（ ）） AMSGrad（ ） 实作 在查看每种算法的完整源代码。 1.具有动量的随机梯度下降 def step ( self , x , y ): g_t = self . func . df ( x , y ) self . v = self . momentum * self . v + self . lr * g_t return ( x - self . v [ 0 ], y - self . v [ 1 ]) 2. AdaGrad def step ( self , x , y ):