Description: 本书涉及的研究方法主要应用于油田生产的实际工作中，包括一般储层参数预测、薄互油藏参数预测、火山岩储层参数预测和储层随机模拟等问题，同时还涉及了石油工业中的油管缺损检测、海底输油管道腐蚀检测等应用问题，对污水处理絮凝过程的智能优化控制及移动机器人的全局和局部路径规划等问题的应用也进行了一定的研究。-Book of research methods involved are mainly used in oil field production of practical work, including the general prediction of reservoir parameters, thin reservoir parameter prediction, volcanic prediction of reservoir parameters and reservoir stochastic simulation and other issues, but also involved in the oil industry pipeline defect detection, submarine detection applications such as pipeline corrosion problem of the sewage treatment process of flocculation and optimal control of intelligent mobile robot path planning global and local issues such as the application have also been some study. Platform: |
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Author:cheny |
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Description: 在很多无线传感器网络应用中，没有节点位置信息的监测信息往往毫无意义。当监测到事件发生时，关心的一个重要问题就是该事件发生的位置，如森林火灾监测，天然气管道泄漏监测等。这些事件的发生，首先需要知道的就是自身的地理位置信息。定位信息除了用来报告事件发生的地点外，还可用于目标跟踪、目标轨迹预测、协助路由以及网络拓扑管理等-In many wireless sensor network applications, there is no node location information of the monitoring information is often meaningless. When monitoring the event occurs, an important issue of concern is the location of the incident, such as forest fire monitoring, natural gas pipeline leak monitoring. These events, first of all need to know is their location information. Addition to its use location information of the sites based on the report of the incident, can be used for target tracking, target trajectory prediction, Xie Zhu routing and network topology management, etc. Platform: |
Size: 110592 |
Author:wjw |
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Description: 使用人工神经网络，将样本输入网络后，进行预测。绘制预报曲线，地上管网急修作业类型-The use of artificial neural networks, the sample input network, to predict. Prediction curve drawn, the type of ground pipeline emergency repair work Platform: |
Size: 2048 |
Author:祝建英 |
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Description: （包含详细说明文档和简单汇编转机器码翻译器）五级流水线实现MIPS指令集（30条）含异常处理。结构采用多分支预测结构（基于历史的动态分支预测）-(Contains detailed documentation and compilation turn simple machine code translator) five pipelined MIPS instruction set (30) with exception handling. Structure using multi-branch prediction structure (based on the dynamic branch prediction history) Platform: |
Size: 1165312 |
Author:yuxueru |
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Description: 属于机器学习的范畴，通过输入训练样本，通过分类或线性回归得到标签的假设性函数-The Gesture Recognition Toolkit (GRT) is a cross-platform, open-source, C++ machine learning library that has been specifically designed for real-time gesture recognition.
In addition to a comprehensive C++ API, the GRT now also includes an easy-to-use graphical user interface (GUI) which enables user s to stream real-time data into the GUI via the Open Sound Control network protocol. Using the GUI you can:
(1) Setup and configure a gesture recognition pipeline that can be used for classification, regression, or timeseries analysis.
(2) Stream real-time data into the GUI via Open Sound Control (OSC) another application (such as Processing, Max, Pure Data, Openframeworks, etc.).
(3) Record, label, save and load your training data.
(4) Train a model for classification or regression.
(5) Test the generalization abilities of the model (using another test dataset or cross validation).
(6) Perform real-time prediction on new data streamed into the GUI via OSC.
(7) Stre Platform: |
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Author:王哲 |
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Description: ARC700 has a relatively long pipeline and branch prediction, so we want to avoid branches that are hard to predict.
Platform: |
Size: 3072 |
Author:bznkxei |
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Search - prediction pipeline