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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, includi
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带分支预测的MIPS流水线的verilog原代码。
详细介绍了流水线的设计代码-Branch prediction with the MIPS pipeline verilog source code. Details of pipeline design code
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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
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(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-bran
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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++ AP
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ARC700 has a relatively long pipeline and branch prediction, so we want to avoid branches that are hard to predict.
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支持向量机(SVM)——分类预测,包括核函数调参,不平衡数据问题,特征降维,网格搜索,管道机制,学习曲线,混淆矩阵,AUC曲线等(Support vector machine (SVM) - classification prediction, including kernel function parameter adjustment, unbalanced data problem, feature dimensionality reduction, grid search, pipelin
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