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baer_fault_diagnosis

Bearing fault diagnosis model based on MCNN-LSTM

bearing-fault-detection

轴承故障检测 训练赛第30名代码

bearing_fault_recognition

利用西储大学开源的轴承故障数据，开发简单的人工神经网络，以实现对轴承故障的检测及识别。

casewesternreserveuniversitydata

cwru

deep-learning-for-image-processing

deep learning for image processing including classification and object-detection etc.

deeplearning_ai_books

deeplearning.ai（吴恩达老师的深度学习课程笔记及资源）

diagnosisdl2tf

使用TensorFlow建立简单的轴承故障诊断模型

fault-diagnosis

基于深度学习机械设备故障诊断模型

javaguide

「Java学习+面试指南」一份涵盖大部分 Java 程序员所需要掌握的核心知识。准备 Java 面试，首选 JavaGuide！

lstm-models-fdd-task

Here we share our experiments regarding training different DRNN configurations on the fault detection diagnosis of HVACs. The repository contains a fully-developed pipeline for data preprocessing of a common HVAC datasets, as well as different file configurations used in the paper. The objective was to optimize the associated hyperparameters, which is a very difficult task.

master-thesis

Master Thesis on Decision Systems Engineering: "Wind Power Forecasting Using Machine Learning Techniques".

mlstm-fcn

Multivariate LSTM Fully Convolutional Networks for Time Series Classification

onjava8

《On Java 8》中文版，又名《Java编程**》 第5版

real-url

获取斗鱼&虎牙&哔哩哔哩&抖音&快手等 58 个直播平台的真实流媒体地址(直播源)和弹幕，直播源可在 PotPlayer、flv.js 等播放器中播放。

short-term-wind-speed-prediction-based-on-deep-learning

LSTM neural network realizes the prediction of wind speed through the learning of various parameters. It can provide important support for the smooth operation of power system and the optimization of control strategy. The fuzzy rough set theory is used to reduce many factors that affect wind speed. It simplifies the input of the neural network prediction model and improves the accuracy and speed. Compared with the traditional neural network prediction method, MAE and MAPE in FRS-LSTM wind speed forecasting model have decreased and the accuracy has been improved greatly.

shukongdashi

使用知识图谱，自然语言处理，卷积神经网络等技术，基于python语言，设计了一个数控领域故障诊断专家系统

stas-wpp

A unified state-space model of a wind power plant, for system dynamics, optimization, and control. Developed for Gnu Octave.

statistical-learning-method_code

手写实现李航《统计学习方法》书中全部算法

top-deep-learning

Top 200 deep learning Github repositories sorted by the number of stars.

wind-phil-emulator

PHIL Wind emulator using a power converter and electrical machines. Includes parameter extraction and system identification of the machines, statistical models of low and high frequency wind, inertia modeling and torque control of PM DC motor.

windpowermonitorandalarmsystem

基于Kafka+Storm+HBase——风电行业实时流计算系统

wtd-library

Wind Turbine Dynamics (WTD) Library features a group of Simulink blocks for simulation of dynamic response of generic models of Wind Turbine Generators (WTG) on power system disturbances, which includes the General Electric (GE) Doubly Fed Induction Generator (DFIG) model. The WTD Library features a set of Simulink blocks that models GE DFIG as well as conventional steam and hydro generating units that are connected to a transmission grid. The Library also includes a set of Matlab m and S functions which are used for power flow calculation and initialization of state variables of the models of GE DFIG and conventional steam and hydro generating units. The WTD library is an open source simulation tool primarily aimed for educational/research purpose since it enables incorporation of user-defined Simulink models. The Library is especially suitable for development and testing of new algorithms for the control of WTG, like virtual inertia and primary frequency control algorithms.

you-get

:arrow_double_down: Dumb downloader that scrapes the web