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Course Introduction and Overview of Big Data课程教案、知识点、字幕

欢迎大家走进来自长安大学的智能电网大数据的课堂
So welcome everyone to BDSG from Chang’an University

我非常荣幸能为大家讲解这门课。
I’m super excited to offer this class.

这门课是关于智能电网和大数据的。
So this class is really about Smart Grid and Big Data.

虽然我觉得没必要提醒大家这门课程内容的重要性
I think I probably don’t need to convince you the importance of this course

但是我还是会在第一次课介绍一下这门课的由来和它的重要应用。
But I will still talk about the origin and important applications of BDSG later.

好的
Okay

这是今天的议程
this is today's agenda.

第一部分是课程的最后一部分
The first part is over view of the course,

第二部分是什么是大数据 我能做什么
and the second part is what is big data and what can I do.

本课程内容共分3部分
it is divided into three parts.

第一部分
First,

是背景和理论
I will provide you a very brief background and rationale.

第二部分
Second,

是技术与应用
we will learn about the related technologies and applications.

第三部分
Finally,

是总结
all above well be summarized,

与展望
and the future research will be talked about.

本课程内容主要有两本参考书
The main reference books for this course are

王继业主编的智能电网大数据
Smart Grid Big Data

和电力大数据技术及其应用
And Power Big Data Technology and Its Application


from Jiye Wang.


who is a senior engineering.

以上是对本课程的一个简介
So that was the quick introduction of this course

现在让我们看看第一部分的章节
Now let's take a look about the chapters in Part One,

第一章是大数据
the first chapter is what is big data,

第二个是
and the second is

怎么认识大数据
what is big data


of smart grid.

我们只关注第一章
We'll just a focus on first chapter.

这是第一部分的第一章
Okay is the first chapter of part one,

在这一章我们将学习其定义和应用
And we will talk about the concepts and applications of big data.

现在让我们看一些图片
Now let's look at some pictures.

这幅图
The big data

可能是人工智能设备采集的
it could be the image sets from some Artificial

图像集
Intelligent equipment

它也可能是一些医学图像
and it also could be medical image


sets

除了这些可视化的数据集之外
Beyond these kinds of visual data

它还可能是不可视的
it could also be the invisible data

比如数据型数据
such as numerical data set.

所以大数据的概念常常因研究者个体的不同而不同
So the concept of big data varies from researcher to research.

说到底
it’s just

概念的区别是由于研究领域的不同造成的
decided by the different forms of research field

但其本质都没有改变
but the essence of big data is always there,

大数据覆盖各个领域
That is big data covers all fields,

它就是一系列庞大数据集的综合体
It is a term for massive data sets

具有数据量大
having large,

变化种类多以及结构复杂的特点
more varied and complex structure

因此也造成了其储存
with the difficulties of storing

分析和可视化等进一步处理的困难
analyzing and visualizing for further processes or results

讲完它的概念
After what it is

让我们来看看它有哪些应用吧
now let’s talk about what can it do

大数据可以用在智慧交通领域
It can be used in intelligent transportation systems (ITS)

在世界各地的很多项目中均可见
which can be seen in many projects around the world

智慧交通会产生大量的数据
Intelligent transportation systems will produce a large amount of data

所产生的数据会对ITS系统的设计和应用产生深刻的影响
The produced data will have profound impacts on the design and application of intelligent transportation systems

这使得ITS更安全
which makes ITS safer

更高效 更便携
more efficient and profitable

而针对ITS的大数据研究也成为了热门研究领域
Studying big data analytics in ITS is a flourishing field.

大数据还可以用在农业方面 它对农业的影响与日俱增
It can also be used in agriculture.And its influence on the smart agriculture is increasing day by day.

例如
For example,

用于农田环境信息采集的智能感知节点低价高效
the intelligent perception nodes for farmland environment information has the features of low cost and high efficiency

这些是农田常用的温湿度
These are the temperature and humidity sensor

光照
light sensor

和风速风向传感器
and wind sensor

通过这些传感器采集到的大量数据
Based on the data from those sensors

采样装置和无线传感装置
Sampling devices and Wireless transmission terminals such as CDMA


or


GPRS


zigbee,


etc.

会帮助建立环境产量模型
can help to establish the environment production model.

以及作物生长
And the system of crop growth

感知和智能决策系统
environment perception and intelligent decision can be built, too.

因此 农田环境要素和作物生长周期以及产量的关系
The relationship between farmland and the environmental factors and crop growth cycle and crop yield,

也一目了然
is available.

除此之外
Additionally,

大数据还可以用于气候管理
big data is useful in climate analysis

电信行业
telecommunication

行业
industry

零售业
retail,


etc.

我们经常在淘宝 京东等购物app看到的商品推送
The product push we often see in the shopping app such as TaoBao JD COM

就是基于零售业大数据的客户行为分析
is the analysis result of customer behavior based on the big data of the retail industry

我分享一个自己的购物推送经历
Let me share a shopping push story from I myself

我给我儿子买了一辆滑轮车后
After I bought a scooter for my son

购物页面推送了头盔
the push page of shopping website highly recommend the Children s helmets

后来我给女儿买了些教材书本
And after I bought the textbooks for my daughter

购物网站开始推送
the push page popped up

双层床等多子女用品
some promotion information of products for non-one-child family


such as double-deck bed

这都是基于购物网站对我的子女情况的猜测
So this is totally based on the analysis


on my shopping list

最后
At the end,

这是本节课相关的参考文献
These are some references for this lecture

现在大家对大数据和应用有所了解了吧
Now I guess you know what is big data and what can it do.

下节课将简要介绍智能电网大数据的概念和应用
Next time we will talk about what is the big data of smart grid

好的
OK,

谢谢
thanks.

Big Data of Smart Grid课程列表:

Chapter 1 What is Big Data

-Course Introduction and Overview of Big Data

-Chapter 1

-Big data review literature

Chapter 2 Big Data of Smart Grid(BDSG)

-2.1 Why Electirc Power + Big Data? 2.2 Applications

-Chapter 2

-An important application of big data in electric power——literature on the identification of small targets such as faults

Chapter 3 Main Application Fields of BDSG

-3.1 Grid Operation and Development

-3.2 Power Consumers

-3.3 Society and Government

-Chapter3

-Related literature on big data applications from the user perspective

Chapter 4 Technology System of BDSG

-4.1 Data Acquisition+4.2 Data Storage

-4.3 Data Processing

-4.4 Data Analysis and Mining

-4.5 Data Visualization

-4.6 Data Security and Privacy Protection

-Chapter4

-Load forecasting technology related literature

Chapter 5 Research Methods and Application Methods of BDSG

-5.1.1Platform Construction: Demand Analysis

-5.1.2Platform Construction: Design (1)

-5.1.2Platform Construction: Design (2)

-5.2 Data collection and management

-5.3.1 Data Aggregation and Fusion: Scheme and process

-5.3.2 Data Aggregation and Fusion: Application Practice

-5.4.1 Analysis and Mining: Scheme and process

-5.4.2 Analysis and Mining: Use-case analysis

-Chapter5

-Commonly used electric power big data deep learning method——application literature of transfer learning

Chapter 6 Project Cases of BDSG

-6.1 Heavy overload prediction of station area

-6.2 Daily load forecasting of large users

-6.3 Fault correlation analysis of power grid control system equipment

-6.4 Reliability of relay protection equipment family-

-6.5Application of random matrix in big data analysis of smart grid

-Chapter6

-Literature on Power Vision Data Processing Technology

Chapter 7 Prospect of BDSG

-Development trend and suggestions for BDIG

-Chapter7

-Intelligent Disaster or Failure Recognition Means——Related Literature of Electric Power Vision Big Data

Course Introduction and Overview of Big Data笔记与讨论

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