Hayu mining machine gtx1060

1. are you using game graphics card or mining card

2. Mining consumes a lot of game graphics cards, so it is recommended to use professional mining cards

1. Power consumption: 243w; Calculation force: 22.4m; Price: 1999 yuan; The number of eth g every 24 hours: 0.015; Revenue generated every 24 hours: 24.8 yuan; Expected payback time: 81.66 days

2. Power consumption of the whole machine: 159w; Calculation force: 24.3m; Price: 1599 yuan; Number of eth g every 24 hours: 0.017; Revenue generated every 24 hours: 27.9 yuan; Expected payback time: 57.31 days

3. Power consumption: 171w; Calculation force: 24.4m; Revenue generated every 24 hours: 27.87 yuan; Expected payback time: 71.73 days

4. Power consumption: 97W; Calculation force: 9.2; Price: 999 yuan; Number of eth g every 24 hours: 0.006; Revenue generated every 24 hours: 10.09 yuan; Expected payback time: 99.1 days

extended data

mining machine risk

1. The problem of electricity charge

in order to make the graphics card full load for a long time, the power consumption will be quite high, and the electricity charge will be higher and higher. Many professional mines at home and abroad are operated in areas with extremely low electricity charges, such as hydropower stations, while more users can only mine at home or in ordinary mines, so the electricity charges are not cheap. Even in a certain residential area in Yunnan, there was a case of crazy mining, which led to a large area trip of the residential area, and the transformer was burned

2. Hardware expenditure

mining is actually a competition of performance and equipment. Some mining machines are composed of more such graphics card arrays. With dozens or even hundreds of graphics cards, the cost of hardware and other costs is very high, and there is a considerable expenditure in mining

3, currency security

the withdrawal of bitcoin requires hundreds of keys, and most people will record this long string of numbers on the computer, but the frequent problems such as hard disk damage will make the key permanently lost, which also leads to the loss of bitcoin

Graphics card digging Monroe is really better than other currencies, the income will be higher! Of course, digging eth is also a good choice

this is my own video card miner. The mining software uses ha Yu miner , (the reason why I choose this software is that ha Yu does not pump water ) there are about 12 pieces per day

Mining is a work that needs a lot of computing power to support. The reason why we use the graphics card mining machine is that the graphics card is easier to carry out a lot of repeated calculations than the CPU, so the general mining machine of the graphics card selects the graphics card mining machine

but mining also need to find a useful mining software, I have been using ha Yu miner mining, easy to use, high income< br />

我今天要去图书馆

I'm going to the library today

重点词汇

• 今天today;now;present

• 图书馆library;bibliotheca

The obtained print value is used as the dependent variable and the original data as the independent variable. Then linear regression, the regression coefficient is the coefficient of linear combination, and the regression is equivalent to a linear equation group, and then it can be reced to the principal component regression equation

logistic regression can be divided into three categories: one is binary logistic regression with dependent variable, which is called binomial logistic regression; the other is multiple logistic regression with dependent variable, such as which proct is preferred, which is called multiple logistic regression

there is another kind of logistic regression in which the dependent variable is ordinal multi classification, such as the degree of illness is high, medium, low, etc. this kind of regression is also called cumulative logistic regression, or ordinal logistic regression

extended data:

Data Standardization (normalization) is a basic work of data mining. Different evaluation indexes often have different dimensions and dimensional units, which will affect the results of data analysis. In order to eliminate the dimensional influence between indexes, data standardization is needed, To solve the comparability between data indicators. The original data after data standardization processing, each index in the same order of magnitude, suitable for comprehensive comparative evaluation

significance: data centralization and standardization in regression analysis is to eliminate the errors caused by different dimensions, self variation or large difference in values

principle: data standardization refers to subtracting the mean value from the value and then dividing it by the standard deviation

data centralization: it means that the variable subtracts its mean value

Objective: through centralization and standardization, we can get the data with the mean value of 0 and the standard deviation of 1, which obey the standard normal distribution