Virtual currency with the largest trading volume
digital currency trading platforms include BTCC, cloud coin, youcoin, yicoin and China bitcoinblockchain lettering and other fields
note:
1. Investing in digital currency is very skillful, but also very cautious. After all, not everyone can make money by investing, and a careless person may fall into the abyss, so it is very important to supplement this knowledge
In the short to medium term, you should not rely too much on digital currency investment. In the worst case, you should be ready to bear the loss of all the moneyThe top ten virtual currency trading platforms are: bitcoin China, Ethereum, Monroe, dascoin, reborn, etc.
Bitcoin China (BTCC), the first and largest bitcoin trading platform in China, is operated by Shanghai satuxi Network Co., Ltd., which was established on June 9, 2011. The team members are mainly from China, Silicon Valley and Europebitcoin China provides a reliable trading platform for users to buy and sell bitcoin through RMB
users can also save bitcoin safely in the platform
bitcoin China has achieved the best balance between high security and user convenience
4. Monro (code name XmR) is an open source cryptocurrency founded in April 2014, which focuses on privacy, decentralization and scalability. Unlike many cryptocurrencies derived from bitcoin, monero is based on cryptonote protocol and has significant algorithm differences in blockchain fuzziness
Dash, formerly known as dark coin, is a technical improvement on the basis of bitcoin. It has good anonymity and decentralization. It is the first digital currency with the purpose of protecting privacy. You can feel that it is liked by the black market when you listen to its name The main characteristics of Dashi coin are as follows:1
2. Instant payment function, timely arrival and low handling charge
China's top ten virtual currency trading platforms are bitcoin, okcoin, Huo coin, jucoin, yuncoin, BTCC, coin security, bitera and viabtc
The largest virtual currency trading platform in China is bitcoin trading platform, and the three most well-known ones are bitcoin China, okcoin and fire coin
secondly, there are some counterfeit currency trading platforms. For example, jucoin.com, Yinying China, bitage and so on
another simple way is to use the generalized RBF network, which can be realized directly with GRNN function. The basic form is y = GRNN (P, t, spread). You can use help GRNN to see the specific usage. The prediction accuracy of GRNN is good
generalized RBF network: from the input layer to the hidden layer is equivalent to mapping the data in the low dimensional space to the high dimensional space, and the number of cells in the input layer is the dimension of the sample, so the number of cells in the hidden layer must be more than that in the input layer. From the hidden layer to the output layer is the process of linear classification of data in high-dimensional space. The learning rules commonly used in single-layer perceptron can be used. See neural network foundation and perceptron
note that the number of neurons in the hidden layer is greater than that in the input layer, and it is not equal to the number of input samples. In fact, it is much less than the number of samples. Because in the standard RBF network, when the number of samples is large, many basis functions are needed, the weight matrix will be large, the calculation is complex and prone to ill conditioned problems. In addition, compared with the traditional RBF network, the wide RBF network has the following differences:
1. The center of the radial basis function is no longer limited to the input data points, but determined by the training algorithm
2. The expansion constant of each radial basis function is no longer unified, but determined by the training algorithm
3. The linear transformation of the output function contains threshold parameter, which is used to compensate the difference between the average value of the basis function on the sample set and the target value
therefore, the design of generalized RBF network includes:
1. Structure design -- the hidden layer contains several nodes, which is suitable
2. Parameter design -- the data center and expansion constant of each basis function, and the weight of output nodes.
but there is no problem, so it can not be determined
few investors and poor liquidity; Lack of supervision and serious manipulation.