Seele's neural cosensus algorithm, blockchain 4.0

The human brain is the most fascinating organ know to man, with advancements in science and technology , scientist are still yet to uncover 20% of the brain’s unique capacity,
We all know the brain to be the command centre of the human being with it directing every movement and cognitive reason, it is able to do this effectively with the help of a network of neurons which serve as messenger,conveying messages to and fro the Brain,hence its uniqueness.

Similar to this way, this is how seele’s neural consensus algorithm works,
Basically the popular consensus algorithms such as proof of work(pow) similar to bitcoin, proof of stake (pos) aren't enough in terms of scalability and efficiency and security.
Bitcoins proof of work algorithm (pow) provides answers to the question ofscalability and safety but not efficiency whereas the proof of stake algorithm meets the need for scalability and efficiency but not security
But with seele's neural consensus algorithm it meets the requirements of scalability, efficiency and security

How does neural consensus algorithm work?
The ability to come to a consensus for a decentralized blockchain is somewhat far fetched, as there may be issues of high computational overhead similar to bitcoin's proof of work and also the issue of unfaithful nodes.
However seele uses in lieu with neural consensus algorithm also ε-differential agreement which is a maths sequence that sums up the entire network nodes into a single value, (just like finding the mean of an ordered set of values in statistics)
With EDA every node in the network will achieve consensus faster, also the parameters of EDA can also be adjusted to ensure efficiency in different applications

Eda parameters

1. S: this is the percentage of nodes that are sampled by every node, during each round
2. E: target convergence interval for the network’s value,when all nodes are within the e-differential, the node is said to be in consensus
3. r: this is the number of rounds of voting the system conducts
   

One of the most important feature of this algorithm is its linear scalability which means that an increase in node size leads to a corresponding increase in performance, which in turn translates to the larger the node size the faster the convergence and performance, also there is the unique feature of data independence makes is very acceptable in almost all platforms such as finance, commerce and traceability.

Major features of neural consensus algorithm
Energy reduction- contrary to proof of work and proof of stake which requires constant supply of power in order to keep the nodes alive, to reduce energy consumption, operations and sequencing are based on integer arithmetic which requires extremely low performance of nodes thereby reducing economic costs

Low transmission overhead - due to its semi dependence, i.e it reduces the nodes dependence on system’s structure

Adjustable parameters - just as the brain sends signals to the body telling it to adjust in certain conditions, neural consensus efficiency parameters can be adjusted with respect to its environment,thereby increasing efficiency.

Other features include
Change of cosensus process to continuous voting
Compatibility with other network structures

For more information
Official website
https://seele.pro
Whitepaper
https://s3.ap-northeast-2.amazonaws.com/wp.s3.seele.pro/Seele_tech_whitepaper_EN_v2.0.pdf
Medium page
https://medium.com/seeletech
Facebook page
https://facebook.com/seeletech