What is a neural network algorithm?
Neural network is a fashionable word in the field of new technologies. Many people have heard this term, but few actually understand what it is. The purpose of this article is to introduce all the basics about neural networks including their functions, general structure, related terminology, types and their applications.
The word "neural network" actually comes from biology, and the correct name of the neural network we are referring to should be "artificial neural networks (ANNs)".
A true neural network is made up of several to billions of cells called neurons (the tiny cells that make up our brains), which are connected in different ways to form a network. Artificial neural networks attempt to simulate this biological architecture and its operation. There's a conundrum here: we don't know much about biological neural networks! Therefore, neural network architectures vary greatly between different types, and all we know is the basic structure of neurons.
Neural algorithms in search engines:
Compare the search engine algorithm to the human brain. There are about 50 to 500 different types of neurons in the brain, which are composed of N many factors to form a neural network system, which is the search engine algorithm. Fengcai Yiyang believes that in the search engine neural network system, a search engine neural algorithm is composed of N websites/pages related to keywords, and each neuron accounts for a different proportion in the neural network system. Of course, some search engines have recently added user behavior algorithms, and user behavior algorithms will also be incorporated into neural algorithms.
The principle of neural algorithm:
Basic neurons include synapses, soma, axons and dendrites. Synapses are responsible for the connections between neurons. They are not directly physically connected, but there is a small gap between them that allows electrical signals to jump from one neuron to another. These electronic signals are then handed over to soma for processing and its internal electronic signals transmit the processing results to axon. Axon will distribute these signals to dendrites. Finally, dendrites take these signals and pass them on to other synapses, and the cycle continues. Continuously mine data from each neuron to form each classification and coding. Each classification is encoded to form some general components of the search engine neural algorithm. Finally, the analysis results are formed into a neural fingerprint. When the user searches, the search engine's neural algorithm will be called. Fingerprints, displayed by neural finger tomb search results.