Artificial intelligence optimization method based on BP neural network

A BP neural network and artificial intelligence technology, applied in the field of artificial intelligence optimization based on BP neural network, can solve problems such as unfavorable use by users, and achieve the effects of high accuracy, convenient use, and low probability of errors.

Inactive Publication Date: 2017-09-12
JINPENG ELECTRONICS INFORMATION MACHINE
View PDF3 Cites 4 Cited by
  • Summary
  • Abstract
  • Description
  • Claims
  • Application Information

AI Technical Summary

Problems solved by technology

[0002] The development of contemporary artificial intelligence technology is not perfect. Users will encounter many problems in the process of using artificial intelligence machines, and artificial intelligence systems will also make many mistakes, which is extremely unfavorable to users. Therefore, how to optimize artificial intelligence and improve artificial intelligence? The accuracy and execution speed of intelligence have become the main problems in the current artificial intelligence research

Method used

the structure of the environmentally friendly knitted fabric provided by the present invention; figure 2 Flow chart of the yarn wrapping machine for environmentally friendly knitted fabrics and storage devices; image 3 Is the parameter map of the yarn covering machine
View more

Examples

Experimental program
Comparison scheme
Effect test

Embodiment 1

[0018] A kind of artificial intelligence optimization method based on BP neural network of the present invention, its steps are as follows:

[0019] Step 1. For each operation in the artificial intelligence system, the user inputs corresponding commands in the artificial intelligence system, establishes an operation and command set mapping pair through the artificial intelligence system, and uses it as the original training set of the BP neural network. Training, the command is the original command information input by the user, and the artificial intelligence system performs preprocessing and feature parameter extraction to it, and the extracted feature parameter value is input to the input end of the BP neural network;

[0020] Step 2. The user inputs command data to the artificial intelligence system. The artificial intelligence system first preprocesses the command data input by the user and extracts the characteristic parameter value of the command. The characteristic para...

Embodiment 2

[0024] A kind of artificial intelligence optimization method based on BP neural network of the present invention, its steps are as follows:

[0025] Step 1. For each operation in the artificial intelligence system, the user inputs corresponding commands in the artificial intelligence system, establishes an operation and command set mapping pair through the artificial intelligence system, and uses it as the original training set of the BP neural network. Training, the command is the original command information input by the user, and the artificial intelligence system performs preprocessing and feature parameter extraction to it, and the extracted feature parameter value is input to the input end of the BP neural network;

[0026] Step 2. The user inputs command data to the artificial intelligence system. The artificial intelligence system first preprocesses the command data input by the user and extracts the characteristic parameter value of the command. The characteristic para...

Embodiment 3

[0030] A kind of artificial intelligence optimization method based on BP neural network of the present invention, its steps are as follows:

[0031] Step 1. For each operation in the artificial intelligence system, the user inputs corresponding commands in the artificial intelligence system, establishes an operation and command set mapping pair through the artificial intelligence system, and uses it as the original training set of the BP neural network. Training, the command is the original command information input by the user, and the artificial intelligence system performs preprocessing and feature parameter extraction to it, and the extracted feature parameter value is input to the input end of the BP neural network;

[0032] Step 2. The user inputs command data to the artificial intelligence system. The artificial intelligence system first preprocesses the command data input by the user and extracts the characteristic parameter value of the command. The characteristic para...

the structure of the environmentally friendly knitted fabric provided by the present invention; figure 2 Flow chart of the yarn wrapping machine for environmentally friendly knitted fabrics and storage devices; image 3 Is the parameter map of the yarn covering machine
Login to view more

PUM

No PUM Login to view more

Abstract

The invention discloses an artificial intelligence optimization method based on a BP neural network. The artificial intelligence optimization method based on the BP neural network comprises the following steps that a user respectively inputs corresponding commands in an artificial intelligence system by aiming at each operation in the artificial intelligence system; the operation and command set mapping pair is built through the artificial intelligence system and is used as an original training set of the BP neural network; the BP neural network is trained; the command is original command information input by the user; the artificial intelligence system performs preprocessing and feature parameter extraction on the command; the extracted feature parameter value is input into the input end of the BP neural network; in the operation and command set mapping pair creating process, the command input by the user is used as the original training set; the error making probability of the artificial intelligence in the command execution process becomes smaller; the execution speed is high; the accuracy is high; the same operation can be controlled by various commands, so that the use of the artificial intelligence is more convenient; the efficiency value of the artificial intelligence is improved.

Description

technical field [0001] The invention relates to the technical field of artificial intelligence equipment, in particular to an artificial intelligence optimization method based on a BP neural network. Background technique [0002] The development of contemporary artificial intelligence technology is not perfect. Users will encounter many problems in the process of using artificial intelligence machines, and artificial intelligence systems will also make many mistakes, which is extremely unfavorable to users. Therefore, how to optimize artificial intelligence and improve artificial intelligence? The accuracy and execution speed of intelligence have become the main issues in the current artificial intelligence research. Contents of the invention [0003] The purpose of the present invention is to provide a kind of artificial intelligence optimization method based on BP neural network, to solve the problem proposed in the above-mentioned background technology. [0004] In ord...

Claims

the structure of the environmentally friendly knitted fabric provided by the present invention; figure 2 Flow chart of the yarn wrapping machine for environmentally friendly knitted fabrics and storage devices; image 3 Is the parameter map of the yarn covering machine
Login to view more

Application Information

Patent Timeline
no application Login to view more
Patent Type & Authority Applications(China)
IPC IPC(8): G10L15/22G10L15/16G10L15/06
Inventor 冯力魏一
Owner JINPENG ELECTRONICS INFORMATION MACHINE
Who we serve
  • R&D Engineer
  • R&D Manager
  • IP Professional
Why Eureka
  • Industry Leading Data Capabilities
  • Powerful AI technology
  • Patent DNA Extraction
Social media
Try Eureka
PatSnap group products