1. Mathematical modeling: Mathematical modeling is one of the important methods of artificial intelligence research. It describes and simulates the problems in the real world by establishing mathematical models, and provides theoretical support for the design and optimization of artificial intelligence systems.
2. Data mining: Data mining is a process of extracting useful information from a large amount of data by using statistics and machine learning technology. In the field of artificial intelligence, data mining is widely used in classification, clustering, prediction and other tasks.
3. Machine learning: Machine learning is one of the hottest research directions in the field of artificial intelligence. It realizes the prediction and classification of unknown data by making the computer automatically learn rules and patterns from the data.
4. Natural language processing: Natural language processing is the process of making computers understand and process human language. Natural language processing technology, including speech recognition, natural language understanding, machine translation and so on, provides strong support for intelligent customer service, smart home and other fields.
5. Computer vision: Computer vision is the process of making computers have the same visual perception as human beings. Computer vision technology, including image recognition, target detection, scene understanding, etc. , widely used in autonomous driving, intelligent security and other fields. For example, the machine vision/natural language/generative artificial intelligence comprehensive application experimental platform is a comprehensive experimental equipment for artificial intelligence related majors, which consists of edge computing host, expansion module, industrial application suite and other parts. ERNIE Bot and other large models are supported, which can meet the teaching, experiment and training needs of core courses and specialized courses of artificial intelligence related majors, including: production artificial intelligence training, machine vision application technology, natural language application technology, etc.
6. Knowledge representation and reasoning: Knowledge representation and reasoning is a process that enables computers to understand and use human knowledge. Knowledge representation and reasoning techniques include conceptual modeling. Knowledge map, etc. It provides strong support for intelligent question answering and intelligent decision-making.
7. Reinforcement learning: Reinforcement learning is a process of automatically learning how to complete tasks in the best way by making computers interact with the environment. Reinforcement learning technology, including deep reinforcement learning Q-learning, provides a new idea for the field of game ai autopilot.
8. Fuzzy logic: Modular boron logic is a kind of bait, which can deal with the problem of uncertainty. It breaks through the law of excluded middle of classical logic and allows the uncertainty in logical expressions to be described by modular sets and membership functions. Fuzzy logic is applied in the field of artificial intelligence, such as control system design and image processing.
These research approaches and methods have their own advantages and disadvantages in different application scenarios, and the selection and combination of research methods is very important for the design and implementation of dry artificial intelligence system. At the same time, these research approaches and methods are constantly developing and improving, which provides more possibilities for the research and application of artificial intelligence.