AI Neural Network Expert System Development
- Indbinding:
- Paperback
- Sideantal:
- 156
- Udgivet:
- 3. juli 2023
- Størrelse:
- 152x9x229 mm.
- Vægt:
- 237 g.
- 2-3 uger.
- 26. november 2024
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- 1 valgfrit digitalt ugeblad
- 20 timers lytning og læsning
- Adgang til 70.000+ titler
- Ingen binding
Abonnementet koster 75 kr./md.
Ingen binding og kan opsiges når som helst.
Beskrivelse af AI Neural Network Expert System Development
This Focuses on the development of an expert system utilizing artificial intelligent neural networks. Expert systems are computer-based programs designed to mimic human expertise in a specific domain. By integrating advanced neural network algorithms, this research aims to enhance the capabilities of expert systems and improve their accuracy and efficiency.
Artificial intelligent neural networks are powerful tools that can learn from data, recognize patterns, and make intelligent decisions. By leveraging the capabilities of neural networks, the developed expert system can analyze complex information, extract relevant features, and provide expert-level recommendations or solutions.
The integration of artificial intelligence techniques in expert systems enables them to adapt and learn from new data, making them more robust and capable of handling dynamic environments. This interdisciplinary approach combines expertise from computer science, machine learning, and domain-specific knowledge to develop a cutting-edge system.
The outcome of this research has significant implications across various domains, including healthcare, finance, engineering, and more. The developed expert system can assist professionals in decision-making, problem-solving, and optimizing complex processes. Ultimately, this study contributes to the advancement of artificial intelligence technologies and their practical applications in expert systems.
Artificial intelligent neural networks are powerful tools that can learn from data, recognize patterns, and make intelligent decisions. By leveraging the capabilities of neural networks, the developed expert system can analyze complex information, extract relevant features, and provide expert-level recommendations or solutions.
The integration of artificial intelligence techniques in expert systems enables them to adapt and learn from new data, making them more robust and capable of handling dynamic environments. This interdisciplinary approach combines expertise from computer science, machine learning, and domain-specific knowledge to develop a cutting-edge system.
The outcome of this research has significant implications across various domains, including healthcare, finance, engineering, and more. The developed expert system can assist professionals in decision-making, problem-solving, and optimizing complex processes. Ultimately, this study contributes to the advancement of artificial intelligence technologies and their practical applications in expert systems.
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