Artificial Intelligence Models in Pattern Recognition
Mohammed Rashad Baker, Umesh Solanki · 2024
Pattern recognition is a complicated process that involves analyzing the data that are being inputted, removing patterns from the data, attempting to compare the patterns to specific standards, and employing the findings to guide the actions that the system will take in the future. Pattern recognition analyzes how robots will monitor their environment and will be able to recognize patterns of interest from the patterns in their environment and then reach logical and acceptable judgments about the groups to which the patterns belong. Developing a pattern recognizer that any machine can utilize has been the subject of investigation for nearly a decade. Artificial intelligence (AI) is promising as an effective alternative to traditional modelling methods. AI is a subfield of computer science that involves the building of intelligent machines and software. It offers advantages over conventional approaches for dealing with problems involving uncertainty, and it is an excellent tool for solving such complicated challenges. Moreover, AI-based solutions are important options for determining variables related to engineering design when testing is impossible, resulting in substantial savings in human time and testing effort. AI can also expedite decision-making, minimize errors, and boost computational effectiveness. Therefore, AI and patten recognition have recently attracted increasing interest and are emerging as new categories of intelligent structural engineering solutions. This chapter presents the details of pattern recognition concepts. It will give an overview of pattern recognition and recent works related to this concept before discussing the most critical AI techniques for pattern recognition. Then, it will discuss how AI and pattern recognition can work together to address a complex problem.