Integrating Artificial Neural Networks with MOORA Method for Construction Material Selection

Artificial neural networks (ANNs) are designed to mimic the complex and flexible structure of the human brain, serve as powerful tools for addressing complex, nonlinear challenges in a variety of domains. This review examines the development, operation, and practical applications of ANNs, focusing on their potential to solve important problems in medical science—particularly within the realm of gastrointestinal research. While basic scientific knowledge has advanced significantly, progress in the clinical management of gastrointestinal diseases has been limited. ANNs present a promising approach because they can learn from data, detect patterns, and make predictions without requiring prior assumptions about the data distribution—providing a distinct advantage over traditional parametric methods. This review emphasizes the importance of selecting appropriate ANN architectures and optimizing their parameters to suit specific problems. However, an optimized neural network represents only the initial stage; its successful application depends on integration into comprehensive decisionsupport systems. Furthermore, this paper highlights the combined potential of combining ANNs with Multi-criteria decision-making approaches - particularly the multi-objective optimization by ratio analysis (MOORA) method - improve problem-solving and decision-making in complex, data-intensive systems. MOORA method enhances ANN-driven applications by providing a structured and efficient framework for evaluating multiple criteria, making them particularly valuable in areas such as material selection, project planning, and performance evaluation. Combining ANNs with other advanced computational techniques – such as fuzzy logic and evolutionary algorithms – further increases their robustness and adaptability. This study addresses common misconceptions about the capabilities of ANNs, encouraging more realistic and practical expectations regarding their implementation. By leveraging ANN properties that mimic the human brain – adaptability, fault tolerance, and the ability to manage uncertain or incomplete information – researchers and experts can build intelligent, high-performance systems. Ultimately, the study underscores the role of ANNs in improving decision-making and driving innovation in a wide range of fields, from healthcare to industrial manufacturing.