Assessing Credit Risk in Construction Contracts with Fuzzy Genetic Modeling: A New Platform Design
Keywords:
Credit Risk Assessment, Construction Contracts, Fuzzy Logic, Genetic Algorithms, Risk ManagementAbstract
This essay outlines the design and development of a novel platform for assessing credit risk in construction contracts using fuzzy genetic modeling. The platform integrates the strengths of fuzzy logic and genetic algorithms to enhance the accuracy and comprehensiveness of risk assessments. Beginning with stakeholder engagement and requirement gathering, the process encompasses data collection and preprocessing, development of the fuzzy logic model, and integration of genetic algorithms for optimization. The platform features a robust system architecture, including a database, processing engines, and user interfaces designed for intuitive use. Rigorous implementation and testing phases ensure seamless functionality and reliability. Deployment strategies, user training, and comprehensive documentation support effective utilization. Continuous monitoring and iterative improvements maintain the platform's relevance and accuracy. By addressing both technical and financial aspects, this platform aims to significantly improve decision-making and risk management in construction projects, benefiting professionals in civil engineering and accounting.
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