Create a neural-network-inspired model specifically designed for cost estimation from the principle of artificial neural networks and a recognized cost estimation model. We select the Time-Driven Activity-based Costing, as a cost estimation framework for our model because it covers the cost both directly and indirectly way, and structures can apply to the structure of artificial neural networks. We propose to create a simple, specific, explainable, and accurate results.
Conference Paper in Genetic and Evolutionary Computing, in series of Lecture Notes in Electrical Engineering (LNEE,volume 1321), Springer, Since 8 Febuaray 2025 and Presentation at International Conference on Genetic and Evolutionary Computing 2024 (ICGEC-2024), Miyazaki, Japan 28 August 2024
Savastham, T., Suvonvorn, N. (2025). Time-Driven Cost Estimation Learning Model. In: Pan, JS., Zin, T.T., Sung, TW., Lin, J.CW. (eds) Genetic and Evolutionary Computing. ICGEC 2024. Lecture Notes in Electrical Engineering, vol 1321. Springer, Singapore. https://doi.org/10.1007/978-981-96-1531-5_26