Title
Evolutionary fuzzy hybrid neural network for project cash flow control
Abstract
This paper develops an evolutionary fuzzy hybrid neural network (EFHNN) to enhance project cash flow management. The developed EFHNN combines neural networks (NN) and high order neural networks (HONN) into a hybrid neural network (HNN), which acts as the major inference engine and operates with alternating linear and nonlinear NN layer connections. Fuzzy logic is employed to sandwich the HNN between a fuzzification and defuzzification layer. The authors developed and applied the EFHNN to sequential cash flow trend problems by fusing HNN, FL, and GA. Results show that the proposed EFHNN can be deployed effectively to sequential cash flow estimation. The performance of linear and nonlinear (high order) neuron layer connectors in the EFHNN was significantly better than the performance achieved by previous models that used singular linear NN. Trained results were used for the prediction and strategic management of project cash flow. The proposed strategy can assist project managers to control project cash flows within the banana envelope of the S-curve to enhance project success.
Year
DOI
Venue
2010
10.1016/j.engappai.2009.10.003
Eng. Appl. of AI
Keywords
Field
DocType
proposed efhnn,high order neural network,cash flow estimation,project cash flow management,project manager,cash flow trend problem,project cash flow control,evolutionary fuzzy hybrid neural,project success,developed efhnn,project cash flow,fuzzy logic,s curve,neural network,cash flow,genetic algorithm,strategic management
Mathematical optimization,Defuzzification,Computer science,Fuzzy logic,Fuzzy set,Hybrid neural network,Artificial intelligence,Artificial neural network,Cash flow forecasting,Genetic algorithm,Machine learning,Cash flow
Journal
Volume
Issue
ISSN
23
4
Engineering Applications of Artificial Intelligence
Citations 
PageRank 
References 
7
0.57
5
Authors
3
Name
Order
Citations
PageRank
Min-Yuan Cheng117419.84
Hsing-Chih Tsai219114.26
Erick Sudjono3181.30