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Sensors and Materials, Volume 31, Number 6(1) (2019)
Copyright(C) MYU K.K.
S&M1907 Research Paper of Special Issue
Published: June 7, 2019
Intelligent Prediction Method for Transport Resource Allocation [PDF]
Yan Kong and Shuzhen Pan
(Received February 19, 2019; Accepted April 18, 2019)
Keywords: cooperative resource allocation, recurrent neural network, linear programming
In transport environments, the resources are owned by independent organizations that always need to work cooperatively to finish some tasks to achieve social welfare. However, social welfare may not be achieved owing to the absence of required resources. In addition, traffic is not regular enough to deal with all of the unpredicted and dynamically occurring tasks, and the unpredictability and dynamism of tasks are big challenging issues in resource allocation. Focusing on these challenges, in this paper, we propose a prediction model based on backpropagation neural network (BPNN) learning-based resource requirement prediction and linear programming, which address the resource requirement and the cooperation of resources, respectively. Evaluation results proved that the proposed prediction-based model was efficient for applications in resource utility.
Corresponding author: Shuzhen Pan
This work is licensed under a Creative Commons Attribution 4.0 International License.
Cite this article
Yan Kong and Shuzhen Pan, Intelligent Prediction Method for Transport Resource Allocation, Sens. Mater., Vol. 31, No. 6, 2019, p. 1917-1925.
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