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Soft computing model using cluster-PCA in port model for throughput forecasting

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Abstract

In the sequence of port throughput analysis, many nonlinear and fluctuation signals are included in order to find the accuracy of port. Besides the socioeconomic factors, the virtually decision making and execution are considered as some kind of forecast. The seasonality and volatility are the critical issues in predicting the efficiency. The forecasting is a useful tool to cross these issues. The forecasting uses many qualitative and casual models and performs time series analysis to find the information about events, pattern changes, relationship between the system elements. It assumes two different kinds of phenomena share the same model of behavior. One is to promote new issues and another is to predict the outcome of the analysis. The judgmental forecasting technique is based on present situation and past situation in order to predict the issues in port. To deal with these issues, this paper addresses a method of hyperchaotic model for optimizing the throughput based on PCA. We review the latest models to provide the theoretical basis and propose novel ideas; the proposed methodology is simulated compared with the other state-of-the-art approaches. The experimental analysis proves the robustness of the model. In the future, more scenarios will be tested.

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Acknowledgements

This research is supported by The National Natural Science Foundation of China Youth Project (41401120) and basic research business fees of central universities (2014B00214).

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Authors and Affiliations

  1. College of Harbour, Coastal and Offshore Engineering, Hohai University, Nanjing, China

    Liupeng Jiang & He Jiang

  2. GoPerception Lab, Ithaca, USA

    Harry Haoxiang Wang

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  1. Liupeng Jiang
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  2. He Jiang
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  3. Harry Haoxiang Wang
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Correspondence to Liupeng Jiang.

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Jiang, L., Jiang, H. & Wang, H.H. Soft computing model using cluster-PCA in port model for throughput forecasting. Soft Comput 24, 14167–14177 (2020). https://doi.org/10.1007/s00500-020-04786-y

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