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Design and Construction of Intelligent Decision-Making System for Marine Protection and Law Enforcement

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Advances on Broad-Band Wireless Computing, Communication and Applications (BWCCA 2019)

Part of the book series: Lecture Notes in Networks and Systems ((LNNS,volume 97))

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Abstract

Marine protection is closely related to the sustainable development of mankind. At present, CHINA COAST GUARD, an important functional department in the business of marine protection in China, mainly relies on manual work in the process of marine protection and law enforcement, which is inefficient and risky. In order to solve this problem, this paper presents a design framework of an intelligent decision-making system for marine protection and law enforcement. By using Internet of Things, Artificial Intelligence, Natural Language Processing and other advanced technologies, the decision-making system can automatically push intelligent punishment measures for marine protection and law enforcement through automatic matching with maritime laws and regulations. The design idea of this paper can also be extended to the assistant decision-making in other domains.

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References

  1. Rikalovic, A.M., Cosic, I., Labati, R.D., et al.: Intelligent decision support system for industrial site classification: a GIS-based hierarchical neuro-fuzzy approach. IEEE Syst. J. 99, 1–12 (2017)

    Google Scholar 

  2. Bykov, A.V., Burmaka, A.A., Korenevskaya, S.N., et al.: An intelligent decision support system for managing patients with lower limb ischemia based on hybrid fuzzy models. Biomed. Eng. 52(4), 271–274 (2018)

    Article  Google Scholar 

  3. Zamani Sabzi, H., King, J.P., Abudu, S.: Developing an intelligent expert system for streamflow prediction, integrated in a dynamic decision support system for managing multiple reservoirs: a case study. Expert Syst. Appl. 83, 145–163 (2017)

    Article  Google Scholar 

  4. Shin, S.J., Kim, D.B., Shao, G., Brodsky, A., et al.: Developing a decision support system for improving sustainability performance of manufacturing processes. J. Intell. Manuf. 28, 1421–1440 (2017)

    Article  Google Scholar 

  5. Galván, B.J., Marco, A.S., Rolin, J.F., et al.: NeXOS contribution to the adaptation of system analysis engineering tools for mature and reliable ocean sensors. In: Sensor Systems for a Changing Ocean (2015)

    Google Scholar 

  6. Arabshahi, P., Chao, Y., Chien, S., et al.: A smart sensor web for ocean observation: integrated acoustics, satellite networking, and predictive modeling. In: Agu Fall Meeting (2013)

    Google Scholar 

  7. Suja, K.J., Chaudhary, B.P., Komaragiri, R.: Design and simulation of pressure sensor for ocean depth measurements. Appl. Mech. Mater. 313–314, 666–670 (2013)

    Article  Google Scholar 

  8. Oliva, J., Serrano, J.I., Del Castillo, M.D., et al.: SyMSS: a syntax-based measure for short-text semantic similarity. Data Knowl. Eng. 70(4), 390–405 (2011)

    Article  Google Scholar 

  9. Zhu, T.T., Lan, M.: Measuring short text semantic similarity using multiple measurements. In: International Conference on Machine Learning & Cybernetics. IEEE, Piscataway (2014)

    Google Scholar 

  10. Shajalal, M., Aono, M.: Semantic textual similarity between sentences using bilingual word semantics. In: Progress in Artificial Intelligence (2019)

    Article  Google Scholar 

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Acknowledgments

This work was supported by National Key Research and Development Program of China under Grant 2017YFC1405403; National Natural Science Foundation of China under Grant 61075059; Philosophical and Social Sciences Research Project of Hubei Education Department under Grant 19Q054; Green Industry Technology Leading Project (product development category) of Hubei University of Technology under Grant CPYF2017008; Research Foundation for Advanced Talents of Hubei University of Technology under Grant BSQD12131; Natural Science Foundation of Anhui Province under Grant 1708085MF161; and Key Project of Natural Science Research of Universities in Anhui under Grant KJ2015A236.

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Authors and Affiliations

  1. School of Computer Science, Hubei University of Technology, Wuhan, China

    Na Deng & Caiquan Xiong

  2. School of Information and Safety Engineering, Zhongnan University of Economics and Law, Wuhan, China

    Xu Chen

Authors
  1. Na Deng
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  2. Xu Chen
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  3. Caiquan Xiong
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Corresponding author

Correspondence to Na Deng .

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Editors and Affiliations

  1. Department of Information and Communication Engineering, Fukuoka Institute of Technology, Fukuoka, Japan

    Leonard Barolli

  2. Department of Electronics, University of Antwerp, Antwerp, Belgium

    Peter Hellinckx

  3. Rissho University, Tokyo, Japan

    Tomoya Enokido

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Deng, N., Chen, X., Xiong, C. (2020). Design and Construction of Intelligent Decision-Making System for Marine Protection and Law Enforcement. In: Barolli, L., Hellinckx, P., Enokido, T. (eds) Advances on Broad-Band Wireless Computing, Communication and Applications. BWCCA 2019. Lecture Notes in Networks and Systems, vol 97. Springer, Cham. https://doi.org/10.1007/978-3-030-33506-9_75

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  • DOI: https://doi.org/10.1007/978-3-030-33506-9_75

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-030-33505-2

  • Online ISBN: 978-3-030-33506-9

  • eBook Packages: EngineeringEngineering (R0)

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