Research and application of rule updating mining algorithm for marine water quality monitoring data

• Autorzy: Sun Q , Zhang J. , Xu X

Identyfikatory

DOI

10.2478/pomr-2018-0122

• Języki publikacji: EN

Abstrakty

EN

This paper studies the characteristics of marine water quality monitoring data monitored by photoelectric sensor network, mines the potential information from the massive data. on account of the continuous accumulation of monitoring data, this paper focuses on the study of database with numerical attribute and proposes a rule updating algorithm for solving the rule maintenance issues caused by changes in the database. according to the rule, the algorithm forms a new database from part of the original data and the new data, and searches the new database by random search, thus can avoid creating a large number of redundant rules and can quickly mine effective rules at the same time. experimental results show that this method not only can avoid mining in the whole original massive data, but also can improve work efficiency, and can quickly and effectively find new data and find useful rules in the data with high practicability.

Słowa kluczowe

EN

marine water quality monitoring; database updating; data mining; rule updating

• Wydawca: Gdańsk University of Technology, Faculty of Ocean Engineering & Ship Technology
• Czasopismo: Polish Maritime Research
• Rocznik: 2018
• Tom: S 3
• Strony: 136--140
• Opis fizyczny: Bibliogr. 21 poz., tab.

Twórcy

autor

Sun Q

• Postdoctoral research station of Geography Hebei Normal University Shijiazhuang 050024 China
• Hebei University of Science and Technology, Shijiazhuang, China

autor

Zhang J.

• Postdoctoral research station of Geography Hebei Normal University Shijiazhuang 050024 China

autor

Xu X

• State Grid Hebei Electric Power Research Institute, Shijiazhuang, China

Bibliografia

• 1. J. Wang, F. Zhang, and F. Liu, Hybrid Forecasting Modelbased Data Mining and Genetic Algorithm-adaptive Particle Swarm Optimisation: A Case Study of Wind Speed Time Series, IET Renewable Power Generation, Vol. 10, No. 3, pp. 287–298, 2016.
• 2. C. K. Huynh, and W. C. Lee, An Interference Avoidance Method using Two-Dimensional Genetic Algorithm for Multicarrier Communication Systems, Journal of Communications and Networks, Vol. 15, No. 5, pp. 486–495, 2013.
• 3. H. Ghorbaninejad, and R. Heydarian, New Design of Waveguide Directional Coupler using Genetic Algorithm, IEEE Microwave and Wireless Components Letters, Vol. 26, No. 2, pp. 86–88, 2016.
• 4. M. M. Abouelsaad, M. A. Abouelatta, and A. R. Salama, Genetic Algorithm-optimised Charge Simulation Method for Electric Field Modelling of Plate-Type Electrostatic Separators, IET Science, Measurement & Technology, Vol. 7, No. 1, pp. 16–22, 2013.
• 5. B. Mohammadi-Ivatloo, A. Rabiee, and A. Soroudi, Nonconvex Dynamic Economic Power Dispatch Problems Solution using Hybrid Immune-Genetic Algorithm, IEEE Systems Journal, Vol. 7, No. 4, pp. 777–785, 2013.
• 6. W. H. Ip, D. Wang, and V. Cho, Aircraft Ground Service Scheduling Problems and Their Genetic Algorithm with Hybrid Assignment and Sequence Encoding Scheme, IEEE Systems Journal, Vol. 7, No. 4, 649–657, 2013.
• 7. S. H. Chung, and H. K. Chan, A Two-Level Genetic Algorithm to Determine Production Frequencies for Economic Lot Scheduling Problem, IEEE Transactions on Industrial Electronics, Vol. 59, No. 1, pp. 611–619, 2011.
• 8. W. Verly, L. R. Araujo, and D. R. R. Penido, A Method for Sizing of Industrial Electrical Systems using Genetic Algorithm, IEEE Latin America Transactions, Vol. 14, No. 2, pp. 681–686, 2016.
• 9. Y. Tominaga, Y. Okamoto, and S. Wakao, Binary-based Topology Optimization of Magnetostatic Shielding by a Hybrid Evolutionary Algorithm Combining Genetic Algorithm and Extended Compact Genetic Algorithm, IEEE Transactions on Magnetics, No. 49, No. 5, pp. 2093–2096, 2013.
• 10. T. Lu, and J. Zhu, Genetic Algorithm for Energy-Efficient QoS Multicast Routing, IEEE Communications Letters, Vol. 17, No. 1, 31-34, 2012.
• 11. L. Shi, Y. K. Deng, and H. F. Sun, An Improved Real-Coded Genetic Algorithm for the Beam Forming of Spaceborne SAR, IEEE Transactions on Antennas and Propagation, Vol. 60, No. 6, pp. 3034–3040, 2012.
• 12. K. Boudjelaba, F. Ros, and D. Chikouche, Adaptive Genetic Algorithm-based Approach to Improve the Synthesis of TwoDimensional Finite Impulse Response Filters, IET Signal Processing, Vol. 8, No. 5, pp. 429–446, 2014.
• 13. T. A. Mota, J. F. Leal, and A. C. Lima, Neural Equalizer Performance Evaluation using Genetic Algorithm, IEEE Latin America Transactions, Vol. 13, No. 10, pp. 3439–3446, 2015.
• 14. K. Thirugnanam, M. Singh, and P. Kumar, Mathematical Modeling of Li-Ion Battery using Genetic Algorithm Approach for V2G Applications, IEEE Transactions on Energy Conversion, Vol. 29, No. 2, pp. 332–343, 2014.
• 15. X. K. Wei, W. Shao, and C. Zhang, Improved Self-Adaptive Genetic Algorithm with Quantum Scheme for Electromagnetic Optimisation, IET Microwaves, Antennas and Propagation, Vol. 8, No. 12, pp. 965–972, 2014.
• 16. S. C. Sen, S. Kasim, M. F. Md Fudzee, R. Abdullah, and R. Atan, Random Walk from Different Perspective, Acta Electronica Malaysia, Vol. 1, No. 2, pp. 26–27, 2017.
• 17. B. Q. Li, and Z. Li (). Design of Automatic Monitoring System for Transfusion, Acta Electronica Malaysia, Vol. 2, No. 1, pp. 07–10, 2018.
• 18. X. N. Gu, Z. G. He, X. Y. Sun, J. Liu, and B. S. Wang, Algebraic dynamic multilevel (ADM) method for compositional multiphase flow simulation, Acta Mechanica Malaysia, Vol. 1, No. 1, pp. 01–03, 2017.
• 19. X. Luo, Research on Anti-Overturning Performance of Multi-Span Curved Girder Bridge with Small Radius, Acta Mechanica Malaysia, Vol. 1, No. 1, pp. 11–15.
• 20. S. K. Md Sa’at, and N. Qamaruzaman, Phytoremediation potential of palm oil mill effluent by constructed wetland treatment, Engineering Heritage Journal, Vol. 1, No. 1, pp. 49–54, 2017.
• 21. S. R. Hassan, N. Qamaruz Zaman, I. Dahlan, Influence of Seed Loads on Start Up of Modified Anaerobic Hybrid Baffled (MAHB) Reactor Treating Recycled Paper Wastewater, Engineering Heritage Journal, Vol. 1, No. 2, pp. 05–09, 2017.

Uwagi

Opracowanie rekordu w ramach umowy 509/P-DUN/2018 ze środków MNiSW przeznaczonych na działalność upowszechniającą naukę (2019).