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Correlation analysis between multifractal characteristics of regional geomorphology and development of geological disasters
Análisis de correlación entre las características multifractales de la geomorfología regional y el desarrollo de desastres geológicos
DOI:
https://doi.org/10.15446/esrj.v25n1.93700Keywords:
Multifractal characteristics of regional geomorphology, Development of geological disasters, Correlation, Accuracy (en)Características multifractales de la geomorfología regional, desarrollo de desastres geológicos, correlación, exactitud (es)
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In view of the inaccuracy of the traditional correlation analysis method, this paper proposes a correlation analysis method between the multifractal characteristics of regional landforms and the development of geological disasters. Firstly, the multifractal characteristics of regional landforms are described by using the basic fractal characteristics of self-similarity or scale invariance. Then the corresponding relation table is established according to the width of the fractal spectrum and the number of landslides and hidden dangers, and the spatial relationship of geological disaster development is analyzed. Combined with the above-mentioned spatial relationship of geological disaster development and the multifractal characteristic data of regional landforms, the correlation coefficient between the two is calculated to complete the correlation analysis between the multifractal characteristics of regional geomorphology and the development of geological disasters. The experimental results show that compared with the traditional correlation analysis method, the correlation analysis results of the multifractal characteristics of regional geomorphology and the development of geological disasters are more accurate.
Debido a la inexactitud del método de análisis de correlación tradicional, este artículo propone un método de análisis de correlación entre las características multifractales de accidentes geográficos regionales y el desarrollo de desastres geológicos. En primer lugar, las características multifractales de los accidentes geográficos regionales se describen a través de las características fractales básicas de autosemejanza o invariancia de escala. Luego se establece la tabla de relación correspondiente de acuerdo con el ancho del espectro fractal y el número de deslizamientos de tierra y peligros ocultos, y la relación espacial del desarrollo de desastres geológicos. Combinado con la relación espacial mencionada anteriormente del desarrollo de desastres geológicos y los datos característicos multifractales de accidentes geográficos regionales, el coeficiente de correlación entre los dos se calcula para completar el análisis de correlación entre las características multifractales de la geomorfología regional y el desarrollo de desastres geológicos. Los resultados experimentales muestran que en comparación con el método de análisis de correlación tradicional, los resultados del análisis de correlación de las características multifractales de la geomorfología regional y el desarrollo de desastres geológicos son más precisos.
References
Alejo, J., Montes-Rojas, G., & Sosa-Escudero, W. (2018). Testing for serial correlation in hierarchical linear models. Journal of Multivariate Analysis, 165, 101-116.
Ali, M. Y., & Lee, J. (2018). Petroleum geology of the nogal basin and surrounding area, northern somalia: part 1, stratigraphy and tectonic evolution. Journal of Petroleum Geology, 42(1), 91-120.
Benammi, M., Adnet, S., Marivaux, L., Yans, J., Noiret, C., Tabuce, R., Surault, J., El Kati, I., Enault, S., Baidder, L., Saddiqi, O. (2019). Geology, biostratigraphy and carbon isotope chemostratigraphy of the paleogene fossil-bearing dakhla sections, southwestern moroccansahara. Geological Magazine, 156(1), 117-132.
Chardon, D., Grimaud, J. L., Beauvais, A., & Bamba, O. (2018). West african lateritic pediments: landform-regolith evolution processes and mineral exploration pitfalls. Earth-Science Reviews, 179(4), 124-146.
Cheng, H. Y., & Liu, Y. N. (2020). An improved RSU-based authentication scheme for VANET. Journal of Internet Technology, 21(4).
Cui K., & Wang Y. X. (2019). Structural styles and origin of the Dabashan foreland arcuate belt and basin-mountain system in central China. Journal of Asian Earth Sciences, 176, 244-252.
Fan, A. H., Liao, L. M, & Wu, M. (2018). Multifractal analysis of some multiple ergodic averages in linear cookie-cutter dynamical systems. Mathematische Zeitschrift, 290(1-2), 63-81.
Galbraith, & de Lavergne, D. (2019). Response of a comprehensive climate model to a broad range of external forcings: relevance for deep ocean ventilation and the development of late cenozoic ice ages. Climate Dynamics, 52(1-2), 653-679.
Gao, N. S., Cheng, B. Z., Hou, H., & Zhang, R. H. (2018). Mesophase pitch based carbon foams as sound absorbers. Materials Letters, 212, 243-246. DOI: 10.1016/j.matlet.2017.10.074
Gao, N. S., Guo, X. Y., Cheng, B. Z., Zhang, Y. N., Wei, Z. Y., & Hou, H. (2019). Elastic Wave Modulation in Hollow Metamaterial Beam With Acoustic Black Hole. IEEE Access, 7, 124141-124146. DOI: 10.1109/access.2019.2938250
Hansen, N. E., Noesen, B. T. Nador, J. D., & Harel, A. (2018). The influence of behavioral relevance on the processing of global scene properties: an erp study. Neuropsychologia, 114, 168-168.
Kleemann, T., Strauss, M., Kouraki, K., Werner, N., & Zahn, R. (2019). Prognostic relevance of new onset arrhythmia and icd shocks in primary prophylactic icd patients. Clinical Research in Cardiology(337), 1-7.
Masson, M., Angot, H., Le Bescond, C., Launay, M., Dabrin, A., Miege, C., Le Coz, J., & Coquery, M. (2018). Sampling of suspended particulate matter using particle traps in the rhône river: relevance and representativeness for the monitoring of contaminants. Science of the Total Environment, 637-638, 538-549.
Leonarduzzi, R. F., Abry, P., Wendt, H., Jaffard, S., Touchette, H. (2018). A generalized multifractal formalism for the estimation of nonconcave multifractal spectra. IEEE Transactions on Signal Processing, 99, 1-1.
Sachica, M., & Martinez, A. (2018). Analysis of correlation in the intercomparison of dc voltage reference standards. IEEE Transactions on Instrumentation and Measurement, 99, 1-4.
Salin, B. M., Kemarskaya, O. N., & Salin, M. B. (2019). Estimating the amplitude of wind waves by correlation analysis of the reverberation signal. Acoustical Physics, 65(1), 41-51.
Soloviev, S. G., Kryazhev, S., & Dvurechenskaya, S. (2018). Geology, mineralization, and fluid inclusion study of the Kuru-Tegerek Au-Cu-Mo skarn deposit in the Middle Tien Shan, Kyrgyzstan. MineraliumDeposita, 80, 79-102.
Valenza, G., Wendt, H., Kiyono, K., Hayano, J., Watanabe, E., Yamamoto, Y., Abry, P., & Barbieri, R. (2018). Mortality prediction in severe congestive heart failure patients with multifractal point-process modeling of heartbeat dynamics. IEEE Transactions on Biomedical Engineering, 65(10), 2345-2354.
Wu, Z., Liu, Y. N., & Jia, X. X. (2020). A Novel Hierarchical Secret Image Sharing Scheme with Multi-Group Joint Management. Mathematics, 8(3), 12. DOI: 10.3390/math8030448
Yang, F., Yang, F., Wang, G. Y., Kong, T., Wang, H., & Zhang, C. S. (2020). Effects of water temperature on tissue depletion of florfenicol and its metabolite florfenicol amine in crucian carp (Carassius auratus gibelio) following multiple oral doses. Aquaculture, 515, 9. DOI: 10.1016/j.aquaculture.2019.734542
Zhang, L., Shi, Z. L., Cheng, M. M., Liu, Y., Bian, J. W., Zhou, J. T., Zheng, G., & Zeng, Z. (2019). Nonlinear regression via deep negative correlation learning. IEEE Transactions on Pattern Analysis and Machine Intelligence, 99, 1-1.
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