Design method of seabed landform type classifier based on factor analysis

Abstract

The invention discloses a method for designing a seabed landform type classifier based on factor analysis. The method comprises the following steps: 1) calculating depth distribution characteristics according to seabed depth measurement data, including skewness, kurtosis, seabed depth standard deviation, seafloor depth difference entropy, seafloor roughness and seafloor depth variation coefficient; 2) using depth distribution characteristics as the original 3) According to the geomorphic factors, use the support vector machine to design a geomorphic type classifier; 4) Calculate the depth distribution eigenvalues ​​and geomorphic factors of the geomorphology to be identified, and use the designed classifier to identify the geomorphic type. The invention has the advantages of simple method, small amount of calculation, high recognition accuracy, manpower saving and the like. The invention is applicable to the type identification of seabed topography.

Description

technical field The invention relates to the technical fields of marine surveying and mapping, marine engineering, marine oil and gas resources, etc., in particular to a design method of a seabed landform type classifier based on factor analysis. Background technique Geomorphology is the general term for various undulating shapes on the earth's surface. The types of submarine topography include paleochannels, scour troughs, submarine canyons, deep water channels, seamounts, carbonate platforms, cliffs, landslides, etc. Geomorphological classification is the basis of seabed geomorphological research and mapping. Geomorphic morphology can reflect the internal relationship between geomorphic genetic types and genetic control forms, and is the key to deep geological knowledge mining. The multi-beam sounding system can detect the fine features of the seabed topography and topography with wide coverage and high resolution. The system adopts strip measurement, which can simultan...

AI Technical Summary

Problems solved by technology

This method can make full use of the knowledge of technicians and has good flexibility, but it requires technicians to have rich geological knowledge and experience in observation and judgment, which has great subjectivity, poor timeliness, and high labor intensity.

Especially due to the massive level of seabed data, it is far from being able to undertake the processing tasks of massive data only relying on the artificial ability of technicians

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