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This is a Quantitative Study study.

Quantitative analysis of landscape morphology using improved self-organizing mapping network

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Quantitative analysis finds improved self-organizing mapping enhances clustering performance, indicating better landscape management implications.

Improved self-organizing mapping demonstrates clustering accuracy of 0.934, indicating its effectiveness.
The method incorporates K-means algorithm after factor analysis for dimensionality reduction.
Assessment on the Iris dataset shows significant enhancement in contour score and adjusted Rand index.
Findings support the potential for improved landscape management in polder areas through effective quantification.

Wu et al. (2025) studied this question.

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Quantitative analysis finds improved self-organizing mapping enhances clustering performance, indicating better landscape management implications.