Analysis of Soil Fertility Based on FUMF Algorithm
The soil nutrition is an important indicator of soil fertility. The method K-means and FCM are always used to evaluating the soil fertility, but the cluster number need to be set, and the outlier couldn’t be eliminated accurately, and there is the deviati
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Institute of Scientific and Technical Information of Jilin, Changchun 130033, China [email protected], [email protected] 2 College of Information Technology, Jilin Agricultural University, Changchun 130118, China [email protected], [email protected], {65447539,45515189,419513823}@qq.com
Abstract. The soil nutrition is an important indicator of soil fertility. The method K-means and FCM are always used to evaluating the soil fertility, but the cluster number need to be set, and the outlier couldn’t be eliminated accurately, and there is the deviation between the real result and the soil fertility. So the paper applied the FUMF to analysis the soil nutrient data of Nong An county for eight years, 2005–2012. The result show that the low fertility soils gradually decreased from 2005 to 2012 by precision fertilization, and the moderate and high fertility soil was rising, the overall soil fertility of Nong An had improved significantly. The analysis result was consistent with the actual situation, The FUMF algorithm is proved that was an effective evaluate method of the soil fertility evaluation. It has the practical significance to analyze the large number of soil fertility of high complexity and interactive, it also provided the technical support for precision fertilization decision-making. Keywords: Fuzzy clustering fertilization FUMF
Soil fertility
Fertility analysis
Precision
1 Introduction Soil nutrient content is an important symbol of fertility and productivity of arable land, also it is an important indicator of soil fertility evaluation. With the arrival of precision agriculture era, spatial variability and correlations of wide variety agricultural data which have complex links relationship are more significantly. The attendant massive, diverse and dynamic changes, incomplete, uncertain and a series of characteristics. Since the 1990s, Data Mining and geographic information systems technology in the agricultural sector has been increasingly widely used. DM and GIS technology can effectively statistics and analysis of massive, complex data. DM Clustering algorithms can dig out the knowledge of soil fertility evaluation from soil nutrient data analysis.
© IFIP International Federation for Information Processing 2016 Published by Springer International Publishing AG 2016. All Rights Reserved D. Li and Z. Li (Eds.): CCTA 2015, Part I, IFIP AICT 478, pp. 564–573, 2016. DOI: 10.1007/978-3-319-48357-3_53
Analysis of Soil Fertility Based on FUMF Algorithm
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Li et al. put forward the application of clustering analysis which is in site classification and soil fertility evaluation [3]. Zheng et al. improved rough K- means algorithm, and put forward the rough K- means clustering algorithm based on density weighted [5]. Chen et al. put forward a weighted spaces fuzzy dynamic clustering algorithm, and proved the validity of method in evaluation of soil fertility [6]. But conventional K-means, FCM and other clustering algorithms have some limitations on soil fertility evaluation. Such as K- means is har
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