Research on Evaluation of Soil Fertilities of Farmland at County Level in Nongan Based on Data Mining

2014 ◽  
Vol 635-637 ◽  
pp. 1671-1674
Author(s):  
Li Ma ◽  
Gui Fen Chen ◽  
Li Ying Cao ◽  
Yue Ling Zhao
Keyword(s):  
Data Mining ◽  
Soil Fertility ◽  
Rough Set ◽  
Evaluation Model ◽  
Arable Land ◽  
Fertility Level ◽  
County Level ◽  
Research On Evaluation ◽  
Subjective Factor ◽  
Grade One

This research used the method of rough set and decision tree in data mining, building the evaluation model of soil fertility, to evaluate NongAn of Jilin province farmland productivity. Results show that the NongAn of arable land is divided into six grades, the fertility of grade one to six account for 6.77%, 14.29%, 23.78%, 23.51%, 20.13%, and 11.54% respectively. The farmland productivity difference is significant. The evaluation model of the evaluation results are in conformity with actual farmland productivity NongAn, avoiding the evaluation differences caused by the subjective factor, can effectively improve the soil fertility level classification accuracy and objectivity.

The Optimization Algorithm and Applied in Soil Fertility Evaluation Based on Data Mining

2014 ◽  
Vol 644-650 ◽  
pp. 1737-1740
Author(s):  
Li Ma ◽  
Gui Fen Chen
Keyword(s):  
Data Mining ◽  
Decision Making ◽  
Decision Tree ◽  
Soil Fertility ◽  
Spatial Data ◽  
Rough Sets ◽  
Evaluation Model ◽  
Attribute Reduction ◽  
Spatial Data Mining ◽  
New Ideas

Clustering, rough sets and decision tree theory were applied to the evaluation of soil fertility levels ,and provided new ideas and methods among the spatial data mining and knowledge discovery. In the experiment, the rough sets - decision tree evaluation model establish by 1400 study samples, the accuracy rate is 92% of the test. The results show :model has good generalization ability; the use of rough sets attribute reduction, can remove redundant attributes, can reduce the size of decision tree decision-making model, reduce the decision-making rules and improving the decision-making accuracy, using the combination of rough set and decision tree decision-making method to infer the level of a large number of unknown samples.

Strategies for Soil Fertility Improvement of Arable Land in China

2018 ◽  
Vol 20 (5) ◽  
pp. 84
Author(s):  
Yingjie Hu ◽  
Xiangbin Kong ◽  
Yuzhen Zhang
Keyword(s):  
Soil Fertility ◽  
Arable Land ◽  
Soil Fertility Improvement

APPLICATION OF THE INTENSIVE CROP GROWING TECHNOLOGIES IN CROP ROTATION IS THE STABILITY CONDITION OF THE HUMUS CONTENT OF SOIL

1970 ◽  
pp. 52-56
Author(s):  
V. А. Shchedrin
Keyword(s):  
Soil Fertility ◽  
Crop Rotation ◽  
Humus Content ◽  
Arable Land ◽  
Weighted Average ◽  
Cropping System ◽  
Investment Project ◽  
Crop Rotations ◽  
High Productivity ◽  
Labile Phosphorus

In OOO “Dubovitskoe” which was organized in 2006 as investment project of the AO “Shchelkovo Agrokhim” for 2010 – 2012 three advanced crop rotations have been developed. Before their introduction the grain crops fraction in the cropping system was 62%, then it fell to 49%. At the same time the portion of raw crops increased from 15 to 20%, legumes from 6 to 8%, others (buckwheat, grain maize, etc.) - up to 23%. As of 2017, the crops of leguminous crops have increased noteworthily. There are two predominant soil types here heavy clay loam podzolized chernozem (6615 ha) and grey forest soil (856 ha). Weighted average indicators (as of 2017): humus content in the soils of arable land is 5, 34%; acidity pH is 4.92; labile phosphorus - 111.8 mg / kg soil; exchange potassium - 144 mg / kg soil. The coefficient of the soil fertility in the enterprise (weighted average) is 0.66. This means that maintaining and increasing the soil fertility for arable land of the enterprise is critical task. As a result of the research, it has been established that the technologies introduced in the crop vegetation management (CVS) in the crop rotation conditions ensure high productivity of cultivated crops and stability of humus content in soils as an energy basis and a guarantor of increasing fertility. The indicators of the labile phosphorus Р205 and exchange potassium К20 in the soils depending on the crop rotation vary from a certain decrease to expressed steady growth. Therefore it is necessary to specify seeding rates based on actual data. Sustainable soil acidification in the crop rotations under crop cultivation in OOO “Dubovitskoe” it is the result of the acid feterlizers high rates application, during studying period did not carried out required agromelioration with calcium contenting elements.

ANALISA DATA EKSPEDISI PAKET DENGAN MENERAPKAN ALGORITMA ROUGH SET (STUDI KASUS: JNE AGEN MENTENG MEDAN)

2019 ◽  
Vol 3 (1) ◽  
Author(s):  
Hasrat Selpia Simorangkir
Keyword(s):  
Data Mining ◽  
Rough Set ◽  
Microsoft Excel ◽  
General Rules ◽  
New Knowledge ◽  
Analyze Data

In analyzing data with data mining using the Rough Set algorithm which has results in the form of rules (rules). The process of determining the rules in the Rough Set method starts from processing the Microsoft Excel database, and continues testing with the Rough Set method. Thus producing General Rules which will become new knowledge in this research.With the existence of data mining using the rough set penilus algorithm, it can analyze data and provide solutions to the weaknesses faced in the menteng Medan field agents that have occurred so that it can be used as an alternative to solving problems in packet expedition encountered so far.Keyword: Data Mining, Descision System, Equivalen Class, ,General Rules, Rough set,Reduction

scholarly journals Recessive Transition Mechanism of Arable Land Use Based on the Perspective of Coupling Coordination of Input–Output: A Case Study of 31 Provinces in China

Land ◽  
2021 ◽  
Vol 10 (1) ◽  
pp. 41
Author(s):  
Yi Lou ◽  
Guanyi Yin ◽  
Yue Xin ◽  
Shuai Xie ◽  
Guanghao Li ◽  
...  
Keyword(s):  
Land Use ◽  
Evaluation Model ◽  
Arable Land ◽  
Temporal Trends ◽  
Mainland China ◽  
Input Output ◽  
Transition Mechanism ◽  
Input And Output ◽  
Spatio Temporal ◽  
Arable Land Use

In the rapid process of urbanization in China, arable land resources are faced with dual challenges in terms of quantity and quality. Starting with the change in the coupling coordination relationship between the input and output on arable land, this study applies an evaluation model of the degree of coupling coordination between the input and output (D_CCIO) on arable land and deeply analyzes the recessive transition mechanism and internal differences in arable land use modes in 31 provinces on mainland China. The results show that the total amount and the amount per unit area of the input and output on arable land in China have presented different spatio-temporal trends, along with the mismatched movement of the spatial barycenter. Although the D_CCIO on arable land increases slowly as a whole, 31 provinces show different recessive transition mechanisms of arable land use, which is hidden in the internal changes in the input–output structure. The results of this study highlight the different recessive transition patterns of arable land use in different provinces of China, which points to the outlook for higher technical input, optimized planting structure, and the coordination of human-land relationships.

Sign in / Sign up

Export Citation Format

Share Document