Articles | Volume 6, issue 3
Research article
20 Aug 2015
Research article |  | 20 Aug 2015

A fuzzy intelligent system for land consolidation – a case study in Shunde, China

J. Wang, A. Ge, Y. Hu, C. Li, and L. Wang

Abstract. Traditionally, potential evaluation methods for farmland consolidation have depended mainly on the experts' experiences, statistical computations or subjective adjustments. Some biases usually exist in the results. Thus, computer-aided technology has become essential. In this study, an intelligent evaluation system based on a fuzzy decision tree was established, and this system can deal with numerical data, discrete data and symbolic data. When the original land data are input, the level of potential of the agricultural land for development will be output by this new model. The provision of objective proof for decision-making by authorities in rural management is helpful. Agricultural land data characteristically comprise large volumes, complex varieties and more indexes. In land consolidation, it is very important to construct an effective index system. A group of indexes need to be selected for land consolidation. In this article, a fuzzy measure was adopted to accomplish the selection of specific features. A fuzzy integral based on a fuzzy measure is a type of fusion tool. The optimal solution with the fewest non-zero elements was obtained for the fuzzy measure by solving a fuzzy integral. This algorithm provides a quick and optimal way to identify the land-index system when preparing to conduct land consolidation. This new research was applied to Shunde's "Three Old" consolidation project which provides the data. Our estimation system was compared with a conventional evaluation system that is still accepted by the public. Our results prove to be consistent, and the new model is more automatic and intelligent. The results of this estimation system are significant for informing decision-making in land consolidation.

Short summary
A fuzzy intelligent system based on a fuzzy decision tree was established for land potential evaluation. We proposed one new model for feature selection based on the fuzzy measure using the L1-norm method, which can help to construct an index system for intelligent evaluation. The data comes from the “Three Old” project of Shunde, China. It is huge and heterogeneous and is therefore used first for research. The fuzzy intelligent system shows good performance for land potential evaluation.