Guifen Chen

Research on the Construction and Implementation of Soil Fertility Knowledge Based on Ontology

Soil fertility is the comprehensive reflection of related factors and the related factors. Soil fertility evaluation knowledge is stored by relational database as usually, and it is difficult to show the correlation and constraints among attributes .In this paper, Nongan county farmland productivity data is as the research object, Using rough set approach to do attribute reduction, using ontology method to establish the soil fertility level knowledge base, using multi Agent technology to implement the prototype system, and complete the reuse and sharing of knowledge, lay the foundation for semantic level reasoning.

Research on Construction and SWRL Reasoning of Ontology of Maize Diseases

In this paper, according to the characteristics of maize disease knowledge, OWL DL language was used to build maize diseases ontology, and the reasoning rule of maize diseases was defined by using the expressive ability of SWRL rule language.The author introduced several realizable reasoning functions,and achieved the diagnostic reasoning of maize disease knowledge by Jess inference engine.The results indicated that constructing the maize diseases ontology,and introducing SWRL rule into maize disease ontology provided an effective way for the construction of high-intelligent, shareable and reused maize disease knowledge database and diagnostic rule database.

Application of Machine Vision Technology in the Diagnosis of Maize Disease

In order to identify the rapid diagnosis of diseases of corn, to take timely preventive measures to improve the diagnosis of diseases of corn. Machine vision technology will be introduced to the diagnosis and identification of maize diseases, laboratory tests show that the uses of machine vision technology, disease recognition model for the disease sample collection process to identify, analyze findings and to get the real practical applications, consistent with the conclusions, to meet the agricultural production practical application. The technology for the diagnosis of diseases of corn provides a quick, inexpensive, non-destructive testing of possible means.

Study on Soil Nutrients Spatial Variability in Yushu City

In order to help farmers to understand soil nutrients, use effectively our soil and protect our environment, at the same time to improve sustainable development of the agricultural system, the topsoil samples were collected form yushu city .The ways of combining Geostatistics with GIS were applied to analyze the spatial variability of soil nutrients, such as Alkaline hydrolysis nitrogen, available phosphorus and available potassium. All results shows that Alkaline hydrolysis nitrogen, available phosphorus and available potassium in the coefficient of variation were from 9% to 46%, and the largest coefficient of variation of available phosphorus was 46%. By using Semi-variogram function of statistical analysis, Alkaline hydrolysis nitrogen, available phosphorus and available potassium show Moderate spatial dependency. The relevance of space about available phosphorus may be the weakest, which is effected mainly by random factors. So the different management and the level of fertilizer may be done according the spatial variability of different area format.

Research and Application of Monitoring and Simulating System of Soil Moisture Based on Three-Dimensional GIS

Taking maize precise assignments section as the research object, using arcgis10.2 as the visual drive tool, comprehensive application of 3D modeling, database and GIS technology, this paper proposed a method of rapid establishment of agricultural areas of 3D virtual scene, developed soil moisture monitoring 3D simulation system based on GIS. The system had the 3D model search module, the dynamic scene simulation module, the dynamic monitoring and spatial information management function module and so on. Using Jilin Province Nong’an County town of Helong corn precision operation as an example, the system were preliminary application, the application results showed that the system can realize the effective management of agriculture areas, soil moisture spatial information and virtual display. According to the 3D model of soil moisture dynamic monitoring module, for the analysis and application of the regional soil moisture laid a solid foundation, and provided effective digital management platform for precision agriculture technique.

Study on the Temporal and Spatial Variability of Maize Yield in Precision Operation Area

Jilin province is an important agricultural production resource in our country. Study on the temporal and spatial variability of maize yield are significant to understand the potential nutrients in soil, and guide agricultural practice for the recent years in precision operate area. The every year yield distribution belonged to the normal distribution by testing K-Sand the coefficient of variation of them were 16.33%, 11.85%, 12.90% respectively. That precise operation can reduce the yield difference in every operate cell. As a result, the temporal and spatial variability of maize yield can be successfully applied to yield prediction in Jilin Province. Partition results can not only guide soil nutrient evaluation, and can be used to implement variable input and precise fertilization recommendation.

An experimental study in computer programming class

The computer programming class is a vital part of the computer system teaching. According to the present situation and characteristic of personnel training process in some university, the paper presented some methods to improve the level of computer teaching. In order to satisfy the need of personnel training, the article described some questions in the programming class experiment teaching. At the same time some methods and reform plans were proposed. They can improve the university student program design level in some extent.

The application of the spatio-temporal data mining algorithm in maize yield prediction

Abstract This paper has advanced a new method of maize yield prediction which is based on the spatio-temporal data mining. On the one hand, this method predicts the sequence of the target object itself by adopting statistics principles. On the other hand, the method calculates the influence of the spatial distribution of adjacent-area soil fertility on maize yield by neural network. Finally, the method obtains the integrated forecast outcome by taking linear regression. Taking the method to predict the maize yield of experimental area for six consecutive years is better than taking no account of the spatial influence. The errors are controlled by 5%. This paper provides a new method to solve the spatio-temporal data update of farmland affected on the maize yield.

Maize Disease Diagnosis Model Based on Ontology and Multi-Agent

According to the uncertainty, dynamics and dependency of maize diseases, this paper puts forward a kind of maize disease diagnosis model combined ontology with multi-Agent. The knowledge representation of ontology provides a clear formal specification for the onset periods and symptom characteristics during maize disease occurs. Using the Agent’s intelligence and the division collaboration of Agent modules, we have solved the bottleneck problem of the acquisition and representation of maize disease knowledge and improved the learning ability of the ontology. Experiments show that the model can diagnose maize diseases accurately and efficiently and has a good application prospect.

Precision fertilizer sharing system based on Oracle database

Yield in a given field may vary in space depending on a combination of factors such as nutrient availability, soil moisture, rooting depth, pest pressure and others. In order to enhance the yield of agricultural production, the maize sharing fertilizer expert system based on oracle database was developed. During designing the system, the author collected clearly some materials for the system and communicated with domain experts about knowledge of maize fertilizer. The sharing system was based B/S. Considering the characteristic of operational research, the author have designed six function modules, which have not been isolated one another, but have integrated to all modules. Every function includes some sub-function modules.