【作者】 彭汉艮；

【导师】 吴沛良； 柯建国；

【作者基本信息】 南京农业大学 ， 作物栽培学与耕作学， 2003， 硕士

【摘要】 种植制度知识模型可为数字化和智能化的种植制度设计提供新的量化工具。本研究以种植业系统为研究对象，以优化利用农业自然资源为出发点，着重运用系统分析原理和数学建模技术来研究种植制度的知识表达体系，在系统收集和分析种植制度设计方面的文献资料以及专家知识和经验的基础上，通过解析和综合种植制度指标与生态环境、品种类型、社会经济条件之间的定量化关系，构建了种植制度知识模型。在此基础上，进一步运用构件化程序设计思想，在Visual C++平台上设计并初步实现了种植制度决策支持系统（CSDSS），且通过实例分析对系统进行了检验和评价，从而为实现种植制度设计的科学化、定量化和信息化奠定了基础。 1、以优化利用种植业资源为目标，在全面总结现有种植制度研究成果及专家知识、经验和文献资料的基础上，综合耕作学、作物生态学、作物栽培学、农业气象学、资源经济学和农业经济学等多个领域的知识，运用系统工程原理和数学建模技术，量化了种植制度指标与生态环境、作物类型、社会经济条件之间的动态关系，构建了种植制度知识模型，解决了传统专家系统中知识库庞大、适应性弱等问题。 2、种植制度知识模型包括作物组合设计知识模型、作物结构动态优化模型和作物布局设计知识模型。其中作物组合设计知识模型包括作物生态（气候、土壤）适应性评价、作物熟制类型设计和作物搭配。作物结构优化模型基于互动的农产品价格预测模型和动态线性规划模型。作物布局设计知识模型基于经济效益、生态效益和社会效益的综合协调。 3、在构建种植制度知识模型的基础上，充分利用软构件的语言无关性、可重用性、简便快捷的系统维护机制等特点，在Visual C⁺⁺平台上初步构建了种植制度决策支持系统。着重明确了系统的组织结构和内容，系统的主要功能及开发流程等。 4、利用不同作物类型等资料对所建种植制度决策支持系统进行了可靠性和适用性测试与检验。结果表明，系统决策的结果与实际生产中的种植制度模式之间具有较好的一致性。更多还原

【Abstract】 The knowledge model for cropping system can provide new quantitative tool and method for digital and intelligent cropping system design. With optimal use of agricultural natural resource as the basis, this research focused on applying the system analysis principle and mathematical modeling technique to study of knowledge expression for cropping system. Based on collecting and analyzing literature, expert knowledge and experience in cropping system, relationships of cropping system indices to ecological conditions, crop types and social economical levels were quantified and integrated, for development of the knowledge model for cropping system design. With the method of component-based programming design, a knowledge model-based decision support system for cropping system n (CSDSS) was established on the platform of Visual C++. In addition, case studies on the system were carried out with different data sets under varied conditions. This work would help make cropping system design more scientific, quantitative and informational.1. Taking optimal resource use as research goal, and based on summarizing cropping system literature, and expert knowledge and experience, and on integrating the knowledge of multi-disciplines as agronomy, crop ecology, crop cultivation, agricultural meteorology, resource and agricultural economics, the dynamic relationships of cropping system indices to ecological conditions, crop types, social and economical levels were quantified with system engineering principle and mathematical modeling technique, and then the knowledge model for cropping system design was developed. The knowledge model overcomes the shortcomings of traditional expert system for cropping system, such as large knowledge base and narrow applicability.2. The knowledge model for cropping system includes submodels of crop combination, dynamic optimization of crop structure and crop distribution design. The submodel of crop combination includes crop ecological adaptability evaluation, year-round cropping number design. The submodel of crop structural dynamic optimization was developed based on the price estimation of agricultural products and53dynamic linear programming model, and the submodel of crop distribution was based on the economical, ecological and social benefits.3. On the basis of the knowledge model for cropping system , a decision support system for cropping system design (CSDSS) was developed on the platform of Visual C++ by fully using the component traits of no correlation between programming languages, reusability, and brief and shortcut system maintenance. In addition, the framework, contents, main functions and development flows of the system were established.4. Testing of the system with the data sets of different eco-sites and crop combinations indicated a good performance of the system in explanation and application.更多还原