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Development and evaluation of an expert system approach to uneven-aged management of loblolly-shortleaf pine stands in the west Gulf region.

机译:开发和评估专家系统方法,以管理墨西哥湾西部地区火炬松-短叶松林的不均衡年龄。

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摘要

Forest managers expend significant time and effort seeking, organizing, and synthesizing information relevant to making effective forestry decisions. Oftentimes, they must rely on the knowledge and experience of human experts, a resource that is in short supply, requires many years to acquire, and is concentrated in a few individuals. This research task suggests expert systems as one viable solution to the problems of technology transfer and automating and maintaining expertise in consistent and usable form.; Expert systems are practical computer programs which solve problems that were previously considered only solvable by human expertise. The expert system developed in this research, named FOREX, was written in ProLog. FOREX is primarily a second-generation expert system for prescribing silvicultural systems. Aside from human expertise stored in its knowledge base, FOREX is linked with growth and yield and optimization models to complement the search for optimal recommendation.; A methodology was developed for transforming available literature/research information and the private knowledge of human experts into decision rules. Factors pertinent to prescribing silvicultural systems were identified. English-like decision rules were developed, and human experts were then asked to verify and confirm these rules. The process of encoding these rules into ProLog format was an important phase of the development process.; In a modified Turing test, nine human evaluators rated prescriptions from four other human experts, FOREX, and another computer-based model. FOREX's scores were found comparable to the research foresters and superior to the industrial foresters and the other computer model. These results indicate that human expertise, in uneven-aged management of loblolly-shortleaf pine stands, has been captured by an expert system. Success in this project should encourage other researchers to apply this approach for other forestry problems.
机译:森林管理者花费大量时间和精力来寻找,组织和综合与制定有效林业决策有关的信息。通常,他们必须依靠人类专家的知识和经验,这是一种短缺的资源,需要很多年才能获得,并且集中在少数几个人身上。这项研究任务建议专家系统作为解决技术转让问题的可行解决方案,并以一致和可用的形式自动化和维护专业知识。专家系统是实用的计算机程序,可以解决以前只能由人类专业知识解决的问题。在这项研究中开发的专家系统,名为FOREX,是用ProLog编写的。 FOREX主要是用于规定造林系统的第二代专家系统。除了存储在其知识库中的人类专业知识外,FOREX还与增长,产量和优化模型相关联,以补充对最佳推荐的搜索。开发了一种方法,用于将可用的文献/研究信息和人类专家的私人知识转换为决策规则。确定了与处方造林系统有关的因素。制定了类似英语的决策规则,然后请人类专家验证和确认这些规则。将这些规则编码为ProLog格式的过程是开发过程的重要阶段。在经过修改的Turing测试中,九名评估人员对另外四名人类专家FOREX和另一个基于计算机的模型的处方进行了评分。发现FOREX的分数可与研究林务人员媲美,并优于工业林务人员和其他计算机模型。这些结果表明,专家系统已经掌握了对火炬松-短叶松木林进行不平均年龄管理的人类专业知识。该项目的成功应鼓励其他研究人员将这种方法应用于其他林业问题。

著录项

  • 作者

    Lorenzo, Alfredo Baptista.;

  • 作者单位

    Louisiana State University and Agricultural & Mechanical College.;

  • 授予单位 Louisiana State University and Agricultural & Mechanical College.;
  • 学科 Agriculture Forestry and Wildlife.; Artificial Intelligence.
  • 学位 Ph.D.
  • 年度 1993
  • 页码 185 p.
  • 总页数 185
  • 原文格式 PDF
  • 正文语种 eng
  • 中图分类 森林生物学;人工智能理论;
  • 关键词

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