全部版块 我的主页
论坛 经济学人 二区 外文文献专区
202 0
2022-03-07
摘要翻译:
本文的目的是提出一种新的生态模型标定方法--基于Agent的软件。该agent的工作分为三个阶段:1-建立矩阵,综合变量间的关系;2.分析了不同变量对不同参数的稳态敏感性;3-它迭代运行模型,并测量模型的拟合、充分性和可靠性不足。第3阶段继续进行,直到达到一些收敛标准。在每次迭代中,代理从阶段1和阶段2中知道哪些参数最有可能对预测结果产生期望的偏移。
---
英文标题:
《Agent-based Ecological Model Calibration - on the Edge of a New Approach》
---
作者:
Antonio Pereira (1 and 2), Pedro Duarte (1), Luis Paulo Reis (2) ((1)
  UFP, Porto, Portugal (2) FEUP, Porto, Portugal)
---
最新提交年份:
2008
---
分类信息:

一级分类:Computer Science        计算机科学
二级分类:Artificial Intelligence        人工智能
分类描述:Covers all areas of AI except Vision, Robotics, Machine Learning, Multiagent Systems, and Computation and Language (Natural Language Processing), which have separate subject areas. In particular, includes Expert Systems, Theorem Proving (although this may overlap with Logic in Computer Science), Knowledge Representation, Planning, and Uncertainty in AI. Roughly includes material in ACM Subject Classes I.2.0, I.2.1, I.2.3, I.2.4, I.2.8, and I.2.11.
涵盖了人工智能的所有领域,除了视觉、机器人、机器学习、多智能体系统以及计算和语言(自然语言处理),这些领域有独立的学科领域。特别地,包括专家系统,定理证明(尽管这可能与计算机科学中的逻辑重叠),知识表示,规划,和人工智能中的不确定性。大致包括ACM学科类I.2.0、I.2.1、I.2.3、I.2.4、I.2.8和I.2.11中的材料。
--
一级分类:Computer Science        计算机科学
二级分类:Multiagent Systems        多智能体系统
分类描述:Covers multiagent systems, distributed artificial intelligence, intelligent agents, coordinated interactions. and practical applications. Roughly covers ACM Subject Class I.2.11.
涵盖多Agent系统、分布式人工智能、智能Agent、协调交互。和实际应用。大致涵盖ACM科目I.2.11类。
--

---
英文摘要:
  The purpose of this paper is to present a new approach to ecological model calibration -- an agent-based software. This agent works on three stages: 1- It builds a matrix that synthesizes the inter-variable relationships; 2- It analyses the steady-state sensitivity of different variables to different parameters; 3- It runs the model iteratively and measures model lack of fit, adequacy and reliability. Stage 3 continues until some convergence criteria are attained. At each iteration, the agent knows from stages 1 and 2, which parameters are most likely to produce the desired shift on predicted results.
---
PDF链接:
https://arxiv.org/pdf/0809.1686
二维码

扫码加我 拉你入群

请注明:姓名-公司-职位

以便审核进群资格,未注明则拒绝

相关推荐
栏目导航
热门文章
推荐文章

说点什么

分享

扫码加好友,拉您进群
各岗位、行业、专业交流群