人工智能的计量校准

doi:10.3969/j.issn.1000-1158.2021.01.13

Abstract
Figure/Table
References (29)
Related Citation (15)

Download: PDF (524 KB) HTML (1 KB)
Export: BibTeX | EndNote (RIS)

Abstract For the measurement and calibration of artificial intelligence, to describe its urgency, necessity and feasibility. Two different artificial intelligence metering solutions are proposed. The first method is based on the seven dimensions of intelligence, and performs linguistic intelligence, mathematical logic intelligence, spatial intelligence, physical intelligence, music intelligence, interpersonal relationship intelligence, and introspective intelligence. Two or more intelligent multiple intelligence systems perform comprehensive weighting for specific task objectives, and give a quantitative evaluation result of the intelligence level to specific task objectives. The second is the engineering method, starting with each specific and clear artificial intelligence system, establishing an evaluation system according to the ideal goal, conducting a measurement calibration study, and finally evaluating the systems sub-items and comprehensive intelligence level in a quantitative manner. Its main idea is to evaluate the intelligence level of any intelligent system in a quantitative way.

Key words： metrology artificial intelligence calibration evaluation

Received: 05 December 2019 Published: 19 January 2021

PACS:

TB973

	Service

	E-mail this article
	Add to my bookshelf
	Add to citation manager
	E-mail Alert
	RSS
	Articles by authors
	LIANG Zhi-guo
	JIANG Yan-huan

Cite this article:

LIANG Zhi-guo,JIANG Yan-huan. The Calibration of Artificial Intelligence[J]. Acta Metrologica Sinica, 2021, 42(1): 78-84.

URL:

http://jlxb.china-csm.org:81/Jwk_jlxb/EN/10.3969/j.issn.1000-1158.2021.01.13 OR http://jlxb.china-csm.org:81/Jwk_jlxb/EN/Y2021/V42/I1/78

［1］朱祝武. 人工智能发展综述［J］. 中国西部科技, 2011, (17): 12-14.
Zhu Z W. The Development of AI［J］. Science and Technology of West China, 2011, (17): 12-14.
［2］钟义信. 人工智能理论: 从分立到统一的奥秘［J］. 北京邮电大学学报, 2006, 29(3): 5-10.
Zhong Y X. A Secret Making AI Theory from Separation to Unification［J］. Journal of Beijing University of Posts and Telecommunications, 2006, 29(3): 5-10.
［3］周光霞, 周方. 美军人工智能空战系统阿尔法初探［C］// 第六届中国指挥控制大会. 2018, 61-65.
［4］荣华, 刘衷瑞. 人机空战: 机器胜! 美空军组织模拟人机空战对抗［J］. 环球军事, 2016, (14): 60-61.
Rong H, Liu Z R, Man-Machine Air Combat: Machine Wins! US Air Force Organizes Simulated Man-Machine Air Combat Confrontation［J］. Global Military, 2016, (14): 60-61.
［5］钟义信. 机制主义人工智能理论——一种通用的人工智能理论［J］. 智能系统学报, 2018, 13(1): 2-18.
Zhong Y X. Mechanism-based Artificial intelligence theory: a universal theory of artificial intelligence［J］. CAAL Transactions on Intelligent Systems, 2018, 13(1): 2-18.
［6］王娅. 基于认知过程的新型人工智能系统设计［J］. 科技通报, 2018, (9): 191-194.
Wang Y. Design of new artificial intelligence system based on cognitive process［J］. Bulletin of Science and Technology, 2018, (9): 191-194.
［7］陈茹, 邓泽林, 刘鼎, 等. 利用人工智能系统预测大面积脑梗死患者的转归［J］. 中国卫生统计, 2014, 31(1): 100-103.
Chen R, Deng Z L, Liu D, et al. Using artificial intelligence systems to predict the outcome of patients with large-scale cerebral infarction［J］. Chinese Journal of Health Statistics, 2014, 31(1): 100-103.
［8］欧阳汉强, 姜亮, 刘晓光, 等. 人工智能在脊柱外科诊断与治疗中的应用现状和发展趋势［J］. 中华骨科杂志, 2019, 39(24): 1543-1548.
Ouyang H Q, Jiang L, Liu X G, et al. application status and development trend of artificial intelligence in the diagnosis and treatment of spinal surgery［J］. Chinese Journal of Orthopaedics, 2019, 39(24): 1543-1548.
［9］黄俊钦, 孟晓风. 智能测试系统的一种设计思想［J］. 计量学报, 1996, 17(3): 48-52+56.
Huang J Q, Meng X F. A design idea of the intelligent measurement systems［J］. Acta Metrologica Sinica, 1996, 17(3): 48-52, 56.
［10］潘文诚. 智能仪器中数字校准技术的研究［J］. 计量学报, 2006, 27(1): 57-60.
Pan W C. Research of Digital Calibration of Intelligent Instruments［J］. Acta Metrologica Sinica, 2006, 27(1): 57-60.
［11］赵英剑, 王建利, 马新辉, 等. 三坐标测量机智能技术［J］. 计量学报, 2001, 22(3): 164-167.
Zhao Y J, Wang J L, Ma X H, et al. The Intelligent Technology of CMM［J］. Acta Metrologica Sinica, 2001, 22(3): 164-167.
［12］AI in the UK: Ready, willing and able? House of Lords. Selecte Committee on Artificial Intelligence report of session 2017-19［EB］. http://www.doc88.com/p-0394876954354.html.
［13］Draft Ethics Guidelines For Trustworthy AI, Jan. 25, 2019［EB］. https://ec.europa.eu/digital-single-market/en/news/draft-ethics-guidelines-trustworthy-ai.
［14］Accelerating Americas Leadership in Artificial Intelligence, 2019-02-11,［EB］. https://www.whitehouse.gov/articles/accelerating-americas-leadership-in-artificial-intelligence/.
［15］新一代人工智能发展规划, 国务院关于印发新一代人工智能发展规划的通知, 国发〔2017〕35号［EB］. http://www.gov.cn/zhengce/content/2017-07/20/conten.
［16］新一代人工智能治理原则——发展负责任的人工智能［EB］. http://www.gov.cn/xinwen/2019-06/17/content_5401006.htm.
［17］Monroe N. Kasparov versus Deep Blue: Computer chess comes of age［M］. New York: Monty Newborn. Springer-Verlag, 1996, 322.
［18］Granter S R, Beck A H, Papke D J. AlphaGo, Deep Learning, and the Future of the Human Microscopist［J］. Archives of pathology & laboratory medicine, 2017, 141(5): 619-621.
［19］中国智能机器人格斗大赛［EB］. https://www.360kuai.com/pc/.
［20］林崇德, 杨治良, 黄希庭. 心理学大辞典［M］. 上海: 上海出版社, 2003, 1704.
［21］霍华德加德纳(Howard Gardner). 多元智能理论, 2018-03-03［EB］. https://baike.so.com/doc/5390959-5627639.html.
［22］黄强, 水超, 孙智信, 等. 科学计量视角下认知科学发展研究［J］. 现代情报, 2011, 31(7): 7-12.
Huang Q, Shui C, Sun Z X, et al. Cognitive Science Development Research under Scientometrics Perspective［J］. Modern Information, 2011, 31(7): 7-12.
［23］罗钧, 吴华, 王强. 具有快速收敛特性蜂群算法的球度误差评定［J］. 计量学报, 2011, 32(6): 501-504.
Luo J, Wu H, Wang Q. Sphericity Error Evaluation with Double-quick Artificial Bee Colony Algorithm［J］. Acta Metrologica Sinica, 2011, 32(6): 501-504.
［24］王东霞, 宋爱国, 温秀兰. 微分进化算法在圆度误差评定中的应用［J］. 计量学报, 2015, 36(2): 123-127.
Wang D X, Song A G, Wen X L. Application of Differential Evolutionary Algorithm for Evaluation of Roundness Error［J］. Acta Metrologica Sinica, 2015, 36(2): 123-127.
［25］刘笑楠, 白雨辰, 尹思璐, 等. 基于类卷积神经网络的可见光虹膜识别方法［J］. 仪器仪表学报, 2017, 38(11): 2651-2658.
Liu X N, Bai Y C, Yin S L, et al. Iris recognition of visible light based on analogous convolutional neural network［J］. Chinese Journal of Scientific Instrument, 2017, 38(11): 2651-2658.
［26］人工智能-百度百科［EB］. https://baike.baidu.com/item/人工智能/9180.
［27］尼尔斯·约翰·尼尔森(Nils John Nilsson)［EB］. https://baike.baidu.com/item/.
［28］尼尔斯·约翰·尼尔森. 理解信念: 人工智能的科学理解［M］. 北京: 机械工业出版社, 2017.
［29］梁志国, 张大治. 复杂系统的计量性设计与评估［J］. 计测技术, 2017, 37(5): 1-6.
Liang Z G, Zhang D Z. Design and Evaluation of the Measure Ability of Complex Products［J］. Metrology & Measurement Technology, 2017, 37(5): 1-6.