Acta Metall Sin  1994, Vol. 30 Issue (13): 22-26    DOI:

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ARTIFICIAL NEURAL NETWORK APPLIED TO PREDICTION OF INTERMEDIATE PHASES IN MOLTEN SALT PHASE DIAGRAMS

TANG BO; QIN Pei; LIU Miaoxiu;ZHANG Weiming;CHEN Nianyi(Shanghai institute of Metallurgy; Chinese Academy of Sciences)

TANG BO; QIN Pei; LIU Miaoxiu;ZHANG Weiming;CHEN Nianyi(Shanghai institute of Metallurgy; Chinese Academy of Sciences). ARTIFICIAL NEURAL NETWORK APPLIED TO PREDICTION OF INTERMEDIATE PHASES IN MOLTEN SALT PHASE DIAGRAMS. Acta Metall Sin, 1994, 30(13): 22-26.

Abstract References Related Articles Recommended Metrics Download:  PDF(336KB)  Export:  BibTeX | EndNote (RIS)       Abstract  Artificial neural network is a new type ofinfonnation processing system based on modelling the neural system structure of human brain. Together with chemical bond parameters, it can be used to extract useful information from the experimental data of molten salt phase diagrams.The semi-empirical rules found can be used for the computerized prediction of the stoichiometry, the melting or decomposition temperature, and the melting behavior(congruent or incongruent melting) of the intermediate phases in unknown molten saltphase diagrams. Key words:  artificial neural network      molten salt phase diagram      intermediate phase      Service E-mail this article Add to citation manager E-mail Alert RSS （） Articles by authors URL:  https://www.ams.org.cn/EN/     OR     https://www.ams.org.cn/EN/Y1994/V30/I13/22 1陈念贻,张桂成．金属学报,1964;7:122陈念贻,江乃雄,谢雷鸣,施天生．中国科学,1981;7:8363靳蕃,范俊波,谭永东．神经网络与神经计算机,西南交通大学出版社,19914CCCP,19615Wells,AF．StructuralInorganicchemistry,fifthedition,ClarendonPress,Oxford,1984:586 [1] HOU Jieshan, ZHOU Lanzhang, GUO Jianting, YUAN Chao. APPLICATION OF ARTIFICIAL NEURAL NETWORK FOR PREDICTION OF SUPERPLASTIC  BEHAVIOUR IN NiAl ALLOYS[J]. 金属学报, 2013, 49(11): 1333-1338. [2] YU Hui KIM Youngmin YU Huashun YOU Bongsun MIN Guanghui. HOT DEFMATION BEHAVIOR AND HOT WORKABILITY OF Mg-Zn-Zr-Ce ALLOY[J]. 金属学报, 2012, 48(9): 1123-1131. [3] LI Xincheng; CHEN Guang; ZHU Weixing; WANG Yun; ZHANG KAihua; WANG Jianmin. Intelligent Expert System Used in Gear Material Selection and its Heat Treatment[J]. 金属学报, 2004, 40(10): 1051-1054 . [4] ZHANG Zhaochun; WU Zhu; LI Chonghe; QIN Pei; CHEN Nianyi(Shanghai Institute of Metallurgy; The Chinese Academy of Sciences; Shanghai 200050)Correspondent: WU Zhu; Tel: (021)62511070-8932; Fax: (021)62513510. APPLICATION OF PATTERN RECOGNITION AND ARTIFICIAL NEURAL NETWORK TO IMPROVE THE MECHANICAL PROPERTIES OF CYLINDER BLOCK CAST OF AUTOMOBILE ENGINE[J]. 金属学报, 1998, 34(10): 1068-1072. [5] GUO Jin; LI Chonghe; QIN Pei; ZENG Wenming; CHEN Nianyi(Shanghai Institute of Metallurgy; Chinese Academy of Sciences; Shanghai 200050) (Manuscript received 1995-06-23 ; in revised form; 1995-09- 15). ARTIFICIAL NEURAL NETWORK METHOD APPLIED TO P-C RELATIONSHIPS OF AB_5-TYPE HYDROGEN STORAGE ALLOYS[J]. 金属学报, 1996, 32(3): 333-33. [6] ZHANG Peng;CUI Jianzhong;ZHANG Qizhi;DU Yunhui;FU Jiangtao;BA Limin (Northeastern University;Shenyang 110006)(Manuscript received 1996-05-21;in revised form 1996-07-11). ARTIFICIAL NEURAL NETWORKS APPLIED TO INVESTIGATION ON SOLID-LIQUID PRESSURE BONDING OF STAINLESS STEEL AND ALUMINIUM[J]. 金属学报, 1996, 32(12): 1275-1278. [7] ZHA NG Peixin; ZHA NG Qizhi; W U Liming; SUI Zhitong(Northeasiern Unirersity.Shenyang 110006). OPTIMIZATION OF MgO-B_2O_3-SiO_2 SLAGGING USING ARTIFICIAL NEURAL NETWORK AND GENETIC ALGORITHM[J]. 金属学报, 1995, 31(18): 284-288. [8] CAI Yudong; XU Weijie; CHEN Nianyi. DESCRIMINATION OF D88 STRUCTURE OF INTER-METALLIC COMPOUNDS BY SELF-ORGANIZATION ARTIFICIAL NEURAL NETWORK[J]. 金属学报, 1995, 31(18): 280-283. No Suggested Reading articles found! Viewed Full text Abstract Cited   Shared      Discussed