¾ðÊóÃμ±³Ø²ñ»ï, Vol. 8, No. 1

¾ðÊóÃμ±³Ø²ñ»ï, 1998, 8(1), 1-2

Semantic Structures of Chemical Data for Problem Solving Systems
Yuzuru Fujiwara¢÷, Jianghong An¢÷¢÷
¢÷Fucalty of Science,Kanagawa University, ¢÷¢÷Institute of Electronics and Information Science,University of Tsukuba

There are diversified semantic relationships such as equivalence, inclusion, causality, and relativity in chemical data. Chemical problem solving systems depend on whether the semantic relationships among chemical concepts can be sufficiently represented and effectively processed. The semantic structures represent the semantic relationships in an easily understandable way for both users and computers. In order to construct this huge and complicated semantic structures, a self organizing approach, i.e., an automatic method is necessary. The information model for semantic representation, method of self organization of conceptual structures of compounds ( a kind of semantic structures), and experimental results are described. The functions of the problem solving systems include similarity measurement of compounds, analogical reasoning of reactions, naming of molecular structures and generating molecular structures from names, as well as substructure search of compounds.

¾ðÊóÃμ±³Ø²ñ»ï, 1998, 8(1), 14-33

»öÎã¥Ù¡¼¥¹¿äÏÀ¤Ë¤è¤ëǮʬÀϻٱ祷¥¹¥Æ¥à
Computer-Assisted Thermal Analysis System Based on Case-Based Reasoning
ÅÄÃæ ¹À°ì¡¤À¾ËÜ ±¦»Ò¡¤Ã滳 ô¡
¿ÀÆàÀîÂç³ØÍý³ØÉô

¡¡Ç®Ê¬ÀϤάÄê¾ò·ïÀßÄê¤ò»Ù±ç¤¹¤ë¥·¥¹¥Æ¥à¤Î¥×¥í¥È¥¿¥¤¥×¤ò»öÎã¥Ù¡¼¥¹¤Ë´ð¤Å¤¯¥¨¥­¥¹¥Ñ¡¼¥È¥·¥¹¥Æ¥à¤È¤·¤Æ³«È¯¤·¤¿¡¥Ç®Ê¬ÀÏ¤Î¥×¥í¥»¥¹¤Ï¡¤(1)¬Äê¾ò·ï¤ÎÀßÄꡤ(2)¬Äꡤ¤ª¤è¤Ó(3)¬Äê·ë²Ì¤Î²òÀÏ¡¤¤È¤¤¤¦£³¤Ä¤Î¥¹¥Æ¥Ã¥×¤ËÂçÊ̤µ¤ì¤ë¤¬¡¤ËÜ¥·¥¹¥Æ¥à¤Ï¤½¤ÎºÇ½é¤Î¥¹¥Æ¥Ã¥×¤ò»Ù±ç¤¹¤ë¤â¤Î¤Ç¤¢¤ë¡¥ËÜ¥·¥¹¥Æ¥à¤Ë¤ª¤¤¤Æ¤Ï¡¤»îÎÁ¾ðÊó¤È¬ÄêÌÜŪ¤È¤¤¤¦£²¤Ä¤Î´ÑÅÀ¤«¤éǮʬÀÏ»öÎã¤Îɽ¸½ÊýË¡¤òÍ¿¤¨¡¤¤½¤Î£²¤Ä¤Î´ÑÅÀ¤«¤é»öÎã´Ö¤ÎÎà»÷À­¤òÄêµÁ¤·¤¿¡¥¤Þ¤¿¡¤»öÎãɽ¸½¤Îµ­½Ò¤ËÍѤ¤¤é¤ì¤ëÍѸì¤Î°ÕÌ£¤ò½ÀÆð¤Ë°·¤¦¤¿¤á¤Ë¥·¥½¡¼¥é¥¹¤ä³µÇ°¼­½ñ¤Ê¤É¤òÍÑ°Õ¤·¤¿¡¥¤Þ¤¿¡¤»öÎ㽤Àµ¤Ï¥ë¡¼¥ë¤Ë¤è¤Ã¤Æ¹Ô¤¦¤¬¡¤³Æ¥ë¡¼¥ë¤Ïµ­½Ò¤ÎÃê¾ÝÅ٤˱þ¤¸¤ÆʬÎव¤ì¤Æ¤¤¤ë¡¥¤½¤Î·ë²Ì¡¤Îà»÷Å٤µ¤¤»öÎ㤷¤«¸«¤Ä¤«¤é¤Ê¤¤¾ì¹ç¤Ç¤â¡¤¤¢¤ëÄøÅ٤Υ¢¥É¥Ð¥¤¥¹¤òÄ󶡤¹¤ë¤³¤È¤¬¤Ç¤­¤ë¡¥Â¬Äê¾ò·ï¤Îº¬µò¤òÍ¿¤¨¤ë¾ðÊó¤ÏÀ°Íý¤µ¤ì¤¿·Á¤Ç¤ÏÌÀ¤é¤«¤Ë¤µ¤ì¤Æ¤ª¤é¤º¡¤»îÎÁ¤ä¬ÄêÌÜŪ¤Ë±þ¤¸¤Æ·Ð¸³¾ðÊó¤äÀìÌçÃμ±¤Ë¤è¤Ã¤Æ¿äÄꤷ¤Æ¤¤¤ë¤Î¤¬¼Â¾ð¤Ç¤¢¤ë¤Î¤Ç¡¤¥¨¥­¥¹¥Ñ¡¼¥È¥·¥¹¥Æ¥à¤ÎÏÈÁȤȤ·¤Æ¤Ïñ½ã¤Ê¥ë¡¼¥ë¤äµ­²±¤Ë¤è¤ë¿äÏÀÊý¼°¤è¤ê¤â»öÎã¤Ë´ð¤Å¤¤¤¿¿äÏÀÊý¼°¤È¤¹¤ë¤Î¤¬Å¬ÀڤǤ¢¤ë¤È¹Í¤¨¤é¤ì¤ë

¾ðÊóÃμ±³Ø²ñ»ï, 1998, 8(1), 34-42

2½Å²½¥Ë¥å¡¼¥é¥ë¥Í¥Ã¥È¤òÍѤ¤¤¿¥¹¥±¥¸¥å¡¼¥ê¥ó¥°¥·¥¹¥Æ¥à¤Î³«È¯
Development of Scheduling System using Dual Neural Networks
°ËÆ£ ¾ÈÌÀ
ÆÁÅçÂç³Ø¹©³ØÉôµ¡³£¹©³Ø²Ê

¡¡À½ÉʤοÍͲ½¤È¥ê¡¼¥É¥¿¥¤¥à¤Îû½ÌÍ×µá¤Ëȼ¤Ã¤Æ¡¤¥×¥í¥¸¥§¥¯¥È¥¹¥±¥¸¥å¡¼¥ê¥ó¥°¤Î½ÅÍ×À­¤¬¤Þ¤¹¤Þ¤¹¹â¤Þ¤Ã¤Æ¤¤¤ë¡£²æ¡¹¤Ï¡¤¤³¤¦¤·¤¿¥×¥í¥¸¥§¥¯¥È¥¹¥±¥¸¥å¡¼¥ê¥ó¥°¤Î»Ù±ç¤òÌÜŪ¤È¤·¤Æ£²½Å²½¥Ë¥å¡¼¥é¥ë¥Í¥Ã¥È¤Ë¤è¤ë¥¢¥×¥í¡¼¥Á¤ò»î¤ß¤¿¡£¤Þ¤º¡¤£±¼¡¥Ë¥å¡¼¥é¥ë¥Í¥Ã¥È¤Ç¤Ï¡¤³Æ¹©Äø¤Î½Å¤ß¤ò·×»»¤¹¤ë¡££²¼¡¥Ë¥å¡¼¥é¥ë¥Í¥Ã¥È¤Ç¤Ï¡¤Ç¼´ü¤È·ÐÈñ¤Ë´Ø¤·¤ÆÍ¿¤¨¤é¤ì¤¿¾ò·ï¤òËþ­¤¹¤ë¥¹¥±¥¸¥å¡¼¥ê¥ó¥°¤ÎºÇŬ²½¤ò¹Ô¤¤¤½¤Î¿ä¾©Ãͤò·×»»¤¹¤ë¡£¤½¤·¤Æ¡¤¿ä¾©Ãͤò»²¹Í¤Ë¤·¤ÆÂоݹ©Äø¤ÎÆâÍÆÊѹ¹¤ò¹Ô¤¤¥×¥í¥¸¥§¥¯¥È¥¹¥±¥¸¥å¡¼¥ê¥ó¥°¤ò´°À®¤¹¤ë¡£ËܹƤǤϡ¤²æ¡¹¤ÎÍѤ¤¤¿¼êË¡¤Ë¤Ä¤¤¤Æ½Ò¤Ù¤ë¤È¤È¤â¤Ë¡¤¤½¤Î¼êË¡¤òÍѤ¤¤Æ³«È¯¤·¤¿¥Ë¥å¡¼¥é¥ë¡¦¥¹¥±¥¸¥å¡¼¥ê¥ó¥°¥·¥¹¥Æ¥à¤È¤½¤Î±þÍѤȤ·¤Æ¥¨¥¯¥¹¥Æ¥ê¥¢À½Éʳ«È¯¥×¥í¥¸¥§¥¯¥È¤Ø¤ÎŬÍÑ»öÎã¤Ë¤Ä¤¤¤Æ½Ò¤Ù¤ë¡£

¾ðÊóÃμ±³Ø²ñ»ï, 1998, 8(1), 43-50

GA-based Design Tool for Piping Route Path Planning
Teruaki Ito
Department of Mechanical Engineering,The University of Tokushima

A genetic algorithm (GA) approach to support collaborative and interactive planning of a piping route path in plant layout design is presented. To present this approach, the paper mainly describes the basic ideas used in the methodology, which include the definition of genes to deal with pipe routes, the concept of spatial potential energy, the method of generating initial individuals for GA optimization, the zone concept in route generation using GAs, the evaluation of crossover methods, and definition and application of fitness functions. In order to apply the method to actual problems and to solve them in a practical manner, the study employs various heuristics, which are concept of direction, generation of initial individuals using intermediate point, extended two-points crossover, and dynamic selection. Those heuristics are also described and their effectiveness in the method is discussed. Then, the paper presents a prototype system that has been developed based on the methodology as a GA-based design tool for piping route path planning, and discusses the validity of the proposed method.

ºÇ½ª¹¹¿·Æü: 2011-02-18 (¶â) 11:36:01

¥È¥Ã¥×   ÊÔ½¸ º¹Ê¬ ¥Ð¥Ã¥¯¥¢¥Ã¥× źÉÕ Ê£À½ ̾Á°Êѹ¹ ¥ê¥í¡¼¥É   ¿·µ¬ °ìÍ÷ ñ¸ì¸¡º÷ ºÇ½ª¹¹¿·   ¥Ø¥ë¥×   ºÇ½ª¹¹¿·¤ÎRSS