\u3010\u65e5\u6642\u30112021\u5e747\u670821\u65e5\uff08\u6c34\uff09 16:00~18:00\uff0815:45~ \u5165\u5ba4\u53ef\u80fd\uff0c\u63a5\u7d9a\u30c6\u30b9\u30c8\u306a\u3069\u3092\u884c\u3044\u307e\u3059\uff09<\/p>\n
\u3010\u5834\u6240\u3011Zoom\u30df\u30fc\u30c6\u30a3\u30f3\u30b0<\/p>\n
\u3010\u53c2\u52a0\u8cbb\u3011\u7121\u6599<\/p>\n
\u3010\u30d7\u30ed\u30b0\u30e9\u30e0\u3011
\n\u958b\u4f1a\u6328\u62f6\uff0816:00~16:05\uff09<\/p>\n
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\n\u8b1b\u5e2b\uff1a\u9ad8\u6a4b \u5948\u6d25\u7f8e \u6c0f\uff08\u9632\u885b\u5927\u5b66\u6821\uff09
\n\u984c\u76ee\uff1a\u591a\u76ee\u7684\u6700\u9069\u5316\u306b\u57fa\u3065\u304f\u30cd\u30c3\u30c8\u30ef\u30fc\u30af\u8a55\u4fa1\u624b\u6cd5
\n\u6982\u8981\uff1a\u96fb\u529b\u7db2\u3084\u901a\u4fe1\u7db2\u3068\u3044\u3063\u305f\u793e\u4f1a\u57fa\u76e4\u3092\u652f\u3048\u308b\u30b7\u30b9\u30c6\u30e0\u306e\u591a\u304f\u306f\u30cd\u30c3\u30c8\u30ef\u30fc\u30af\u69cb\u9020\u3092\u6709\u3059\u308b\u3002\u3053\u308c\u3089\u30cd\u30c3\u30c8\u30ef\u30fc\u30af\u306e\u8a55\u4fa1\u6307\u6a19\u306f\u3001\u4f8b\u3048\u3070\u9053\u8def\u4ea4\u901a\u7db2\u3084\u9244\u9053\u7db2\u3067\u306f\u76ee\u7684\u5730\u3078\u306e\u8ddd\u96e2\u3084\u6642\u9593\u3001\u901a\u4fe1\u7db2\u306a\u3069\u3067\u306f\u901a\u4fe1\u91cf\u306b\u52a0\u3048\u3066\u56de\u7dda\u63a5\u7d9a\u306e\u5b89\u5b9a\u6027\u306a\u3069\u3001\u5bfe\u8c61\u3068\u306a\u308b\u30cd\u30c3\u30c8\u30ef\u30fc\u30af\u3084\u8a55\u4fa1\u8005\u306e\u72b6\u6cc1\u306b\u3088\u308a\u69d8\u3005\u3067\u3042\u308b\u3002\u305d\u3053\u3067\u672c\u7814\u7a76\u3067\u306f\u3001\u591a\u69d8\u306a\u4fa1\u5024\u89b3\u306b\u5bfe\u5fdc\u3057\u305f\u8907\u6570\u306e\u8a55\u4fa1\u6307\u6a19\u3092\u6709\u3059\u308b\u30cd\u30c3\u30c8\u30ef\u30fc\u30af\u306e\u8a55\u4fa1\u624b\u6cd5\u306b\u3064\u3044\u3066\u691c\u8a0e\u3059\u308b\u3002\u521d\u3081\u306b\u3001\u4fe1\u983c\u5ea6\u3068\u30b3\u30b9\u30c8\u3092\u8003\u616e\u3057\u305f\u30cd\u30c3\u30c8\u30ef\u30fc\u30af\u8a2d\u8a08\u554f\u984c\u3092\u53d6\u308a\u4e0a\u3052\u308b\u3002\u3053\u306e\u554f\u984c\u306b\u5bfe\u3057\u3066\u907a\u4f1d\u7684\u30a2\u30eb\u30b4\u30ea\u30ba\u30e0\uff08GA\uff09\u306e\u9069\u7528\u3092\u691c\u8a0e\u3057\u3001\u9078\u629e\u30fb\u4ea4\u53c9\u306e\u904e\u7a0b\u306b\u304a\u3044\u3066\u3001\u30d1\u30ec\u30fc\u30c8\u89e3\u306e\u5206\u5e03\u6027\u8cea\u3092\u53cd\u6620\u3059\u308b\u3053\u3068\u3067\u3001\u751f\u6210\u500b\u4f53\u6570\u306e\u524a\u6e1b\u3092\u56f3\u308b\u3002\u6b21\u306b\u591a\u76ee\u7684\u3092\u6709\u3059\u308b\u6700\u9069\u7d4c\u8def\u63a2\u7d22\u554f\u984c\u306b\u3064\u3044\u3066\u691c\u8a0e\u3059\u308b\u3002\u7d4c\u8def\u306e\u63a2\u7d22\u7a7a\u9593\u3092\u7e2e\u5c0f\u3059\u308b\u305f\u3081\u306b\u6709\u7528\u306a\u57fa\u6e96\u7d4c\u8def\u306e\u5229\u7528\u53ca\u3073\u63a2\u7d22\u9806\u5e8f\u3092\u691c\u8a0e\u3059\u308b\u3053\u3068\u3067\u3001\u52a3\u89e3\u306e\u7d4c\u8def\u751f\u6210\u3092\u524a\u6e1b\u3057\u63a2\u7d22\u3092\u52b9\u7387\u5316\u3059\u308b\u3002<\/p>\n
\u4f11\u61a9\uff0816:55~17:05\uff09<\/p>\n
\u8b1b\u6f14\uff12\uff0817:05~17:55\uff09
\n\u8b1b\u5e2b\uff1aJunjun Zheng\uff08Ritsumeikan University\uff09
\n\u984c\u76ee\uff1aOpportunity-Based Age Replacement Models with Markovian Arrival Process
\n\u6982\u8981\uff1aIn this talk, we focus on the age replacement problems under the assumption that the arrival of opportunities follows a stochastic point process. The opportunity is a chance to make the replacement, and a unit can be replaced with low cost at the opportunity. In this work, we extend the opportunity-based age replacement models by Dekker and Dijkstra (1991) and Zhao and Nakagawa (2012) in the environment that the opportunity process is in accordance with a Markovian arrival process (MAP). The MAP is one of the general point processes, and involves a Poisson process and some classes of renewal processes. This work is the first attempt to generalize the arrival process of the preventive replacement problems with opportunities. Furthermore, we comprehensively evaluate the opportunity-based age replacement policies by Dekker and Dijkstra (1991) and Zhao and Nakagawa (2012) in our generalized modeling framework.<\/p>\n
\u9589\u4f1a\u6328\u62f6\uff0817:55~18:00\uff09<\/p>\n","protected":false},"excerpt":{"rendered":"
\u3010\u65e5\u6642\u30112021\u5e747\u670821\u65e5\uff08\u6c34\uff09 16:00~18:00\uff0815:45~ \u5165\u5ba4\u53ef\u80fd\uff0c\u63a5\u7d9a\u30c6\u30b9\u30c8\u306a\u3069\u3092\u884c\u3044\u307e\u3059\uff09 \u3010\u5834\u6240\u3011Zoom\u30df\u30fc\u30c6\u30a3\u30f3\u30b0 \u3010\u53c2\u52a0\u8cbb\u3011\u7121\u6599 \u3010\u30d7\u30ed\u30b0\u30e9\u30e0\u3011 \u958b\u4f1a\u6328\u62f6\uff0816:00~16:05\uff09 \u8b1b\u6f14\uff11\uff081 … <\/p>\n