This volume collects the accepted papers presented at the Learning and Intelligent OptimizatioN conference (LION 2007 II) held December 8–12, 2007, in Trento, Italy. The motivation for the meeting is related to the c...
详细信息
ISBN:
(数字)9783540926955
ISBN:
(纸本)9783540926948
This volume collects the accepted papers presented at the Learning and Intelligent OptimizatioN conference (LION 2007 II) held December 8–12, 2007, in Trento, Italy. The motivation for the meeting is related to the current explosion in the number and variety of heuristic algorithms for hard optimization problems, which raises - merous interesting and challenging issues. Practitioners are confronted with the b- den of selecting the most appropriate method, in many cases through an expensive algorithm configuration and parameter-tuning process, and subject to a steep learning curve. Scientists seek theoretical insights and demand a sound experimental meth- ology for evaluating algorithms and assessing strengths and weaknesses. A necessary prerequisite for this effort is a clear separation between the algorithm and the expe- menter, who, in too many cases, is "in the loop" as a crucial intelligent learning c- ponent. Both issues are related to designing and engineering ways of "learning" about the performance of different techniques, and ways of using memory about algorithm behavior in the past to improve performance in the future. Intelligent learning schemes for mining the knowledge obtained from different runs or during a single run can - prove the algorithm development and design process and simplify the applications of high-performance optimization methods. Combinations of algorithms can further improve the robustness and performance of the individual components provided that sufficient knowledge of the relationship between problem instance characteristics and algorithm performance is obtained.
This volume contains the papers selected for presentation at the 11th Int- national Conference on Rough Sets, Fuzzy Sets, Data Mining, and Granular Computing (RSFDGrC 2007), a part of the Joint Rough Set Symposium (JR...
详细信息
ISBN:
(数字)9783540725305
ISBN:
(纸本)9783540725299
This volume contains the papers selected for presentation at the 11th Int- national Conference on Rough Sets, Fuzzy Sets, Data Mining, and Granular Computing (RSFDGrC 2007), a part of the Joint Rough Set Symposium (JRS 2007) organized by Infobright Inc. and York University. JRS 2007 was held for the ?rst time during May 14–16, 2007 in MaRS Discovery District, Toronto, Canada. It consisted of two conferences: RSFDGrC 2007 and the Second Int- national Conference on Rough Sets and Knowledge Technology (RSKT 2007). The two conferences that constituted JRS 2007 investigated rough sets as an emerging methodology established more than 25 years ago by Zdzis law Pawlak. Roughsettheoryhasbecomeanintegralpartofdiversehybridresearchstreams. In keeping with this trend, JRS 2007 encompassed rough and fuzzy sets, kno- edgetechnologyanddiscovery,softandgranularcomputing,dataprocessingand mining, while maintaining an emphasis on foundations and applications. RSFDGrC 2007 followed in the footsteps of well-established international initiatives devoted to the dissemination of rough sets research, held so far in Canada, China, Japan, Poland, Sweden, and the USA. RSFDGrC was ?rst - ganized as the 7th International Workshop on Rough Sets, Data Mining and Granular Computing held in Yamaguchi, Japan in 1999. Its key feature was to stress the role of integrating intelligent information methods to solve real-world, large, complex problems concerned with uncertainty and fuzziness. RSFDGrC achieved the status of a bi-annual international conference, starting from 2003 in Chongqing, China.
An asynchronous unit delay is an n input n output asynchronous sequential circuit in which the present value of the output n-tuple is equal to the value of the input n-tuple prior to the last input change. This paper ...
详细信息
An asynchronous unit delay is an n input n output asynchronous sequential circuit in which the present value of the output n-tuple is equal to the value of the input n-tuple prior to the last input change. This paper considers the problem of determining when a fundamental mode flow table is realizable as a feedback-free connection of asynchronous unit delays. It is shown that such a realization exists if and only if the flow table is asynchronous definite, where the asynchronous definite property is a modification of the definite property of synchronous sequential machines. A straightforward method of realizing asynchronous definite flow tables without critical races by feedback-free circuits of asynchronous unit delays and combinational gates is developed. The use of asynchronous unit delays for definite tables avoids complicated secondary assignment problems, results in circuits with very simple structure, and brings closer the theories of synchronous and asynchronous sequential machines.
暂无评论