TY - GEN
T1 - Weight modification method for performance evaluation model of computing system based on Bayes' theorem
AU - Fang, Daliang
AU - Lan, Yuqing
N1 - Publisher Copyright:
© 2018 Association for Computing Machinery.
PY - 2018/1/13
Y1 - 2018/1/13
N2 - The definition of a computing system in this paper refers to an integrated system that includes hardware of common computer equipment (servers, personal computers) and operating systems. With the continuous development of the domestic basic hardware and software, the performance evaluation of computing system can provide important basis for decision during its development. This paper explores a weight modification method, which aims to modify the weight of the computational system performance evaluation model that is constructed with the analytic hierarchy process. After establishing the performance evaluation model of the computing system, the model weight is regarded as the probability by the mathematical approximation, and a weight modification algorithm is proposed based on Bayes' theorem. The weight modification algorithm is analyzed, the recommended range of the relevant parameters is figured out, and the weight of the modification is elicited.
AB - The definition of a computing system in this paper refers to an integrated system that includes hardware of common computer equipment (servers, personal computers) and operating systems. With the continuous development of the domestic basic hardware and software, the performance evaluation of computing system can provide important basis for decision during its development. This paper explores a weight modification method, which aims to modify the weight of the computational system performance evaluation model that is constructed with the analytic hierarchy process. After establishing the performance evaluation model of the computing system, the model weight is regarded as the probability by the mathematical approximation, and a weight modification algorithm is proposed based on Bayes' theorem. The weight modification algorithm is analyzed, the recommended range of the relevant parameters is figured out, and the weight of the modification is elicited.
KW - Analytic Hierarchy Process
KW - Bayes' theorem
KW - Performance evaluation model
KW - Weight modification
UR - https://www.scopus.com/pages/publications/85047088541
U2 - 10.1145/3180374.3180378
DO - 10.1145/3180374.3180378
M3 - 会议稿件
AN - SCOPUS:85047088541
T3 - ACM International Conference Proceeding Series
SP - 207
EP - 211
BT - Proceedings of 2018 2nd International Conference on Management Engineering, Software Engineering and Service Sciences, ICMSS 2018
PB - Association for Computing Machinery
T2 - 2nd International Conference on Management Engineering, Software Engineering and Service Sciences, ICMSS 2018
Y2 - 13 January 2018 through 15 January 2018
ER -