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第3期 林燕清,等:基于NSGA-Ⅱ的扩展置信规则库激活规则多日标优化方法 ·429· 个最合适的解,如何减少算法的复杂度等,这些都 ence and technology,2015,9(8):985-994. 是将来的研究工作重点。 [13]CHEN Yuwang,YANG Jianbo,XU Dongling,et al.Infer- ence analysis and adaptive training for belief rule based 参考文献: systems[J].Expert systems with applications,2011,38(10): []周志杰,杨剑波,胡昌华,等.置信规则库专家系统与复杂 12845-12860. 系统建模M.北京:科学出版社,2011. 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[1] YANG Jianbo, LIU Jun, WANG Jin, et al. Belief rule-base inference methodology using the evidential reasoning ap￾proach-RIMER[J]. IEEE transactions on systems, man, and cybernetics-part A: systems and humans, 2006, 36(2): 266–285. [2] DEMPSTER A P. A generalization of Bayesian inference [J]. Journal of the royal statistical society. Series B (method￾ological), 1968, 30(2): 205–247. [3] SHAFER G. A mathematical theory of evidence[M]. Prin￾ceton: Princeton University Press, 1976. [4] HWANG C L, YOON K. Multiple attribute decision mak￾ing: methods and applications a state of the art survey[M]. New York: Springer, 1981: 22–34. [5] ZADEH L A. Fuzzy sets[J]. Information and control, 1965, 8(3): 338–353. [6] ZHOU Zhijie, HU Changhua, YANG Jianbo, et al. Online updating belief rule based system for pipeline leak detection under expert intervention[J]. Expert systems with applica￾tions, 2009, 36(4): 7700–7709. [7] XU Dongling, LIU Jun, YANG Jianbo, et al. Inference and learning methodology of belief-rule-based expert system for pipeline leak detection[J]. Expert systems with applications, 2007, 32(1): 103–113. [8] YANG Jianbo, LIU Jun, XU Dongling, et al. Optimization models for training belief-rule-based systems[J]. IEEE trans￾actions on systems, man, and cybernetics-part A: systems and humans, 2007, 37(4): 569–585. [9] YANG Ying, FU Chao, CHEN Yuwang, et al. A belief rule based expert system for predicting consumer preference in new product development[J]. Knowledge-based systems, 2016, 94: 105–113. [10] JIANG Jiang, LI Xuan, ZHOU Zhijie, et al. Weapon sys￾tem capability assessment under uncertainty based on the evidential reasoning approach[J]. Expert systems with ap￾plications, 2011, 38(11): 13773–13784. [11] 杨隆浩, 蔡芷铃, 黄志鑫, 等. 出租车乘车概率预测的置 信规则库推理方法[J]. 计算机科学与探索, 2015, 9(8): 985–994. YANG Longhao, CAI Zhiling, HUANG Zhixin, et al. Be￾lief rule-base inference methodology for predicting probab￾ility of taking taxi[J]. Journal of frontiers of computer sci- [12] ence and technology, 2015, 9(8): 985–994. CHEN Yuwang, YANG Jianbo, XU Dongling, et al. Infer￾ence analysis and adaptive training for belief rule based systems[J]. Expert systems with applications, 2011, 38(10): 12845–12860. [13] 常瑞, 张速. 基于优化步长和梯度法的置信规则库参数 学习方法[J]. 华北水利水电学院学报, 2011, 32(1): 154– 157. Chang Rui, Zhang Su. An algorithm for training paramet￾ers in belief rule-bases based on the gradient methods with optimization step size[J]. Journal of north China institute of water conservancy and hydroelectric power, 2011, 32(1): 154–157. [14] 吴伟昆, 杨隆浩, 傅仰耿, 等. 基于加速梯度求法的置信 规则库参数训练方法[J]. 计算机科学与探索, 2014, 8(8): 989–1001. WU Weikun, YANG Longhao, FU Yanggeng, et al. Para￾meter training approach for belief rule base using the accel￾erating of gradient algorithm[J]. Journal of frontiers of computer science and technology, 2014, 8(8): 989–1001. [15] 苏群, 杨隆浩, 傅仰耿, 等. 基于变速粒子群优化的置信 规则库参数训练方法[J]. 计算机应用, 2014, 34(8): 2161–2165. SU Qun, YANG Longhao, FU Yanggeng, et al. Parameter training approach based on variable particle swarm optim￾ization for belief rule base[J]. Journal of computer applica￾tion, 2014, 34(8): 2161–2165. [16] 王韩杰, 杨隆浩, 傅仰耿, 等. 专家干预下置信规则库参 数训练的差分进化算法[J]. 计算机科学, 2015, 42(5): 88–93. WANG Hanjie, YANG Longhao, FU Yanggeng, et al. Dif￾ferential evolutionary algorithm for parameter training of belief rule base under expert intervention[J]. Computer sci￾ence, 2015, 42(5): 88–93. [17] ZHOU Zhijie, HU Changhua, YANG Jianbo, et al. A se￾quential learning algorithm for online constructing belief￾rule-based systems[J]. Expert systems with applications, 2010, 37(2): 1790–1799. [18] CHANG Leilei, ZHOU Yu, JIANG Jiang, et al. Structure learning for belief rule base expert system: a comparative study[J]. Knowledge-based systems, 2013, 39: 159–172. [19] 王应明, 杨隆浩, 常雷雷, 等. 置信规则库规则约简的粗 糙集方法[J]. 控制与决策, 2014, 29(11): 1943–1950. WANG Yingming, YANG Longhao, CHANG Leilei, et al. Rough set method for rule reduction in belief rule base[J]. Control and decision, 2014, 29(11): 1943–1950. [20] [21] LIU Jun, MARTINEZ L, CALZADA A, et al. A novel be- 第 3 期 林燕清,等:基于 NSGA-II 的扩展置信规则库激活规则多目标优化方法 ·429·
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