[1] SCHANK R C. Dynamic Memory:a Theory of Reminding and Learning in Computers and People[M]. New York:Cambridge University Press,1983:227-229. [2] YEH A G O, SHI X. Case-Based Reasoning (CBR) in development control[J]. International Journal of Applied Earth Observation and Geoinformation,2001,3(3):238-251. [3] YAN A,YU H,WANG D. Case-based reasoning classifier based on learning pseudo metric retrieval[J]. Expert Systems with Applications,2017,89:91-98. [4] SARAIVA R,PERKUSICH M,SILVA L,et al. Early diagnosis of gastrointestinal cancer by using case-based and rule-based reasoning[J]. Expert Systems with Applications,2016,61:192-202. [5] XU Z,LI S,LI H,et al. Modeling and problem solving of building defects using point clouds and enhanced case-based reasoning[J]. Automation in Construction,2018,96:40-54. [6] AAMODT A, PLAZA E. Case-based reasoning:foundational issues,methodological variations,and system approaches[J]. AI Communications,1994,7(1):39-59. [7] YAN A,SHAO H,GUO Z. Weight optimization for case-based reasoning using membrane computing[J]. Information Sciences, 2014,287:109-120. [8] WILSON D R,MARTINEZ T R. Reduction techniques for instancebased learning algorithms[J]. Machine Learning,2000,38(3):257-286. [9] BRIGHTON H,MELLISH C. Advances in instance selection for instance-based learning algorithms[J]. Data Mining and Knowledge Discovery,2002,6(2):153-172. [10] SAHOO M,SAHOO S,DHAR A,et al. Effectiveness evaluation of objective and subjective weighting methods for aquifer vulnerability assessment in urban context[J]. Journal of Hydrology,2016,541(Pt B):1303-1315. [11] ALEMI-ARDAKANI M,MILANI A S,YANNACOPOULOS S, et al. On the effect of subjective, objective and combinative weighting in multiple criteria decision making:a case study on impact optimization of composites[J]. Expert Systems with Applications,2016,46:426-438. [12] BEDDOE G R,PETROVIC S. Selecting and weighting features using a genetic algorithm in a case-based reasoning approach to personnel rostering[J]. European Journal of Operational Research,2006,175(2):649-671. [13] XIAO Q,HE R,MA C,et al. Evaluation of urban taxi-carpooling matching schemes based on entropy weight fuzzy matter-element[J]. Applied Soft Computing,2019,81:No. 105493. [14] 康俊杰, 牛玉广, 张国斌, 等. 电站锅炉燃烧系统案例推理自适应寻优方法及应用研究[J]. 仪器仪表学报,2019,40(12):214-223.(KANG J J,NIU Y G,ZHANG G B,et al. Study on case-based reasoning adaptive optimization method and its application in power plant boiler combustion system[J]. Chinese Journal of Scientific Instrument,2019,40(12):214-223.) [15] 李俊达, 李远富, 李世琦, 等. 基于CBR的山区铁路隧道开挖方法辅助决策模型研究[J]. 现代隧道技术,2019,56(5):35-41. (LI J D,LI Y F,LI S Q,et al. A CBR-based aided decision model for the mountain railway tunnel excavation method[J]. Modern Tunnelling Technology,2019,56(5):35-41.) [16] 刘华, 史燕宇. 基于案例推理的交通基础设施PPP项目再谈判触发点识别研究[J]. 隧道建设(中英文),2019,39(3):348-354.(LIU H,SHI Y Y. Identification of renegotiation trigger point in transport infrastructure PPP projects based on CBR[J]. Tunnel Construction,2019,39(3):348-354.) [17] SMITI A, ELOUEDI Z. SCBM:soft case base maintenance method based on competence model[J]. Journal of Computational Science,2018,25:221-227. [18] SMITI A,ELOUEDI Z. WCOID-DG:an approach for case base maintenance based on Weighting,Clustering,Outliers,Internal Detection and Dbsan-Gmeans[J]. Journal of Computer and System Sciences,2014,80(1):27-38. [19] AYED S B,ELOUEDI Z,LEFEVRE E. An evidential integrated method for maintaining case base and vocabulary containers within CBR systems[J]. Information Sciences,2020,529:214-229. [20] TORRENT-FONTBONA F,MASSANA J,LÓPEZ B. Case-base maintenance of a personalised and adaptive CBR bolus insulin recommender system for type 1 diabetes[J]. Expert Systems with Applications,2019,121:338-346. [21] MIRJALILI S. The ant lion optimizer[J]. Advances in Engineering Software,2015,83:80-98. [22] BILMES J A. A gentle tutorial of the EM algorithm and its application to parameter estimation for Gaussian mixture and hidden Markov models:TR-97-021[R]. Berkeley:International Computer Science Institute,1998:1-15. [23] 严爱军, 余凌云, 倪鹏飞. 反渗透膜故障的案例推理诊断方法[J]. 北京工业大学学报,2018,44(11):1396-1400.(YAN A J,YU L Y,NI P F. Fault diagnosis method by case-based reasoning for reverse osmosis membrane[J]. Journal of Beijing University of Technology,2018,44(11):1396-1400.) [24] 倪鹏飞. 反渗透脱盐水处理过程的自动控制和故障诊断系统研发[D]. 北京:北京工业大学,2017:1-67.(NI P F. Research and development on automatic control and fault diagnosis system for reverse osmosis water desalination treatment process[D]. Beijing:Beijing University of Technology,2017:1-67.) [25] DUA D,GRAFF C. UCI machine learning repository[DS/OL].[2020-09-10]. http://archive.ics.uci.edu/ml. [26] PENG H,LONG F,DING C. Feature selection based on mutual information:criteria of max-dependency,max-relevance,and minredundancy[J]. IEEE Transactions on Pattern Analysis and Machine Intelligence,2005,27(8):1226-1238. |