正在加载图片...
·82· 智能系统学报 第13卷 [58]SUNDAR S,SUGANTHAN P N,JIN C T,et al.A hybrid [6刀郭丽萍,李向涛,谷文祥,等,改进的萤火虫算法求解阻 artificial bee colony algorithm for the job-shop scheduling 塞流水线调度问题.智能系统学报,2013,81少:33-38. problem with no-wait constraint[J].Soft computing,2016. GUO Liping,LI Xiangtao,GU Wenxiang,et al.An im- 21(5):1193-1202. proved firefly algorithm for the blocking flow shop [59吴少华,单剑锋.基于改进蜂群算法的数字信号调制识 scheduling problem[J].CAAI transactions on intelligent 别[).计算机技术与发展,2016,26(7):46-50. systems,.2013,8(1):33-38 WU Shaohua,SHAN Jianfeng.A modulation identifica- [68]RAY A,DE D.An energy efficient sensor movement ap- tion algorithm for digital signals based on modified artifi- proach using multi-parameter reverse glowworm swarm cial bee colony algorithm[J].Computer technology and de- optimization algorithm in mobile wireless sensor network velopment,2016,26(7):46-50. [J].Simulation modelling practice and theory,2016,62: 60]刘霞,张姗姗,胡铭鉴.基于混沌人工蜂群算法优化的 117-136 SVM齿轮故障诊断[.吉林大学学报:信息科学版, [6杨海,丁毅,沈海斌.基于改进萤火虫算法的SVM核参 2015,33(4):476-484 数选取[.计算机应用与软件,2015,32(6):256-258, LIU Xia,ZHANG Shanshan,HU Mingjian.SVM optimiz- 287. ation based on chaotic artificial colony algorithm gear fault YANG Hai,DING Yi,SHEN Haibin.SVM kernel para- diagnosis[J].Journal of Jilin university:information sci- meter selection based on improved gso[J].Computer ap- ence edition,2015,33(4)476-484. plications and software,2015,32(6):256-258,287. [6刘铭,黄凡玲,傅彦铭,等,改进的人工蜂群优化支持向 [70]李茜楠,苏红军.基于萤火虫算法的高光谱遥感波段选 量机算法在入侵检测中的应用.计算机应用与软件, 择方法.遥感技术与应用,2014,295):761-770, 2017,341230-235,246 LI Qiannan,SU Hongjun.A novel hyperspectral band se- LIU Ming,HUANG Fanling,FU Yanming,et al.Applica- lection method using improved firefly algorithm[J].Re- tion of improved support vector machine algorithm optim- mote sensing technology and application,2014,29(5): ized by artificial bee colony algorithm in intrusion detec- 761-770. tion[J].Computer applications and software,2017,34(1): [71]刘玉坤,夏栋梁,马丽.基于AGSO-LSSVM的热点话题 230-235,246. 预测模型[J].重庆邮电大学学报:自然科学版,2014, 62]李璟民,郭敏.人工蜂群算法优化支持向量机的分类研 26(6:803-808 究).计算机工程与应用,2015,51(2):151-155 LIU Yukun,XIA Dongliang,MA Li.Hot topic prediction LI Jingmin,GUO Min.Study on classification of artificial model based on AGSO-LSSVM[J].Journal of Chongqing bee colony algorithm to optimization of support vector ma- university of posts and telecommunications:natural sci- chine[J].Computer engineering and applications,2015, ence edition,2014,26(6):803-808 51(2):151-155 [72]YANG Xinshe.A new metaheuristic bat-inspired al- [63]YANG Dalian,LIU Yilun,LI Songbai,et al.Gear fault gorithm[C]//Proceedings of Nature Inspired Cooperative diagnosis based on support vector machine optimized by Strategies for Optimization.Berlin,Heidelberg,Germany, artificial bee colony algorithm[J].Mechanism and ma- 2010:65-74. chine theory,2015,90:219-229. [73]YANG Xinshe,HE Xingshi.Bat algorithm:literature re- 64]BUI D T,TUAN T A,HOANG N D,et al.Spatial predic- view and applications[J].International journal of bio-in- tion of rainfall-induced landslides for the Lao Cai area(Vi- spired computation,2013,5(3):141-149. etnam)using a hybrid intelligent approach of least squares [74]YANG Xinshe,GANDOMI A H.Bat algorithm:a novel support vector machines inference model and artificial bee approach for global engineering optimization[J].Engineer- colony optimization[J].Landslides,2017,14(2):447-458. ing computations,2012,29(5):464-483. [65]MUSTAFFA Z,YUSOF Y,KAMARUDDIN SS.En- [75]DHAR S,ALAM S,SANTRA M,et al.A novel method hanced artificial bee colony for training least squares sup- for edge detection in a gray image based on human psycho- port vector machines in commodity price forecasting[J]. visual phenomenon and Bat algorithm[C]//Proceedings of Journal of computational science,2014,5(2):196-205. Computer Communication and Electrical Technology. [66]KRISHNANAND K N,GHOSE D.Glowworm swarm op- Murshidabad,India,2017:3-7. timisation:a new method for optimising multi-modal func- [76]ZHOU Yongquan,LUO Qifang,XIE Jian,et al.A hybrid tions[J.International journal of computational intelligence bat algorithm with path relinking for the capacitated studies..2009,1(1):93-119 vehicle routing problem[MJ//YANG Xinshe,BEKDAS G,SUNDAR S, SUGANTHAN P N, JIN C T, et al. A hybrid artificial bee colony algorithm for the job-shop scheduling problem with no-wait constraint[J]. Soft computing, 2016, 21(5): 1193–1202. [58] 吴少华, 单剑锋. 基于改进蜂群算法的数字信号调制识 别[J]. 计算机技术与发展, 2016, 26(7): 46–50. WU Shaohua, SHAN Jianfeng. A modulation identifica￾tion algorithm for digital signals based on modified artifi￾cial bee colony algorithm[J]. Computer technology and de￾velopment, 2016, 26(7): 46–50. [59] 刘霞, 张姗姗, 胡铭鉴. 基于混沌人工蜂群算法优化的 SVM 齿轮故障诊断[J]. 吉林大学学报: 信息科学版, 2015, 33(4): 476–484. LIU Xia, ZHANG Shanshan, HU Mingjian. SVM optimiz￾ation based on chaotic artificial colony algorithm gear fault diagnosis[J]. Journal of Jilin university: information sci￾ence edition, 2015, 33(4): 476–484. [60] 刘铭, 黄凡玲, 傅彦铭, 等. 改进的人工蜂群优化支持向 量机算法在入侵检测中的应用[J]. 计算机应用与软件, 2017, 34(1): 230–235, 246. LIU Ming, HUANG Fanling, FU Yanming, et al. Applica￾tion of improved support vector machine algorithm optim￾ized by artificial bee colony algorithm in intrusion detec￾tion[J]. Computer applications and software, 2017, 34(1): 230–235, 246. [61] 李璟民, 郭敏. 人工蜂群算法优化支持向量机的分类研 究[J]. 计算机工程与应用, 2015, 51(2): 151–155. LI Jingmin, GUO Min. Study on classification of artificial bee colony algorithm to optimization of support vector ma￾chine[J]. Computer engineering and applications, 2015, 51(2): 151–155. [62] YANG Dalian, LIU Yilun, LI Songbai, et al. Gear fault diagnosis based on support vector machine optimized by artificial bee colony algorithm[J]. Mechanism and ma￾chine theory, 2015, 90: 219–229. [63] BUI D T, TUAN T A, HOANG N D, et al. Spatial predic￾tion of rainfall-induced landslides for the Lao Cai area (Vi￾etnam) using a hybrid intelligent approach of least squares support vector machines inference model and artificial bee colony optimization[J]. Landslides, 2017, 14(2): 447–458. [64] MUSTAFFA Z, YUSOF Y, KAMARUDDIN S S. En￾hanced artificial bee colony for training least squares sup￾port vector machines in commodity price forecasting[J]. Journal of computational science, 2014, 5(2): 196–205. [65] KRISHNANAND K N, GHOSE D. Glowworm swarm op￾timisation: a new method for optimising multi-modal func￾tions[J]. International journal of computational intelligence studies, 2009, 1(1): 93–119. [66] 郭丽萍, 李向涛, 谷文祥, 等. 改进的萤火虫算法求解阻 塞流水线调度问题[J]. 智能系统学报, 2013, 8(1): 33–38. GUO Liping, LI Xiangtao, GU Wenxiang, et al. An im￾proved firefly algorithm for the blocking flow shop scheduling problem[J]. CAAI transactions on intelligent systems, 2013, 8(1): 33–38. [67] RAY A, DE D. An energy efficient sensor movement ap￾proach using multi-parameter reverse glowworm swarm optimization algorithm in mobile wireless sensor network [J]. Simulation modelling practice and theory, 2016, 62: 117–136. [68] 杨海, 丁毅, 沈海斌. 基于改进萤火虫算法的 SVM 核参 数选取[J]. 计算机应用与软件, 2015, 32(6): 256–258, 287. YANG Hai, DING Yi, SHEN Haibin. SVM kernel para￾meter selection based on improved gso[J]. Computer ap￾plications and software, 2015, 32(6): 256–258, 287. [69] 李茜楠, 苏红军. 基于萤火虫算法的高光谱遥感波段选 择方法[J]. 遥感技术与应用, 2014, 29(5): 761–770. LI Qiannan, SU Hongjun. A novel hyperspectral band se￾lection method using improved firefly algorithm[J]. Re￾mote sensing technology and application, 2014, 29(5): 761–770. [70] 刘玉坤, 夏栋梁, 马丽. 基于 AGSO-LSSVM 的热点话题 预测模型[J]. 重庆邮电大学学报: 自然科学版, 2014, 26(6): 803–808. LIU Yukun, XIA Dongliang, MA Li. Hot topic prediction model based on AGSO-LSSVM[J]. Journal of Chongqing university of posts and telecommunications: natural sci￾ence edition, 2014, 26(6): 803–808. [71] YANG Xinshe. A new metaheuristic bat-inspired al￾gorithm[C]//Proceedings of Nature Inspired Cooperative Strategies for Optimization. Berlin, Heidelberg, Germany, 2010: 65–74. [72] YANG Xinshe, HE Xingshi. Bat algorithm: literature re￾view and applications[J]. International journal of bio-in￾spired computation, 2013, 5(3): 141–149. [73] YANG Xinshe, GANDOMI A H. Bat algorithm: a novel approach for global engineering optimization[J]. Engineer￾ing computations, 2012, 29(5): 464–483. [74] DHAR S, ALAM S, SANTRA M, et al. A novel method for edge detection in a gray image based on human psycho￾visual phenomenon and Bat algorithm[C]//Proceedings of Computer Communication and Electrical Technology. Murshidabad, India, 2017: 3–7. [75] ZHOU Yongquan, LUO Qifang, XIE Jian, et al. A hybrid bat algorithm with path relinking for the capacitated vehicle routing problem[M]//YANG Xinshe, BEKDAŞ G, [76] ·82· 智 能 系 统 学 报 第 13 卷
<<向上翻页向下翻页>>
©2008-现在 cucdc.com 高等教育资讯网 版权所有