Application of Interval Type-2 Fuzzy Linear Programming to Chlorine Injection in a Water Distribution System

被引:0
作者
Wang, Yumin [1 ]
Ran, Weijian [2 ]
机构
[1] Southeast Univ, Sch Energy & Environm, 2 Sipailou St, Nanjing 210096, Jiangsu, Peoples R China
[2] Univ Elect Sci & Technol, Sch Glasgow, Chengdu 610054, Sichuan, Peoples R China
关键词
Water distribution system (WDS); Type-2 fuzzy number; Fuzzy linear programming (FLP); Injection mass; Booster cost; CHANCE-CONSTRAINED OPTIMIZATION; BOOSTER DISINFECTION; LOCATION; DESIGN; MODEL;
D O I
10.1061/JWRMD5.WRENG-6268
中图分类号
TU [建筑科学];
学科分类号
0813 ;
摘要
In this paper, an interval type-2 fuzzy linear programming (IT2FLP) model was proposed to deal with uncertainty in booster optimization of a water distribution system (WDS). The IT2FLP model was applied to two cases to verify the efficiency of the method on the booster cost optimization under uncertainty. After formulating the IT2FLP model, the injection mass and booster costs in a type-2 fuzzy set (T2FS) can be obtained. The effects of booster number and injection pattern on optimal results and nodal chlorine concentration were compared. The results indicated that the injection mass decreased with an increase of booster number. However, the booster costs may increase or decrease with the increase of booster number, which depends not only on the construction costs related to booster number, but also operation cost related to injection mass. In addition, the nodal average chlorine concentrations in the WDS become more uniform with the increase of booster number under injection pattern 1 as well as injection pattern 2. The results obtained can provide more information for managers to make boosters schemes under uncertainty.
引用
收藏
页数:14
相关论文
共 50 条
[21]   On the justification to use a novel simplified interval type-2 fuzzy logic system [J].
Biglarbegian, Mohammad ;
Mendel, Jerry M. .
JOURNAL OF INTELLIGENT & FUZZY SYSTEMS, 2015, 28 (03) :1071-1079
[22]   Low power membership function generator for interval type-2 fuzzy system [J].
Souza, Gabriel A. F. ;
Santos, Rodrigo B. ;
Faria, Lester A. .
JOURNAL OF INTELLIGENT & FUZZY SYSTEMS, 2019, 36 (06) :6103-6112
[23]   DSP-Based Optical Character Recognition System Using Interval Type-2 Neural Fuzzy System [J].
Lee, Ching-Hung ;
Chang, Feng-Yu ;
Lin, Chih-Min .
INTERNATIONAL JOURNAL OF FUZZY SYSTEMS, 2014, 16 (01) :86-96
[24]   Simplified Interval Type-2 Fuzzy Logic Systems [J].
Mendel, Jerry M. ;
Liu, Xinwang .
IEEE TRANSACTIONS ON FUZZY SYSTEMS, 2013, 21 (06) :1056-1069
[25]   On the Monotonicity of Interval Type-2 Fuzzy Logic Systems [J].
Li, Chengdong ;
Yi, Jianqiang ;
Zhang, Guiqing .
IEEE TRANSACTIONS ON FUZZY SYSTEMS, 2014, 22 (05) :1197-1212
[26]   The Reduction of Interval Type-2 LR Fuzzy Sets [J].
Chen, Chao-Lieh ;
Chen, Shen-Chien ;
Kuo, Yau-Hwang .
IEEE TRANSACTIONS ON FUZZY SYSTEMS, 2014, 22 (04) :840-858
[27]   The TOPSIS Method in the Interval Type-2 Fuzzy Setting [J].
Dymova, Ludmila ;
Sevastjanov, Pavel ;
Tikhonenko, Anna .
PARALLEL PROCESSING AND APPLIED MATHEMATICS, PPAM 2015, PT II, 2016, 9574 :445-454
[28]   An Incremental Interval Type-2 Neural Fuzzy Classifier [J].
Pratama, Mahardhika ;
Lu, Jie ;
Zhang, Guangquan .
2015 IEEE INTERNATIONAL CONFERENCE ON FUZZY SYSTEMS (FUZZ-IEEE 2015), 2015,
[29]   Interpolation functions of interval type-2 fuzzy systems [J].
Zhao, Shan ;
Li, Zhao .
JOURNAL OF INTELLIGENT & FUZZY SYSTEMS, 2021, 41 (02) :3183-3200
[30]   Efficiency Calculation with Interval Type-2 Fuzzy Sets [J].
Ercan-Teksen, Hatice .
INTELLIGENT AND FUZZY SYSTEMS, VOL 3, INFUS 2024, 2024, 1090 :606-613