2018
DOI: 10.1007/s11269-018-2082-6
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Investigation the Effect of Using Variable Values for the Parameters of the Linear Muskingum Method Using the Particle Swarm Algorithm (PSO)

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Cited by 31 publications
(14 citation statements)
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“…Particle swarm optimization (PSO) algorithm is a population-based evolutionary algorithm and is used in civil engineering and water resources optimization problems such as reservoir performance (Nagesh Kumar and Janga Reddy, 2007), water quality management (Afshar et al 2011, Lu et al 2002, Chau, 2005 and optimization of the Muskingum method coefficients (Chu and Chang 2009, Moghaddam et al 2016, Bazargan and Norouzi 2018, Norouzi and Bazargan 2020, Norouzi and Bazargan 2021. Therefore, in the present study, the particle swarm optimization (PSO) algorithm was used to optimize the coefficients of the Forchheimer binomial equation (Eq.…”
Section: K = 65mentioning
confidence: 99%
“…Particle swarm optimization (PSO) algorithm is a population-based evolutionary algorithm and is used in civil engineering and water resources optimization problems such as reservoir performance (Nagesh Kumar and Janga Reddy, 2007), water quality management (Afshar et al 2011, Lu et al 2002, Chau, 2005 and optimization of the Muskingum method coefficients (Chu and Chang 2009, Moghaddam et al 2016, Bazargan and Norouzi 2018, Norouzi and Bazargan 2020, Norouzi and Bazargan 2021. Therefore, in the present study, the particle swarm optimization (PSO) algorithm was used to optimize the coefficients of the Forchheimer binomial equation (Eq.…”
Section: K = 65mentioning
confidence: 99%
“…Particle swarm optimization (PSO) algorithm is a population-based evolutionary algorithm and is used in civil engineering and water resources optimization problems such as reservoir performance (Nagesh Kumar and Janga Reddy, 2007), water quality management (Afshar et al 2011, Lu et al 2002, Chau, 2005 and optimization of the Muskingum method coefficients (Chu and Chang 2009, Moghaddam et al 2016, Bazargan and Norouzi 2018, Norouzi and Bazargan 2020.…”
Section: K =mentioning
confidence: 99%
“…}=Q[ Q}O=kt Qo = OvDiQo xH}Dv w OvOQm sUQ = Q |HwQN h= QowQO}y w OvOQm w O@=}|t V}=Ri= |HwQN |@O u= R}t CkO 'OvW=@ C@=FQ}e w Cw=iDt sD} Qwor= ? }=Q[ Q}O=kt uOw@ C@=F CQwY QO w CU= 2=44 \UwDt |@Uv |=]N u= R}t x@ 2020 u= Q=mty w xi}rN [15] "Ovm|t O=H}= = Q 89 |=]N u= R}t sD} Qwor= sD} Qwor= R= xO=iDU= =@ xOQ=m xv=NOwQ ?q}U |]NQ}e |@=} Q}Ut |R=Uxv}y@ |UQQ@ "OvOQm xU}=kt |Ww=m = Qi |=ysD}Qwor= Q}=U =@ w OvDN=OQB GOA Mrt |R=Uxv}y@ |=ysD}Qwor= x@ C@Uv sD} Qwor= u}= QD?U=vt OQmrta R= |m =L =yp}rLD w x} RHD |=yVwQ OQ@Q=m Q}N= |=yp=U QO xm OwW|t xO}O [16] "CU= xOw@ xO=iDU= OQwt uwo=vwo CqO=at |R=Uxv}y@ w |v}@V}B Qw_vtx@ |Ww=m = Qi |=ysD}Qwor= w OvtWwy xDW=O x= Qty x@ = Q |@U=vt G}=Dv xQ=wty w xOw@ hrDNt swra u=kkLt xHwD OQwt "CU= uwvm=D xm OyO|t u=Wv OvOQm xO=iDU= xr=kt u}= u=oOvU}wv xm |a@=vt |UQQ@ %CU= X k (min) X k X k (max) (9) "OyO|t u=Wv = Q K Oa@ QO q=@ OL X k (max)K Oa@ QO u}}=B OL X k (min) xm "OwW|t O=H}= p=tQv `} RwD `@=D R= xO=iDU= =@ lk=HvU |=yC}akwt '=U=U= X k = X k (min) + (X k (max) X k (min)) rand (10) w OQ}o|t |OwQw u=wva x@ = Q lk=HvU |=yC}akwt '|oOvR= Q@ `@=D l} C}=yv QO "OyO|t V}=tv = Q C= QP 'CU= xwkr=@ ?wN pLx=Q Qov=}=tv xm |OOa |HwQN l} [17] "Ovm|t |wQ}B Q} R uwv=k xU R= C= QP Q=DiQ ROrwv}Q |xDio j@] Q@ "OwW|t Qo}O pt=a =@ pt=a OQwNQ@ `v=t 'l}miD "1 "=ypt=a Q}=U x@ C@Uv pt=a CaQU '|R= QDsy "2 "OQ=O xQ=W= =yx}=Uty R= RmQt l} CtU x@ C= QP V}=Qo x@ '|oDUw}B "3…”
Section: "S}kdutq}e |Xt}qhmentioning
confidence: 99%