干旱区生态环境知识资源中心(Arid): Comparison of three different bio-inspired algorithms to improve ability of neuro fuzzy approach in prediction of agricultural drought, based on three different indexes

Arid

DOI	10.1016/j.compag.2020.105279
	Comparison of three different bio-inspired algorithms to improve ability of neuro fuzzy approach in prediction of agricultural drought, based on three different indexes
	Aghelpour, Pouya 1; Bahrami-Pichaghchi, Hadigheh 2; Kisi, Ozgur 3
通讯作者	Aghelpour, Pouya ; Kisi, Ozgur
来源期刊	COMPUTERS AND ELECTRONICS IN AGRICULTURE
ISSN	0168-1699
EISSN	1872-7107
出版年	2020
卷号	170
英文摘要	Monitoring agricultural drought utilizing the least variables can be useful at the areas with just rain gauge stations, especially in Iran, which is located in arid belt of the world. In this study, all of the stations having long duration data in Iran (31 stations with more than 59 years' data), have been used to calculate three drought indices: (1) Palmer Drought Severity Index (PDSI); (2) Standardized Precipitation Index (SPI); (3) Multivariate Standardized Precipitation Index (MSPI). According to the recommendation of world meteorological organization (WMO), Palmer index has been defined as the reference index and SPI9 (9-month time window of SPI), SPI10, SPI11 & SPI12, and also MSPI9-12 (9-12 months' time window), was evaluated by Palmer index. The results showed significant relation between SPI11 or SPI12 and PDSI in Iran's climates. MSPI9-12 has a significant relation with PDSI too, and the correlation of MSPI with Palmer Index was found to be stronger than the SPI, in all stations. The relation between MSPI and PDSI is also stronger in extra-arid climates, and weaker in humid and per-humid areas. So, MSPI can be used for agricultural drought monitoring in the places where there are restrictions in meteorological dataset (when precipitation data are only available). In the second part, prediction of MSPI9-12 has been done using Adaptive Neuro-Fuzzy Inference System (ANFIS) merged with bio-inspired optimization algorithms. The meta-heuristic models implemented are ANFIS-ACO (ANFIS merged with Ant Colony Optimization), ANFIS-GA (ANFIS merged with Genetic Algorithm) and ANFIS-PSO (ANFIS merged with Particle Swarm Optimization). The models had their best predictions in arid, semi-arid and Mediterranean climates while humid climate provided the weakest predictions. Among the mentioned algorithms, the ACO and GA had the best performances to optimize ANFIS; they improved the ANFIS's accuracy by 45.9% and 43.2%, respectively.
英文关键词	Agricultural drought MSPI SPI PDSI Bio-inspired algorithms
类型	Article
语种	英语
国家	Iran ; Georgia
收录类别	SCI-E
WOS记录号	WOS:000519652000020
WOS关键词	SUPPORT VECTOR REGRESSION ; RIVER-BASIN ; INFERENCE SYSTEM ; COLONY OPTIMIZATION ; MODELS ; MACHINE ; ANFIS ; SEVERITY ; PDSI
WOS类目	Agriculture, Multidisciplinary ; Computer Science, Interdisciplinary Applications
WOS研究方向	Agriculture ; Computer Science
资源类型	期刊论文
条目标识符	http://119.78.100.177/qdio/handle/2XILL650/314280
作者单位	1.Univ Tehran, Coll Agr & Nat Resources, Fac Agr Engn & Technol, Dept Irrigat & Reclamat Engn,Agr Meteorol, Karaj, Iran; 2.Sari Agr Sci & Nat Resources Univ, Fac Agr Engn, Dept Water Engn, Sari, Iran; 3.Ilia State Univ, Sch Technol, Tbilisi, Georgia
推荐引用方式 GB/T 7714	Aghelpour, Pouya,Bahrami-Pichaghchi, Hadigheh,Kisi, Ozgur. Comparison of three different bio-inspired algorithms to improve ability of neuro fuzzy approach in prediction of agricultural drought, based on three different indexes[J],2020,170.
APA	Aghelpour, Pouya,Bahrami-Pichaghchi, Hadigheh,&Kisi, Ozgur.(2020).Comparison of three different bio-inspired algorithms to improve ability of neuro fuzzy approach in prediction of agricultural drought, based on three different indexes.COMPUTERS AND ELECTRONICS IN AGRICULTURE,170.
MLA	Aghelpour, Pouya,et al."Comparison of three different bio-inspired algorithms to improve ability of neuro fuzzy approach in prediction of agricultural drought, based on three different indexes".COMPUTERS AND ELECTRONICS IN AGRICULTURE 170(2020).