干旱区生态环境知识资源中心(Arid): Classifying and Predicting Salinization Level in Arid Area Soil Using a Combination of Chua's Circuit and Fractional Order Sprott Chaotic System

Arid

DOI	10.3390/s19204517
	Classifying and Predicting Salinization Level in Arid Area Soil Using a Combination of Chua's Circuit and Fractional Order Sprott Chaotic System
	Tian, Anhong 1; Fu, Chengbiao 1; Su, Xiao-Yi 2; Yau, Her-Terng 3; Xiong, Heigang4,5
通讯作者	Yau, Her-Terng
来源期刊	SENSORS
EISSN	1424-8220
出版年	2019
卷号	19 期号:20
英文摘要	Soil salinization is very complex and its evolution is affected by numerous interacting factors produce strong non-linear characteristics. This is the first time fractional order chaos theory has been applied to soil salinization-level classification to decrease uncertainty in salinization assessment, solve fuzzy problems, and analyze the spectrum chaotic features in soil with different levels of salinization. In this study, typical saline soil spectrum data from different human interference areas in Fukang City (Xinjiang) and salt index test data from an indoor chemical analysis laboratory are used as the base information source. First, we explored the correlation between the spectrum reflectance features of soil with different levels of salinization and chaotic dynamic error and chaotic attractor. We discovered that the chaotic status error in the 0.6 order has the greatest change. The 0.6 order chaotic attractors are used to establish the extension matter-element model. The determination equation is built according to the correspondence between section domain and classic domain range to salinization level. Finally, the salt content from the chemical analysis is substituted into the discriminant equation in the extension matter-element model. Analysis found that the accuracy of the discriminant equation is higher. For areas with no human interference, the extension classification can successfully identify nine out of 10 prediction data, which is a 90% identification accuracy rate. For areas with human interference, the extension classification can successfully identify 10 out of 10 prediction data, which is a success rate of 100%. The innovation in this study is the building of a smart classification model that uses a fractional order chaotic system to inversely calculate soil salinization level. This model can accurately classify salinization level and its predictive results can be used to rapidly calculate the temporal and spatial distribution of salinization in arid area/desert soil.
英文关键词	fractional order compound master-slave chaotic system extension matter-element model arid area soil dynamic error salinization level areas with different levels of human interference
类型	Article
语种	英语
国家	Peoples R China ; Taiwan
开放获取类型	Green Published, gold
收录类别	SCI-E
WOS记录号	WOS:000497864700165
WOS关键词	SALT CONTENT ; CHINA ; SALINITY ; SPECTRA ; REGION
WOS类目	Chemistry, Analytical ; Engineering, Electrical & Electronic ; Instruments & Instrumentation
WOS研究方向	Chemistry ; Engineering ; Instruments & Instrumentation
EI主题词	2019-10-02
来源机构	新疆大学
资源类型	期刊论文
条目标识符	http://119.78.100.177/qdio/handle/2XILL650/310258
作者单位	1.Qujing Normal Univ, Coll Informat Engn, Qujing 655011, Peoples R China; 2.Natl Taipei Univ Technol, Grad Inst Automat Technol, Taipei 10608, Taiwan; 3.Natl Chin Yi Univ Technol, Dept Elect Engn, Taichung 41170, Taiwan; 4.Beijing Union Univ, Coll Appl Arts & Sci, Beijing 100083, Peoples R China; 5.Xinjiang Univ, Coll Resource & Environm Sci, Urumqi 830046, Peoples R China
推荐引用方式 GB/T 7714	Tian, Anhong,Fu, Chengbiao,Su, Xiao-Yi,et al. Classifying and Predicting Salinization Level in Arid Area Soil Using a Combination of Chua's Circuit and Fractional Order Sprott Chaotic System[J]. 新疆大学,2019,19(20).
APA	Tian, Anhong,Fu, Chengbiao,Su, Xiao-Yi,Yau, Her-Terng,&Xiong, Heigang.(2019).Classifying and Predicting Salinization Level in Arid Area Soil Using a Combination of Chua's Circuit and Fractional Order Sprott Chaotic System.SENSORS,19(20).
MLA	Tian, Anhong,et al."Classifying and Predicting Salinization Level in Arid Area Soil Using a Combination of Chua's Circuit and Fractional Order Sprott Chaotic System".SENSORS 19.20(2019).