Decision Making Based on Valued Fuzzy Superhypergraphs

This paper explores the defects in fuzzy (hyper) graphs (as complex (hyper) networks) and extends the fuzzy(hyper) graphs to fuzzy (quasi) superhypergraphs as a new concept.We have modeled the fuzzy superhypergraphsas complex superhypernetworks in order to make a relation between labeled objects in the form of details andgeneralities. Indeed, the structure of fuzzy (quasi) superhypergraphs collects groups of labeled objects and analyzesthem in the form of the part to part of objects, the part of objects to the whole group of objects, and the whole tothe whole group of objects at the same time.We have investigated the properties of fuzzy (quasi) superhypergraphsbased on any positive real number as valued fuzzy (quasi) superhypergraphs, considering the complement of valuedfuzzy (quasi) superhypergraphs, the notation of isomorphism of valued fuzzy (quasi) superhypergraphs based onthe permutations, and we have presented the isomorphic conditions of (self complemented) valued fuzzy (quasi)superhypergraphs. The concept of impact membership value of fuzzy (quasi) superhypergraphs is introducedin this study and it is applied in designing the real problem in the real world. Finally, the problem of businesssuperhypernetworks is presented as an application of fuzzy valued quasi superhypergraphs in the real world.

AN IMPROVED ALGORITHM FOR SUPERVISED FUZZY C-MEANS CLUSTERING OF REMOTELY SENSED DATA

This paper describes an improved algorithm for fuzzy c-means clustering of remotely sensed data, by which the degree of fuzziness of the resultant classification is de- creased as comparing with that by a conventional algorithm: that is, the classification accura- cy is increased. This is achieved by incorporating covariance matrices at the level of individual classes rather than assuming a global one. Empirical results from a fuzzy classification of an Edinburgh suburban land cover confirmed the improved performance of the new algorithm for fuzzy c-means clustering, in particular when fuzziness is also accommodated in the assumed reference data.

Screening and evaluation of reliable traits of upland cotton(Gossypium hirsutum L.)genotypes for salt tolerance at the seedling growth stage

Background:Salt stress significantly inhibits the growth,development,and productivity of cotton because of osmotic,ionic,and oxidative stresses.Therefore,the screening and development of salt tolerant cotton cultivars is a key issue towards sustainable agriculture.This study subjected 11 upland cotton genotypes at the seedling growth stage to five different salt concentrations and evaluated their salt tolerance and reliable traits.Results:Several morpho-physiological traits were measured after 10 days of salinity treatment and the salt tolerance performance varied significantly among the tested cotton genotypes.The optimal Na Cl concentration for the evaluation of salt tolerance was 200 mmol·L-1.Membership function value and salt tolerance index were used to identify the most consistent salt tolerance traits.Leaf relative water content and photosynthesis were identified as reliable indicators for salt tolerance at the seedling stage.All considered traits related to salt tolerance indices were significantly and positively correlated with each other except for malondialdehyde.Cluster heat map analysis based on the morpho-physiological salt tolerance-indices clearly discriminated the 11 cotton genotypes into three different salt tolerance clusters.Cluster I represented the salt-tolerant genotypes(Z9807,Z0228,and Z7526)whereas clusters II(Z0710,Z7514,Z1910,and Z7516)and III(Z0102,Z7780,Z9648,and Z9612)represented moderately salttolerant and salt-sensitive genotypes,respectively.Conclusions:A hydroponic screening system was established.Leaf relative water content and photosynthesis were identified as two reliable traits that adequately represented the salt tolerance of cotton genotypes at the seedling growth stage.Furthermore,three salt-tolerant genotypes were identified,which might be used as genetic resources for the salt-tolerance breeding of cotton.

Low Temperature Tolerance of Parental,Inbred and Hybrid Lines of Brassica Napus at Germination Stage

In order to screen rapeseed accessions with low temperature tolerance in triple cropping area,comprehensive membership function method was used to evaluate the low temperature tolerance of 176 accessions including inbred and hybrid lines of Brassica napus with germination rate,germination energy,germination index and average germination time as indicators.The results showed that 103 accessions with strong low temperature tolerance and 27 accessions with sensitive to low temperature stress were identified.The low temperature tolerance was significant different among accessions(P<0.001)while insignificantly different among different types(sterile lines,maintainer lines,restorer lines,and hybrid lines,P=0.07).The integrated membership function value was significantly correlated with germination rate,germination index and average germination time,which provided valuable information for the future breeding of low temperature tolerant varieties,especially in the middle reaches of the Yangtze River basin.