Some properties of linguistic preference relation and its ranking in group decision making

The group decision making problem with linguistic pref- erence relations is studied. The concept of additive consistent linguistic preference relation is defined, and then some properties of the additive consistent linguistic preference relation are studied. In order to rank the alternatives in the group decision making with the linguistic preference relations, the weighted average is first utilized to combine the group linguistic preference relations to one linguistic preference relation, and then the transformation function is proposed to transform the linguistic preference relation to the multiplicative preference relation, and thus the Saaty＇s eigenvec- tor method （EM） of multiplicative preference relation is utilized to rank the alternatives in group decision making with the linguistic preference relations. Finally, an illustrative numerical example is given to verify the proposed method. A comparative study to the linguistic ordered weighted averaging （LOWA） operator method is also demonstrated.

Soil Atterberg Limits and Consistency Indices as Influenced by Land Use and Slope Position in Western Iran

Atterberg limits and consistency indices are used for classifications of cohesive(fine-grained) soils in relation with compaction and tillage practices. They also provide information for interpreting several soil mechanical and physical properties such as shear strength, compressibility, shrinkage and swelling potentials. Although, several studies have been conducted regarding the land use effects on various soil mechanical properties, little is known about the effects of land use and slope positions on Atterberg limits and consistency indices. This study was conducted to investigate the effects of land use and slope position on selected soil physical and chemical properties, Atterberg limits and consistency indices in hilly region of western Iran. Three land uses including dryland farming, irrigated farming and pasture and four slope positions(i.e., shoulder, backslope, footslope, and toeslope) were used for soil samplings. One hundred eleven soil samples were collected from the surface soil(0-10 cm). Selected physical and chemical properties, liquid limit(LL), plastic limit(PL) and shrinkage limit(SL) were measured using the standard methods; and consistency indices including plastic index(PI), friability index(FI), shrinkage index(SI) and soil activity(A=PI/clay) were calculated. The results showed that irrigated farming significantly increased organic matter content(OM) and OM/clay ratio, and decreased bulk density(ρb) and relative bulk density(ρb-rel) as a result of higher biomass production and plant residues added to the soil compared to other land uses. Except for sand content, OM, ρb, cation exchange capacity(CEC) and calcium carbonate equivalent(CCE), slope position significantly affected soil physical and chemical properties. The highest values of silt, OM/clay and CEC/clay were found in the toeslope position, predominantly induced by soil redistribution within the landscape. The use of complexed(COC)- noncomplexed organic carbon(NCOC) concept indicated that majority of the studied soils were located below the saturation line and the OM in the soils was mainly in the COC form. The LL, PI, FI and A showed significant differences among the land uses; the highest values belonged to the irrigated farming due to high biomass production and plant residues returned to the soils. Furthermore, slope position significantly affected the Atterberg limits and consistency indices except for SL. The highest values of LL, PI, SI and A were observed in the toeslope position probably because of higher OM and CEC/clay due to greater amount of expandable phyllosilicate clays. Overall, soils on the toeslope under irrigated farming with high LL and SI and low values of FI need careful tillage management to avoid soil compaction.

Fuzzy Consistent Relation and Decision Making

This paper presents a kind of fuzzy consistent relation, discusses its main properties - center-division transitivity, describes its combined operation. At the same time, introduce the applications of fuzzy consistent relation in decision making.

Model Checking-Based Testing of Web Applications

A formal model representing the navigation behavior of a Web application as the Kripke structure is proposed and an approach that applies model checking to test case generation is presented. The Object Relation Diagram as the object model is employed to describe the object structure of a Web application design and can be translated into the behavior model. A key problem of model checking-based test generation for a Web application is how to construct a set of trap properties that intend to cause the violations of model checking against the behavior model and output of counterexamples used to construct the test sequences. We give an algorithm that derives trap properties from the object model with respect to node and edge coverage criteria.

The construction and combined operation for fuzzy consistent matrixes

Fuzziness is one of the general characteristics of human thinking and objective things. Introducing fuzzy techniques into decision-making yields very good results. Fuzzy consistent matrix has many excellent characteristics, especially cen- ter-division transitivity conforming to the reality of the human thinking process in decision-making. This paper presents a new approach for creating fuzzy consistent matrix from mutual supplementary matrix in fuzzy decision-making. At the same time, based on the distance between individual fuzzy consistent matrix and average fuzzy consistent matrix, a kind of combined opera- tion for several fuzzy consistent matrixes is presented which reflects most opinions of experienced experts. Finally, a practical example shows its flexibility and practicability further.

On Methodology of Fuzzy Systems

Fuzziness is one of the general characteristics of human thinking and objective things.Fuzzy systems are efficient tools to simulate human thinking and execute fuzzy information processing. This paper discusses several fundamental problems on methodology of fuzzy systems briefly,including generalized fuzzy entropy, generalized defuzzification strategies and fuzzy consistent relation.

Approaches to Improving Consistency of Interval Fuzzy Preference Relations

This article introduces a consistency index for measuring the consistency level of an interval fuzzy preference relation（IFPR）.An approach is then proposed to construct an additive consistent IFPR from a given inconsistent IFPR.By using a weighted averaging method combining the original IFPR and the constructed consistent IFPR,a formula is put forward to repair an inconsistent IFPR to generate an IFPR with acceptable consistency.An iterative algorithm is subsequently developed to rectify an inconsistent IFPR and derive one with acceptable consistency and weak transitivity.The proposed approaches can not only improve consistency of IFPRs but also preserve the initial interval uncertainty information as much as possible.Numerical examples are presented to illustrate how to apply the proposed approaches.

Spoil characterisation using UAV-based optical remote sensing in coal mine dumps

The structural integrity of mine dumps is crucial for mining operations to avoid adverse impacts on the triple bottom-line.Routine temporal assessments of coal mine dumps are a compliant requirement to ensure design reconciliation as spoil off-loading continues over time.Generally,the conventional in-situ coal spoil characterisation is inefficient,laborious,hazardous,and prone to experts'observation biases.To this end,this study explores a novel approach to develop automated coal spoil characterisation using unmanned aerial vehicle(UAV)based optical remote sensing.The textural and spectral properties of the high-resolution UAV images were utilised to derive lithology and geotechnical parameters(i.e.,fabric structure and relative density/consistency)in the proposed workflow.The raw images were converted to an orthomosaic using structure from motion aided processing.Then,structural descriptors were computed per pixel to enhance feature modalities of the spoil materials.Finally,machine learning algorithms were employed with ground truth from experts as training and testing data to characterise spoil rapidly with minimal human intervention.The characterisation accuracies achieved from the proposed approach manifest a digital solution to address the limitations in the conventional characterisation approach.