3D modeling of geological anomalies based on segmentation of multiattribute fusion

3D modeling of geological bodies based on 3D seismic data is used to define the shape and volume of the bodies, which then can be directly applied to reservoir prediction, reserve estimation, and exploration. However, multiattributes are not effectively used in 3D modeling. To solve this problem, we propose a novel method for building of 3D model of geological anomalies based on the segmentation of multiattribute fusion. First, we divide the seismic attributes into edge- and region-based seismic attributes. Then, the segmentation model incorporating the edge- and region-based models is constructed within the levelset- based framework. Finally, the marching cubes algorithm is adopted to extract the zero level set based on the segmentation results and build the 3D model of the geological anomaly. Combining the edge-and region-based attributes to build the segmentation model, we satisfy the independence requirement and avoid the problem of insufficient data of single seismic attribute in capturing the boundaries of geological anomalies. We apply the proposed method to seismic data from the Sichuan Basin in southwestern China and obtain 3D models of caves and channels. Compared with 3D models obtained based on single seismic attributes, the results are better agreement with reality.

Study on effectiveness evaluation of weapon systems based on grey relational analysis and TOPSIS

To evaluate the effectiveness of weapon systems, the advantages and disadvantages of grey relational analysis and TOPSIS for multiattribute decision-making is pointed out, and an effectiveness evaluation model of weapon systems by combining grey relational analysis and TOPSIS is proposed. The model aggregates the grey relational grade and the distance to a new integrated closeness and reflects not only the trend but also the situation of the alternative. The example illuminates that the model is effective for the effectiveness evaluation of weapon systems.

Generalized ordered weighted averaging operators based methods for MADM in intuitionistic fuzzy set setting

Multiattribute decision making（MADM） problems, in which the weights and ratings of alternatives are expressed with intuitionistic fuzzy（IF） sets, are investigated.Firstly, the relative degrees of membership and the relative degrees of non-membership are formulated as IF sets, the weights and values of alternatives on both qualitative and quantitative attributes may be expressed as IF sets in a unified way.Then a MADM method based on generalized ordered weighted averaging operators is proposed.The proposed method is illustrated with a numerical example.

Cubic q-Rung Orthopair Fuzzy Linguistic Set and Their Application to Multiattribute Decision-making with Muirhead Mean Operator

The objective of this paper is to present a new concept,named cubic q-rung orthopair fuzzy linguistic set(Cq-ROFLS),to quantify the uncertainty in the information.The proposed Cq-ROFLS is a qualitative form of cubic q-rung orthopair fuzzy set,where membership degrees and nonmembership degrees are represented in terms of linguistic variables.The basic notions of Cq-ROFLS have been introduced and study their basic operations and properties.Furthermore,to aggregate the different pairs of preferences,we introduce the Cq-ROFL Muirhead mean-(MM),weighted MM-,dual MM-based operators.The major advantage of considering the MM is that it considers the interrelationship between more than two arguments at a time.On the other hand,the Cq-ROFLS has the ability to describe the qualitative information in terms of linguistic variables.Several properties and relation of the derived operators are argued.In addition,we also investigate multiattribute decision-making problems under the Cq-ROFLS environment and illustrate with a numerical example.Finally,the effectiveness and advantages of the work are established by comparing with other methods.

An estimation approach for dividable multiattribute utility of housing via questionnaires of consumers’ ordinal multicriteria preferences

Compared with ordinary commercial products, housing has many special characteristics including the multi-function characteristic. How to evaluate the multi-functional nature of housing is very useful in both theory and in application, yet it is often ignored in China. This paper introduces an approach to estimate the multicriteria function of housing using multiattribute utility theory (MAUT) based on consumers’ ordinal multicriteria preferences as determined via questionnaires. When compared with the classic framework in which MAUT is applied, this approach needs less prior information and subjective comparisons and thus can allay many of the operational difficulties involved in assessment. Some potential applications to the China housing market are also discussed.

Pricing Model of Multiattribute Derivatives Based on Mixed Process

By Analyzing the behavior and character of derivative security, the authors established a pricing model of multiattribute derivative security whose underlying asset pricing process is a mixed process, and obtained a new model for option pricing of multiattribute derivatives based on mixed process, and improved some original results.

Optimization of Group Multiattribute Decision-Making Model in Commercial Space Investment

A group multiattribute decision-making model was proposed by implementing prospect theory,multi-attribute decision-making,group decision-making and entropy methods for the optimization in commercial space investment.First,the decision-making function was decided using prospect theory by the preference of each expert to reach the comprehensive prospect value based on different investment options;second,expert decision weights were reached according to entropy method;third,the expert group decision-making information was congregated according to the group decision-making congregation algorithm to reach the most optimized investment option;finally,an example was given to demonstrate the feasibility and effectiveness of the method.This model com-prehensively takes the advantages of many methods to congregate experts'experiences and avoid the subjective influences,thus providing a scientific decision-making approach for the commercial space investment.

The Utility Additive Method and Its Usage for Studying Consumer Behavior

Multiattribute utility theory is a powerful theory tool to reveal the preferences of the consumers according to multiple attribute points of view. Utility additive (UTA) method based on Multiattribute utility theory is an ordinal regression method using linear programming. The purpose of the UTA method presented in this paper is to assess additive utility functions that aggregate multiple attributes in a composite attribute. The results of it are important for the study of consumer behavior. Finally, a simple illustrative example is presented and some extensions of the method are proposed.

Fusion Method for Interval Number Multi-sensor Information

The interval numbers are used to types and observation of sensors, a new fusion represent the characteristic values of object method for multi-sensor object recognition is proposed from the viewpoint of decision making theory. The method defines the distance matrix and grey association matrix between all object types and unknown object. After solving the optimization problem of maximizing the standard deviations for all attributes, the weights of the attributes are obtained. Thus, the result of recognition for the unknown object is given by the grey association degree. This method avoids the subjectivity of selecting attributes weights. It is straightforward and can be performed on computer easily. The simulated example demonstrates the feasibility and effectiveness of the proposed method.