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Estimating the coefficients of objective functions in multi-objective model is sometimes difficult in real situations. Mathematical analysis of statistical data is used to determine the coefficients. In various cases, the statistical data may not contain only randomness, but also fuzziness, which should be treated properly. Thus, this paper employs fuzzy random regression model to approximate the...
The fuzzy analytic hierarchy process (FAHP), which decomposes the complicated objects into simple hierarchical decision-making processes, with the fuzzy pairwise judgment matrix is constructed by the fuzzy logic relation of the factors in each layer. The total fuzzy weights are obtained based on the weight of each layer, which provide the quantitative analysis basis for the decision-making. The volume...
The advantages of soft c-means over its hard and fuzzy versions render it more attractive to use in a wide variety of applications. Its main merit lies in its relatively higher convergence speed, which is more obvious in the presence of huge high dimensional data. This work presents a new approach to accelerate the convergence of the original soft c-means. It is mainly based on an iterative optimization...
Due to the coupling and nonlinear relationship between processing variables, it is difficult to achieve the comprehensive optimization of injection part quality effectively only by conventional methods. To solve the problem above, firstly some quality indices were extracted according to the quality requirements of the product and a fuzzy comprehensive evaluation formula including the pertinent indices...
An extended evaluation method for the decision-making problems of alternatives is introsuced by means of extension theory. The extended evaluation method can carry out the decision-making problems of the alternatives based on matter-element models and extended relational degrees. The matter-element model of the desired alternative (ideal alternative) and the matter-element models of alternatives are...
The goal of this research is to identify the significant factors affecting the firm performance and estimate the system behavior in different operating conditions. By determining the statistical relations of the productivity and effectiveness of the firm with these factors, a decision-making framework can be provided to improve the system performance within the competitive strategy of the whole supply...
This paper is concerned with the optimal problem for team and member selection in Mathematical Contest in Modeling (MCM). Based on fuzzy mathematical theory and optimization theory, the optimization model for team and member selection is proposed. Specifically, in view of this proposed team selection index system, the basic qualities and abilities which mathematical modeling team members should have...
Image segmentation based on Bee Colony Algorithm (BCA) and fuzzy entropy is presented in this paper. The fuzzy entropy function is simplified with single parameter. The BCA is applied to search the minimum value of fuzzy entropy function. According to the minimum function value, the optimal image threshold is obtained. Experimental results are provided to demonstrate the superior performance of the...
Aiming at fuzziness of water-saving irrigation technology evaluation and the independence and incompatibility of each single index, a entropy-weight based fuzzy matter-element model for paddy field water-saving irrigation technology optimization was established based on the combination of fuzzy matter-element and the entropy theory in paddy field water-saving irrigation technology evaluation in the...
This paper presents an application of a neuro-fuzzy modeling approach in order to characterize essential behavior of biological processes. The gathered information from experiments was employed to develop a fuzzy model for an enzyme-catalyzed esterification process. The accuracy of developed model was validated by comparing the response of the model and actual data from experiments. A model-based...
Based on the characteristics of many factors with uncertainties in flood control, multi-objective fuzzy optimal theory and method is introduced, and multi-objective fuzzy optimal selection model of flood control's projects of storage and detention basin is established, and the model is applied in actual flood control, the problem of multi - objective decision system affected by certain factors and...
Optimization method with triangular fuzzy numbers is introduced to describe the expected yield rate and risk loss of securities investment, and a combinational fuzzy optimization model of inclinations with exchange fee to avoid risks is presented in this paper. The experimental results on the data investigated from real-world securities markets show that our new method exploits a new strategy for...
Based on the fuzzy probability theory of the third kind of fuzzy events, a new multi-objective optimization model of fuzzy probability is developed. And the application procedure of the fuzzy probability model is illuminated in detail. In order to assess index weighted value scientifically, the analytic hierarchy process (AHP) is introduced into the fuzzy weighted values to avoid the uncertainties...
Reliability of the Fuzzy Association Rules (FARs) extraction is a challenging research in knowledge discovery and data mining. Reliability refers to the trade-off between the prediction accuracy and the rules diversity. In this paper, an approach called Diverse Fuzzy Rule Base (DFRB) is proposed to extract the FARs which are used later to predict the future values. This approach also aims to ensure...
C-regression models are known as very useful tools in many fields. Since now, many trials to construct c-regression models for data with uncertainty in independent and dependent variables have been done. However, there are few c-regression models for data with uncertainty in independent variables in comparison with dependent variables now. The reason is as follows. The models are constructed using...
The shelling performance of a certain model castor capsule sheller with a twin-roller structure is affected by many factors, such as the roller gap, roller rotation speed, rotation speed differential and moisture content of the castor capsule. In addition, the shelling performance is usually measured in two competing indexes such as the shelling rates and the broken rates. In this paper, the orthogonal...
CM is the grouping of discrete multi-machines that produce part families with similar geometry or sequence of process and aims to improve manufacturing systems productivity. The methods/models used are classified into: array-based, clustering, mathematical programming based (viz., integer programming), graph theoretic, Multi-Criteria Decision-Making (MCDM) and artificial intelligence techniques. Fuzzy...
Proposed a T-S Fuzzy to improve the performance of a integrated GNSS and MEMS-IMU which be used in a land vehicle. The T-S Fuzzy model is used to predict the position and velocity errors, inputs these errors to Kalman filter during GNSS signal outages. The performances of the model were simulated test and compared to the common Kalman filter. The results show the integrated system used the proposed...
We developed a chaos quantum honey bee algorithm inspired by the foraging and mating procedure of honey bee colony, incorporating chaos optimization and quantum computation to optimize complex uncertain problems such as transmission system expansion planning based on random fuzzy chance-constrained programming. This paper designed calculation steps and the solution, Gauss quantum mutation is used...
Considered is two-stage method of identification of fuzzy cognitive models of preferences systems of the decision maker (DM PS) for information reflexive systems. At the first stage optimization and non-optimization methods were used, while at the second stage we used the methods of inverse problem.
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