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For the status that researches on customers' utility merely take up a small proportion in the studies on the cloud resource allocation, this paper proposes a cloud allocation model borrowing the idea of Network Utility Maximization(NUM)model, which maximizes the customers' utility. The model can be simplified to the Lagrangian dual function by the Lagrange function. Finally, a fuzzy subgradient algorithm...
There are many factors affect the stability of reservoir slopes, each of them is associated and coupled with others. Generally, the analysis of slopes stability can be achieved by the method of effect-factors analogy and cluster analysis. Traditional cluster analysis is difficult to obtain the stable global optimal solution, since the results are sensitive to the initial cluster center and the order...
This paper is based on data analysis and literatures, land use system, demographic factors, and economic development situation, fiscal and financial policies which have influence on the price of the house are studied. In order to discuss housing price purely on the basis of statistical data, the main factors and their weights are calculated based on the survey of house price and usage of grey theory...
Regardless of creation method, Fuzzy rules are of great importance in the implementation and optimization systems. Although using human knowledge in creating Fuzzy rules, has the advantage of readability and is near the experimental expertise, but it cannot be implemented in all systems. Since Output of a system is based on its correct function over the time, output data is reliable with higher percentage...
Complex job shop scheduling problems are mostly NP-hard. When some knowledge is imprecise, e.g., the processing times are denoted by fuzzy numbers, the fuzzy scheduling problems need new methods to be handled. ANFIS has some characteristics of self- learning, the nonlinear mapping and the form of if-then fuzzy rules. So this paper adopts ANFIS to combine the heuristic rules nonlinearly and takes the...
Fracturing sand control is a complex sand prevention method. There are so many influence factors which can not be modeled by the structuring models in both the decision and the operation process. Expert system for the optimization design of the fracturing sand control can simulate the thinking patterns of those experts, collect the computer knowledge and models in the field, apply the fuzzy mathematics...
To equilibrate the physical material in the process of inventory and transportation in supply chain operation, and to make them optimize, a multi-objective optimization model is constructed by using fuzzy mathematics, in which transportation and inventory are considered together. Through analyzing, the results are shown that the total cost of transportation can be saved effectively and the multi-objective...
The proposed work presented a modified MAX-MIN Ant System (MMAS) algorithm to solve the routing problem, in which known demand are supplied from a store house with parallel routes for new local search. Routing Problem is an optimization problem and solved to nearly optimum by heuristics. The objective of routing issues is to use a fleet of vehicles with specified capacity to serve a number of users...
Fuzzy optimization neural networks combines neural networks model with fuzzy optimization model, its application must establishes fixed expression topology according to actual problem. Aiming at the experiments in which multiple stages, influence factors and treatment levels should be considered, a tower-topology is established to simulate relationships between factors and results in this paper. In...
In this paper, a novel approach to MRI Brain Image segmentation based on the Hybrid Parallel Ant Colony Optimization (HPACO) with Fuzzy C-Means (FCM) Algorithm have been used to find out the optimum label that minimizes the Maximizing a Posterior (MAP) estimate to segment the image. There are M colonies, M-1 colonies treated as slaves and one colony for master. Each colonies visit all the pixels with...
Transformation formula between single value data and Vague data, also known as transformation formula between interval value data and Vague data, and the similarity measure formula between Vague sets. Both of them are technical support of Vague similarity measure analysis. The target of applying Vague similarity measure analysis method to optimize coconut species is to bring forward scientific suggestions...
Supply chain performance measurement has become a popular topic. However, the existing performance measure model still lacks providing interaction aspects of key performance indicators (KPIs) and measuring. The aim of this paper is therefore to propose the conceptual of performance measurement. It can be categorized into the five dimensions which are represented in term of Cost, Flexibility, Responsiveness,...
In order to find the appropriate matching pairs between knowledge demanders and knowledge suppliers, this paper researches the matching problem in knowledge service. Based on the expectation level information of demanders and the actual level information of suppliers, it is an important research topic to match the two sides in multi-attribute trade. It gives the description of multi-attribute trade...
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...
In the recent years, forests of decision trees have seen an increasing interest from the Machine Learning community since they allow to aggregate the decisions from a set of decision trees into one robust answer. However, this approach suffers from two well-known limits: first, their performances depend on the number of trees and thus finding the right size and how to aggregate decisions could be...
The probabilistic and possibilistic methods of reliability analysis of structures have been developed independently. However, the designers will prefer the flexibility of modeling the structural parameter uncertainty either probabilistically or possibilistically depending on the nature and quality of the available data. Thereby, the complex structural model will involve both types of uncertain parameters...
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...
In China, More than 458 cities and more than 50% of the population are distributed in natural disaster-prone areas. It is important to establish a complete post-disaster reconstruction and rehabilitation system to respond to sudden natural disasters. In order to get post-disaster restoration items scheduling, we invited experts to give the fuzzy preference relation coefficients on the restoration...
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...
Evolutionary algorithms are an important branch of soft computing, being able to provide approximate solutions to problems in a reasonable amount of time. The underlying principle can be realized in an almost unlimited number of ways. This paper presents four main variants of evolutionary algorithms, and a method of running them in a topology consisting of multiple populations. The resources given...
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