Simulation Study And Application Of Fuzzy Multi-attribute Decision Making Model In Heterogeneous Networks Convergence

The convergence of heterogeneous wireless access technologies has been envisioned to characterize the next generation wireless networks.In order to keep the communication with characteristics such as a high speed of transmission,a large capacity,an universal converge and a realization of optimum distribution of resources,and provide users with broadband,individualized and intelligentized services,we need to strategically combining those access technologies and realize a converged system.Moreover the decision-making mechanisms in many pivotal technologies tend to be comprehensive multi-attribute decision-making process in the heterogeneous wireless network environment.This paper studied some key methods of multi-attribute decision making model in the heterogeneous networks.The normalization of attribute values is quite critical to the final decision making in the multi-attribute decision making model in the heterogeneous networks.A novel normalization method is proposed.The innovation lies in that it takes into account two types of information:one is the difference between the attribute values of current alternative and the others under the same attribute,and the other one is the correlation between the attribute values of current alternative and the ideal solutions.As a result,the normalized attribute values can reflect the original diversity between current alternative and the others under the same attribute and the performance of the current alternative simultaneously.The stability and efficiency of the new normalization method have been verified by simulations.Determining the weights of attributes has been a difficulty in the field of multi-attribute decision making model in the heterogeneous networks.This paper studied the models of calculating weights both in the intuitionistic fuzzy multi-attribute decision making process and the unambiguous decision making process.On one hand,we introduced a novel distance measure between intuitionistic fuzzy sets(IFSs)and a new weight model,which based on the new distance formula and the principle of maximum deviation in the intuitionistic fuzzy multi-attribute decision making process.A new trapezoidal approximation of IFSs and a novel distance measure between IFSs based on the area relations of membership function graphs of their corresponding trapezoidal fuzzy sets are proposed.The main innovation of our distance approach for IFSs consists in integrating comprehensive and continuous information in calculation instead of partial discrete variables,which can efficiently avoid information loss and better distinguish IFSs.Then from the perspective of facilitating the decision making,an optimization model is developed on the basis of attributes diversity calculated by the distance measure.Simulations demonstrate the effectiveness of the above methods.On the other hand,an innovative mathematical model determining the objective weights of attributes based on the entropy and cross-entropy measure was put forward in the unambiguous decision making environment.This model gave the bigger weight to attributes who satisfy the following constraints simultaneously:the attribute can better distinguish alternatives;the attribute contains less uncertainty.Simulations show ours more effective and practical compared with some other methods.