Papers by Keyword: Weight Value

Abstract: The Dempster-Shafer (D-S) evidence theory is an effective method for uncertain information fusion. Because multiple evidences from different sources of different importance or reliability in the reassembling fractured 3D objects are not equally important when they are combined. This paper presents a social cognitive optimization algorithm (SCO) to generate optimal evidence weight values based on historical training data. In the algorithm, a constrained nonlinear optimized model is established, which is solved by SCO. Compared with the two methods, optimization weight D-S proves more effective than the traditional D-S.

Abstract: It introduces the algorithm of particle filter and the Bayes theory. The way is improved necessarily in the navigation system and then used in it. When one channel in the system is interfered and can’t work, using the changing particle’s weight factors which stand for the emanative channel in the system can control the interferer. The simulation shows the particle filter algorithm can through other channels control the interferer which occurs in the one channel. So the system also can work naturally.

Abstract: To discover requested web services in Internet, this paper proposes a new web service discovery algorithm based on ontology. It uses tree-form data structure to describe the web services and give all the nodes a weight value by certain strategy, then compute the semantic similarity between the web services requested and the services registered. To validate the feasibility and effectiveness of the algorithm, the paper constructs a self-developed prototype system to show how well it works. The experiments prove that this algorithm has high recall rate and precision than other methods.

Abstract: In this paper, we present a solution developed at rough set theory and weight value to make multiattribute decision with incomplete information. The paper defined the concepst of breaking points and recovered the incomplete information system according to the relationship between the condition attributes and decision attributes. And introduced OWGA(ordered weight geometric averaging) operators to calculate the aggregation value of each project. Finally, selected the project with the maximum aggregation value as the best decision making. The illustration and experiments were implemented and the results indicate that the method is effective and efficient.

Abstract: The prevention of environmental pollution is an important work and an assessment indicator for thermal power enterprises,it is also the key factor for sustainable development.This paper presents a new qualitative analysis method for thermal power enterprises to analyze its environmental impact. It takes four thermal power units for example, uses entropy method to determine the weight values of indicators, and filter the indicators based on the size of the values. For the characteristic matrix of the remaining evaluation indexes, it uses multi-objective fuzzy optimization model to transform the absolute amount of the indicator values into the relative amount ones, then it calculates the positive ideal distance and negative ideal distance of each evaluation object, and ranks them based on the plus menbership grade maximal principle. The positive analysis result shows that this method has a strong practical significance, it provides a more reliable evaluation method for environmental protectors.

Abstract: Many methods have been used such as UDDI and DWS to discovery requested web services. But they are just a kind of simple syntax match based on keywords and have a low ratio and precision. This paper proposes A Semantic Web Service Discovery Method Based on Ontology. It uses tree-form data structure to describe the web services and give all the nodes a weight value by certain strategy, then compute the semantic similarity between the web services requested and the services registered. To validate the feasibility and effectiveness of the algorithm, we construct a self-developed prototype system to show how well it works. The experiments prove that this algorithm has high recall and precision than other methods.