Information fusion is an advanced research area which can assist decision makers in enhancing their decisions. This paper aims at designing a new multi-layer framework that can support the process of performing decisions from the obtained beliefs using information fusion. Since it is not an easy task to cross the gap between computed beliefs of certain hypothesis and decisions, the proposed fra...

Characteristics of uncertainty and imprecision, even imperfection is presented from knowledge acquisition in map reconstruction of autonomous mobile robots. Especially in the course of building grid map using sonar, this characteristic of uncertainty is especially servere. Jean Dezert and Florentin Smarandache have recently proposed a new information fusion theory (DSmT), whose greatest merit i...

Robot perception is becoming more and more popular with the development of artificial intelligence in computer science. Many sensors are usually involved to get a better perception of the surrounding unknown environment, especially multi-sonar sensors because of their low cost, simplicity and convenience. However the information acquired from multi-sonar sensors in building maps presents charac...

For nodes deployment of heterogeneous sensor network, based on different probability sensing models of heterogeneous nodes, refer to organic small molecule model, ‘class-molecule’ sensing model of heterogeneous nodes is proposed. Combined with DSmT data fusion model, the changes of network coverage ratio after using the new sensing model and data fusion algorithm is studied. According to the re...

Traditional particle filter (PF) will have bad effect when the target’s color is similar to the background or the target is blocked, and an improved tracking algorithm is presented in the framework of PF and DSmT. According to the location cue, a new tracking approach is given to establish the model of multiple moving targets based on information fusion. Experimental results demonstrate that th...

Quite often, during long-distance pipe leakage, critical decisions have to be made quickly and with as much certainty as possible using conflicting and uncertain sources of information. Key to providing quality decision options is an appropriate method of combining, or fusing, these heterogeneous evidence sources. Since the development of belief function theory introduced by Shafer in the 1970s...

Modern systems for information retrieval, fusion and management need to deal more and more with information coming from human experts usually expressed qualitatively in natural language with linguistic labels. In this paper, we propose and use two new 2-Tuple linguistic representation models (i.e., a distribution function model (DFM) and an improved Herrera-Mart́ınez’s model) jointly with the fu...

Any decision is closely linked to the quality and availability of information. Innovative methodologies are proposed to help decisions based on imperfect information provided by more or less reliable and conflicting sources in uncertain context. These methods combine new uncertainty theories and multicriteria decision making. The ER-MCDA methodology associates the Analytic Hierarchy Process (AH...

In this paper, we present a Non-Bayesian conditioning rule for belief revision. This rule is truly Non-Bayesian in the sense that it doesn’t satisfy the common adopted principle that when a prior belief is Bayesian, after conditioning by X, Bel(X|X) must be equal to one. Our new conditioning rule for belief revision is based on the proportional conflict redistribution rule of combination develo...