The Infona portal uses cookies, i.e. strings of text saved by a browser on the user's device. The portal can access those files and use them to remember the user's data, such as their chosen settings (screen view, interface language, etc.), or their login data. By using the Infona portal the user accepts automatic saving and using this information for portal operation purposes. More information on the subject can be found in the Privacy Policy and Terms of Service. By closing this window the user confirms that they have read the information on cookie usage, and they accept the privacy policy and the way cookies are used by the portal. You can change the cookie settings in your browser.
Representation of spatial information in unpredictable environments is restricted by uncertainty, complexity, and unreliability issues of mobile robots and their environments. In this context, a new cognitive approach based on the dynamic evolution of the grey hazy set will be proposed. The dynamic evolution of the grey hazy set is able to emulate human gradually cognitive experience about how to...
In this paper we show how deductive and abductive reasoning in distributed authorisation can be efficiently ported to Android. Such logical-inference processes prove to be important tools due to the intrinsic autonomic-nature of these mobile devices. Both deduction and abduction are represented by using Constraint Handling Rules (CHR), a high-level declarative constraint programming-language, and...
Background: Clinical decision support is a tool to help experts make optimal and efficient decisions. However, little is known about the high level of abstractions in the thinking process for the experts. Objective: The objective of the study is to understand how clinicians manage complexity while dealing with complex clinical decision tasks. Method: After approval from the Institutional Review Board...
It is worthwhile to incorporate human knowledge with conventional machine learning approaches for big data analytics. Focusing on big video data understanding, this paper presents a formal scenario recognition framework where knowledge-based logic representation and reasoning is combined with data-based learning approach to enhance scenario recognition capabilities. This is achieved via multi-layered...
Evidential networks are considered as a powerful and flexible tools, commonly used for analyzing complex systems and handling different types of uncertainty in data. A crucial step to benefit from the reasoning process in these models is to quantify them. Thus, we address, in this paper, the issue of estimating parameters in evidential networks from evidential databases, by applying the maximum likelihood...
Group decision making problems are characterized by the participation of multiple experts with different points of view, who attempt to find a common solution to a problem composed by a set of alternatives. Such problems are often defined in environments of uncertainty caused by the imprecision and vagueness of information, therefore experts must utilize appropriate information domains to deal with...
In this paper, the conventional Fuzzy Cognitive Maps (FCMs), which has already achieved success in many fields, are extended by using triangular fuzzy numbers (TFNs). The advantage of FCMs is that they are relatively easy to construct and parameterize and are capable of handling the full range of system feedback structure, including density-dependent effects. However, it is a well-known fact that...
Multi-source decision is considered to be useful to make completed results. In this paper, D-S evidence theory is used to do multi-source decision fusion, and the conflict between evidences is thought to be caused by the uncertainty of mass function. In many traditional researches, evidence's own characteristics are seldom considered when fusing different mass functions. To solve this problem, the...
With the ability of data mining and reasoning, Bayesian network could well solve the problems with uncertainties and incompletion, and the result of assessment is closer to the real condition. Therefore, the Bayesian network is to solve the problems in battle damage assessment. The paper firstly analyses the damage indexes and variables of UAV-to-ground attacking. Given conditional probability by...
This paper presents a fuzzy multicriteria decision making approach for evaluating and selecting the most suitable solid waste disposal method and disposal site respectively. Case-based reasoning and fuzzy IF-THEN rules are adopted for evaluating and determining the most suitable solid waste disposal method based on past experiences. An efficient algorithm is developed for producing a performance index...
System fault detection and recovery deals with a decision problem under uncertainty in which we first attempt to isolate a fault according to information we collect regarding the system behavior, and after to recovery from the failure by the application of some recovery actions. In this paper we propose a method which makes use of Bayesian networks to reason under uncertainty and decision analysis...
As the fuzzy set is actually a precise constant function, it can't accurately describe the uncertainty of the language. While the determining of type-2 fuzzy set(T2FS) membership function is provided with a certain degree of freedom, which is convenient to facilitate the calculation. Meanwhile, the determination of the continuous primary membership function contains the uncertain influence caused...
Measuring semantic similarity between words is a classical problem in nature language processing, the result of which can promote many applications such as machine translation, word sense disambiguation, ontology mapping, computational linguistics, etc. This paper combines knowledge-based methods with statistical methods in measuring words similarity, the novel aspect of which is that subjective Bayes...
A Simple Temporal Network with Uncertainty (STNU) is a data structure for representing and reasoning about temporal constraints where the durations of certain temporal intervals---the contingent links---are only discovered during execution. The most important property of anSTNU is whether it is dynamically controllable (DC)---that is, whether there exists a strategy for executing time-points that...
Since the ship fire is a result of multiple risk factors combined effect, its assessment is a process of multiple risk factors quantification analysis. Majority of these risk factors, which are often intangible, dynamic, and artificial, are very difficult to be quantified. To solve this problem, a method named as ontology Based ship fire risk assessment is proposed. Firstly, the ship fire ontology...
The Semantic Web vision introduces the concept of machine-oriented web information. This information is characterized by the notions of uncertainty and vagueness. Towards this notions, an ontology model for representing uncertain or vague information, as well as an inference method for reasoning about this kind of information is necessary. Our approach faces the aforementioned issues, i.e. the imperfect...
The similarity measure and entropy of fuzzy sets are two important fuzzy measures in fuzzy logic theory and it is significant to research their relationship. In this paper, we mainly discuss the relationship between the similarity measure and entropy of interval type-2 fuzzy sets (IT2 FSs) proposed by Zheng et al., and give two Theorems and a Corollary that can reflect the mutual conversion relationship...
Creation and design of products based on human sensory perceptions, such as color, smell or taste, require the participation of professionals or experts with highly developed sensory abilities. When a group of experts is involved in such creative process as a team, consensus and group decision-making (GDM) techniques able to deal with qualitative descriptions and uncertainty, can be required. In this...
This paper proposes an enhanced fuzzy evidential reasoning (EFER) approach for decision making for means of water quality monitoring in the distribution networks under uncertain data and subjective knowledge. The proposed EFER approach can model epistemic uncertainties including ambiguity, interval-valued belief degrees and vagueness in information related to a complex system. Nonlinear optimization...
This paper is devoted to the problem of measuring similarity between pieces of uncertain (incomplete) information in the framework of I-fuzzy set theory (Atanassov's intuitionistic fuzzy sets and interval-valued fuzzy sets). We propose a way of determining an interval-valued similarity measure of I-fuzzy sets that preserves information about the operands' uncertainty by approximating lower and upper...
Set the date range to filter the displayed results. You can set a starting date, ending date or both. You can enter the dates manually or choose them from the calendar.