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Parts assembly, in a broad sense, is to make multiple objects to be in specific relative poses in contact with each other. One of the major reasons that make it difficult is uncertainty. Because parts assembly involves physical contact between objects, it requires higher precision than other manipulation tasks like collision avoidance. The key idea of this paper is to use simulation-aided physical...
This paper presents a risk assessment algorithm for automatic lane change maneuvers on highways. It is capable of reliably assessing a given highway situation in terms of the possibility of collisions and robustly giving a recommendation for lane changes. The algorithm infers potential collision risks of observed vehicles based on Bayesian networks considering uncertainties of its input data. It utilizes...
This paper develops an abnormity control scheme based on fuzzy Bayesian network (BN) for the thickening process of gold hydrometallurgy. By analyzing the causes and corresponding solutions of the abnormity, the operator experience of removing the abnormity is transformed to construct the BN. The BN combines the expert knowledge with quantitative data analysis to make decisions and remove the abnormity...
Ontology learning has become a popular research field recently. However, the typical ontology may not be sufficient to represent uncertainty information. Fuzzy ontology is proposed to solve the uncertainty reasoning problems. But the construction of fuzzy ontology is still a tedious and painstaking task. The cognitive model of fuzzy ontology learning is an automatic model of fuzzy ontology construction...
Architectural Sustainability refers to the ability of an architecture to achieve its goals while sustaining its value on dimensions related to environmental, social, economic, individual and/or technical during its operation and evolution. While the process of architectural design implies a fit between the requirements, system conditions and constraints; incomplete information and uncertainty may...
Uncertainties regarding wireless propagation environments pose challenges for spectrum management in general and specifically hinder the implementation of dynamic spectrum sharing systems. Without the ability to reliably evaluate interference risks, spectrum sharing policies specify spectrum access behaviors such as exclusion zones and maximum transmit powers based on risk thresholds applied to statistical...
Ontological RDF data are extracted from multiple sources on the web through mapping and alignment for various purposes, but extracting and reasoning about ontologies from different sources causes information ambiguity and uncertainty. A reasonable solution to this problem is to annotate extracted ontology data with truth values to determine the reliability of information. However, the recent growth...
The relation of knowledge is vividly represented by hypergraph in big knowledge base. In this paper, hierarchical quotient space theory in granular computing model is applied to weighted hypergraph, so uncertainty inference of knowledge in big knowledge base is converted to the optimal path approximate of weighted hypergraph based on granular computing model. Thus, the complex degree of solving problem...
This research proposes the use of a Belief Rule-Based (BRB) approach to assess an enterprise's level commitment to environmental issues. Participating companies will have to complete a structured questionnaire. An automated analysis of their responses will determine their environmental responsibility level. This is followed by a recommendation on how to progress to the next level. The recommended...
Bronchopneumonia is an acute or chronic inflammation of the lungs, in which the alveoli and/or interstitial are affected. Usually the diagnosis of Bronchopneumonia is carried out using signs and symptoms of this disease, which cannot be measured since they consist of various types of uncertainty. Consequently, traditional disease diagnosis, which is performed by a physician, cannot deliver accurate...
Many decision problems have more than one objective that need to be dealt with simultaneously. Moreover, because of the qualitative nature of the most of real world problem it is an inevitable activity and very important to interpret and present the uncertain information for making effective decision. The Evidential Reasoning (ER) approach which is one of the latest development within multi criteria...
Fuzzy logic has flexibility in defining fuzzy sets. Zadeh defined fuzzy sets for incomplete information with single fuzzy membership. The two fold fuzzy set will give more information than the single membership function. In this paper, two fuzzy set is studied with two membership functions “Belief” and “Disbelief”. The Fuzzy Certainty Factor (FCF) is difference between “Belief” and “disbelief”. The...
In the present paper, general form of α-ordered linear resolution method is established in lattice-valued logic system with linguistic truth-values. Firstly, general form of α-ordered linear resolution method is investigated in linguistics truth-valued lattice-valued propositional logic system based on linguistics truth-valued lattice implication algebra. It can obtain a resolvent under a linguistic...
Complex clinical decision-making could be facilitated by using population health data to inform clinicians. In two previous studies, we interviewed 16 infectious disease experts to understand complex clinical reasoning. For this study, we focused on answers from the experts on how clinical reasoning can be supported by population-based Big-Data. We found cognitive strategies such as trajectory tracking,...
Planning problems are usually expressed by specifying which actions can be performed to obtain a given goal. In temporal planning problems, actions come with a time duration and can overlap in time, which noticeably increase the complexity of the reasoning process. Action-based temporal planning has been thoroughly studied from the complexity-theoretic point of view, and it has been proved to be EXPSPACE-complete...
Integrating logical and probabilistic reasoning and integrating reasoning over observations and predictions are two important challenges in AI. In this paper we propose P-MTL as an extension to Metric Temporal Logic supporting temporal logical reasoning over probabilistic and predicted states. The contributions are (1) reasoning over uncertain states at single time points, (2) reasoning over uncertain...
In order to deal with the subjectivity, epistemic uncertainty and incompleteness of input data, a novel methodology is proposed for interactive decision making between two players based on the graph model for conflict resolution (GMCR) with belief preference. First, a new GMCR model is calibrated, in which belief preferences are generated via evaluating the utilities of feasible states. Second, new...
Recently, innovative and mobile health services have been developed by embedding knowledge-based systems, with the aim of remotely promoting wellness and healthy lifestyle, monitoring patients' chronic diseases and improving their adherence to therapies. Even if different knowledge-based systems have been proposed for mobile devices, they are typically based on precise production rules built on the...
Two human factors studies were conducted to assess the effectiveness of intelligent agents' user interfaces that were designed based on the Situation awareness-based Agent Transparency (SAT) model. Results show that agents' transparency (based on the SAT model) can benefit operator performance and support proper calibration of trust in the agents. Increasing levels of transparency enhanced operator's...
Fault diagnosis is of great significance to maintain safe and stable operation of the traction power supply system. Fast diagnosing fault to restore power supply is important. A kind of TPSS fault diagnosis model based on Bayesian network considering the uncertainty of information is proposed in this paper. The fault diagnosis model inherits the capability of dealing with uncertain information of...
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