Search results for "Fuzzy rule"
showing 8 items of 8 documents
A context-aware approach for long-term behavioural change detection and abnormality prediction in ambient assisted living
2015
This research aims to describe pattern recognition models for detecting behavioural and health-related changes in a patient who is monitored continuously in an assisted living environment. The early anticipation of anomalies can improve the rate of disease prevention. Here we present different learning techniques for predicting abnormalities and behavioural trends in various user contexts. In this paper we described a Hidden Markov Model based approach for detecting abnormalities in daily activities, a process of identifying irregularity in routine behaviours from statistical histories and an exponential smoothing technique to predict future changes in various vital signs. The outcomes of t…
Predicting the Short-Term Exchange Rate Between United State Dollar and Czech Koruna Using Hilbert-Huang Transform and Fuzzy Logic
2017
In this paper, the combination of the Hilbert-Huang Transform, fuzzy logic and an embedding theorem is described to predict the short-term exchange rate from United States dollar to Czech Koruna. By Using the Hilbert-Huang Transform as an adaptive filter, the proposed method decreases the embedding dimension space from five (original samples) to four (de-noising samples). This dimension space provides the number of inputs to the fuzzy rule base system, which causes the number of rules, the time for training and the inference process to decrease. Experimental results indicated that this method achieves higher accuracy prediction than the direct use of original data.
Boosting Design Space Explorations with Existing or Automatically Learned Knowledge
2012
During development, processor architectures can be tuned and configured by many different parameters. For benchmarking, automatic design space explorations (DSEs) with heuristic algorithms are a helpful approach to find the best settings for these parameters according to multiple objectives, e.g. performance, energy consumption, or real-time constraints. But if the setup is slightly changed and a new DSE has to be performed, it will start from scratch, resulting in very long evaluation times. To reduce the evaluation times we extend the NSGA-II algorithm in this article, such that automatic DSEs can be supported with a set of transformation rules defined in a highly readable format, the fuz…
Risk assessment of component failure modes and human errors using a new FMECA approach: application in the safety analysis of HDR brachytherapy
2014
Failure mode, effects and criticality analysis (FMECA) is a safety technique extensively used in many different industrial fields to identify and prevent potential failures. In the application of traditional FMECA, the risk priority number (RPN) is determined to rank the failure modes; however, the method has been criticised for having several weaknesses. Moreover, it is unable to adequately deal with human errors or negligence. In this paper, a new versatile fuzzy rule-based assessment model is proposed to evaluate the RPN index to rank both component failure and human error. The proposed methodology is applied to potential radiological over-exposure of patients during high-dose-rate brach…
A Fuzzy Adaptive Controller for an Ambient Intelligence Scenario
2014
The definition of effective energy saving strategies capable of satisfying users’ requirements for environmental wellness is a complex task that requires the definition of well-tuned optimization algorithms. Sensory information depends on the environments observed, hence the model adopted to describe it should be adaptive and dynamic. This chapter presents a methodology for the tuning of a fuzzy controller capable of minimizing energy consumption while maximizing the users comfort in an Ambient Intelligence Scenario. A meta-heuristic search algorithm produces different sets of fuzzy rules depending on the needs of the system. An ontology has been developed to describe the configurations of …
Fuzzy Systems Based on Multispecies PSO Method in Spatial Analysis
2012
We present a method by using the hierarchical cluster-based Multispecies particle swarm optimization to generate a fuzzy system of Takagi-Sugeno-Kang type encapsulated in a geographical information system considered as environmental decision support for spatial analysis. We consider a spatial area partitioned in subzones: the data measured in each subzone are used to extract a fuzzy rule set of above mentioned type. We adopt a similarity index (greater than a specific threshold) for comparing fuzzy systems generated for adjacent subzones.
Fuzzy sliding mode control design for a class of disturbed systems
2014
This paper discusses the problem of the fuzzy sliding mode control for a class of disturbed systems. First, a fuzzy auxiliary controller is constructed based on a feedback signal not only to estimate the unknown control term, but also participates in the sliding mode control due to the fuzzy rule employed. Then, we extend our theory into the cases, where some kind of system information can not be obtained, for better use of our theoretical results in real engineering. Finally, some typical numerical examples are included to demonstrate the effectiveness and advantage of the designed sliding mode controller. Refereed/Peer-reviewed
Ordered fuzzy rules generation based on incremental dataset
2021
This paper proposes a novel approach for building transparent knowledge-based systems by generating interpretable fuzzy rules that allow for present dependences between quantitative variables by accounting for uncertainty and the dynamics of their values. In the approach, IF-THEN rules are used to show the conditional relationship between the ordered fuzzy numbers, which contain additional information about the tendencies of variables' value changes. This paper elaborates an approach of mining ordered fuzzy rules from numerical data included in an incremental database. This approach develops the ability to record uncertainty and its change in the context of rapidly changing data. In additio…