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The objective of this paper is to present the first results concerning the mapping and implementation of the Fuzzy Semantic Model (FSM) as a Fuzzy Object-Relational database Model (FuzzORM). This solution permits to take advantages of both relational and object-oriented databases. The object-relational database management system PostgreSQL has been used for the implementation of the FuzzORM.
The paper deals with the F-transform with polynomial components with respect to a generalized fuzzy partition given by B-splines. We investigate approximation properties of the inverse F-transform in this case and prove that using B-splines allows us to improve the quality of approximation of smooth functions.
This paper presents a Fuzzy-PID controller for maximum power point tracking (MPPT) of photovoltaic (PV) systems. A DC/DC buck converter to regulate the output power of the photovoltaic system is considered. The Fuzzy-PID scheme operates on MPP and improves the performance of solar energy conversion efficiency. The offline optimization algorithm of Big Bang - Big Crunch (BB-BC) is applied on the parameters...
The recently proposed hesitant fuzzy linguistic terms sets (HFLTSs) are utilized to represent the expert's subjective preferences in a linguistic preference relation and therefore a hesitant fuzzy linguistic preference relation (HFLPR) is constructed. This paper aims to present a consensus process to assist the experts in achieving a predefined consensus level in the case of HFLPRs. A possibility...
Probabilistic fuzzy system (PFS) combines a linguistic description of the system behaviour with statistical properties of data. In this paper, we propose a multi-covariate multi-output PFS for explaining and forecasting quarterly US inflation data, which shows different patterns over time such as inflation level and volatility changes. An application of a PFS to model inflation was not considered...
Quality evaluation is a fundamental problem in the field of linguistic description of data. In this work, we analyze the concept of quality and study different approaches to measure quality. Although most of the approaches considered focused on time series data, that are one of the most frequent datasets in real application domains, they can be used for quality assessment of linguistic descriptions...
In 1996, Zadeh coined Computing With Words (CWWs) to be a methodology in which words are used instead of numbers for computing and reasoning. One of the main challenges which faced the CWWs paradigm has been modelling words adequately. Mendel has pointed out that the CWWs paradigm should employ type-2 fuzzy logic to model words. This paper proposes employing an Enhanced Interval Approach (EIA) to...
Graph databases have aroused a large interest in the last years thanks to their large scope of potential applications (e.g. social networks, biomedical networks, data stemming from the web). In a similar way as what has already been proposed in relational databases, defining a language allowing a flexible querying of graph databases may greatly improve usability of data. This paper focuses on the...
Recent studies have confirmed that the problem of female deficit in India is the result of sex selective abortion, negligence of girls, infanticides and foeticide, preference of son for the preservation for clan, gender bias and emergence of new technologies in medical field. This paper addresses this critical problem of gender inequality in India using fuzzy cognitive maps. Fuzzy cognitive maps model...
Differing from previous studies, where sliding mode control theory-based rules are proposed for only the consequent part of the network, the developed algorithm in this paper applies fully sliding mode parameter update rules for both the premise and consequent parts of the interval type-2 fuzzy neural networks. The stability of the proposed learning algorithm has been proved by using an appropriate...
Most real world classification problems involve a high degree of uncertainty, unsolved by a traditional type-1 fuzzy classifier. In this paper, a novel interval type-2 classifier, namely Evolving Type-2 Classifier (eT2Class), is proposed. The eT2Class features a flexible working principle built upon a fully sequential and local working principle. This learning notion allows eT2Class to automatically...
The question how to manage the contradictive requirements of accuracy and compactness in classification systems remains an important question in machine learning and data mining. This paper proposes a approach that belongs to the domain of fuzzy rule-based classification and uses the method of rule granulation for error reduction and the method of rule consolidation for complexity reduction. The cooperative...
Weather modeling and prediction has been quite a challenge over the years. Predictions based on climatic models whose dynamical behavior is nonlinear, nonstationary, and based on high order difference equations is a tough task and usually requires a demanding and non-intuitive tuning expertise. This paper suggests an ensemble of evolving fuzzy models for multivariate time series prediction. The proposed...
Interval type-2 fuzzy logic controllers (IT2 FLCs) have been treated as a black box in most control applications because the input-output relationship is not fully understood. Reason is that the input-output mapping is very difficult to be expressed in closed-form, therefore, most fuzzy control designers use evolutionary computation methods such as genetic algorithm and big bang-big crunch optimisation...
Three-way decision method is a kind of new developed uncertain decision theory, in which a set of objects can be divided into three regions, called the acceptance, rejection and uncertainty regions, respectively. However, seldom researches that involve the fusion of linguistic information and three-way decisions are found. In this paper, we propose a novel decision method, called linguistic three-way...
Research on physical human-robot interaction has been attracting attention recently, focusing on robot embodiment. The work reported here proposes Active Touch Communication Robot (AcToR), a robot that is modeled on the hearing dog. A hearing dog is a type of dog assist people who are deaf or hard of hearing by alerting their handler to important sounds. AcToR uses the sense of touch to notify a human...
According to the World Health Organization, breast cancer is the most common type of cancer in women. It is also the second leading cause of death among women around the world, becoming the most fatal form of cancer. However, to detect and classify masses is a hard task even for experts. Therefore, due to medical experience, different diagnoses to an image are commonly found. The use of a computer...
Technology progress brings the very rapid growth of patent publications, which increases the difficulty of domain experts to measure the development of various topics, handle linguistic terms used in evaluation and understand massive technological content. To overcome the limitations of keyword-ranking type of text mining result in existing research, and at the same time deal with the vagueness of...
In the recent past, semantic technologies have played an significant role in service retrieval and service querying. Annotating services semantically enables machines to understand the purpose of services and can further assist in intelligent and precise service retrieval, selection and composition. A key issue in semantically annotating services is the manual nature of service annotation. Manual...
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