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Fuzzy logic

Niloofar Yousefi Moteghaed, Keivan Maghooli, Masoud Garshasbi
Background: Gene expression data are characteristically high dimensional with a small sample size in contrast to the feature size and variability inherent in biological processes that contribute to difficulties in analysis. Selection of highly discriminative features decreases the computational cost and complexity of the classifier and improves its reliability for prediction of a new class of samples. Methods: The present study used hybrid particle swarm optimization and genetic algorithms for gene selection and a fuzzy support vector machine (SVM) as the classifier...
January 2018: Journal of Medical Signals and Sensors
Payal Dande, Purva Samant
Tuberculosis [TB] has afflicted numerous nations in the world. As per a report by the World Health Organization [WHO], an estimated 1.4 million TB deaths in 2015 and an additional 0.4 million deaths resulting from TB disease among people living with HIV, were observed. Most of the TB deaths can be prevented if it is detected at an early stage. The existing processes of diagnosis like blood tests or sputum tests are not only tedious but also take a long time for analysis and cannot differentiate between different drug resistant stages of TB...
January 2018: Tuberculosis
Salama A Mostafa, Aida Mustapha, Mazin Abed Mohammed, Mohd Sharifuddin Ahmad, Moamin A Mahmoud
Autonomous agents are being widely used in many systems, such as ambient assisted-living systems, to perform tasks on behalf of humans. However, these systems usually operate in complex environments that entail uncertain, highly dynamic, or irregular workload. In such environments, autonomous agents tend to make decisions that lead to undesirable outcomes. In this paper, we propose a fuzzy-logic-based adjustable autonomy (FLAA) model to manage the autonomy of multi-agent systems that are operating in complex environments...
April 2018: International Journal of Medical Informatics
Iris Lucas, Michel Cotsaftis, Cyrille Bertelle
This paper introduces an original mathematical description for describing agents' decision-making process in the case of problems affected by both individual and collective behaviors in systems characterized by nonlinear, path dependent, and self-organizing interactions. An application to artificial financial markets is proposed by designing a multi-agent system based on the proposed formalization. In this application, agents' decision-making process is based on fuzzy logic rules and the price dynamics is purely deterministic according to the basic matching rules of a central order book...
February 2018: Chaos
Melih Iphar, Ali Kivanc Cukurluoz
Decision matrix method is preferred as a measure of risk evaluation considering the risk value obtained by two risk factors such as the likelihood and severity of the hazard. However, it has some deficiencies since crisp risk score is assigned for the likelihood and severity. In this paper, fuzzy logic based safety evaluation method to enhance the risk assessment process is introduced to overcome the uncertainties encountered in classical decision matrix risk assessment method. The proposed method is of more realistic evaluation of the risks which may be available in the mechanized coal panels in Turkey...
March 1, 2018: International Journal of Occupational Safety and Ergonomics: JOSE
Qing Sun, Min Zhang, Arun S Mujumdar
Intellectualization is an important direction of drying development and artificial intelligence (AI) technologies have been widely used to solve problems of nonlinear function approximation, pattern detection, data interpretation, optimization, simulation, diagnosis, control, data sorting, clustering, and noise reduction in different food drying technologies due to the advantages of self-learning ability, adaptive ability, strong fault tolerance and high degree robustness to map the nonlinear structures of arbitrarily complex and dynamic phenomena...
March 1, 2018: Critical Reviews in Food Science and Nutrition
Mohammad Reza Shooshtarian, Mansooreh Dehghani, Ferrante Margherita, Oliveri Conti Gea, Shima Mortezazadeh
This study aggregated Land Change Modeller (LCM) as a useful model in GIS with an extended Groundwater Quality Index (GWQI) developed by fuzzy Multi-Criteria Group Decision-Making models to investigate the effect of land use change and conversion on groundwater quality being supplied for drinking. The model's performance was examined through an applied study in Shiraz, Iran, in a five year period (2011 to 2015). Four land use maps including urban, industrial, garden, and bare were employed in LCM model and the impact of change in area and their conversion to each other on GWQI changes was analysed...
February 14, 2018: Food and Chemical Toxicology
Jorge Yunta, Daniel Garcia-Pozuelo, Vicente Diaz, Oluremi Olatunbosun
Tires are a key sub-system of vehicles that have a big responsibility for comfort, fuel consumption and traffic safety. However, current tires are just passive rubber elements which do not contribute actively to improve the driving experience or vehicle safety. The lack of information from the tire during driving gives cause for developing an intelligent tire. Therefore, the aim of the intelligent tire is to monitor tire working conditions in real-time, providing useful information to other systems and becoming an active system...
February 6, 2018: Sensors
Muntaser A Salman, Suat Ozdemir, Fatih V Celebi
Traffic signal control (TSC) with vehicle-to everything (V2X) communication can be a very efficient solution to traffic congestion problem. Ratio of vehicles equipped with V2X communication capability in the traffic to the total number of vehicles (called penetration rate PR) is still low, thus V2X based TSC systems need to be supported by some other mechanisms. PR is the major factor that affects the quality of TSC process along with the evaluation interval. Quality of the TSC in each direction is a function of overall TSC quality of an intersection...
January 27, 2018: Sensors
Harilton da Silva Araújo, Raimir Holanda Filho, Joel J P C Rodrigues, Ricardo de A L Rabelo, Natanael de C Sousa, José C C L S Filho, José V V Sobral
The Internet of Things (IoT) is based on interconnection of intelligent and addressable devices, allowing their autonomy and proactive behavior with Internet connectivity. Data dissemination in IoT usually depends on the application and requires context-aware routing protocols that must include auto-configuration features (which adapt the behavior of the network at runtime, based on context information). This paper proposes an approach for IoT route selection using fuzzy logic in order to attain the requirements of specific applications...
January 26, 2018: Sensors
Belgacem Agoubi, Radhia Dabbaghi, Adel Kharroubi
Assessing groundwater vulnerability is an important procedure for sustainable water management. Various methods have been developed for effective assessment of groundwater vulnerability and protection. However, each method has its own conditions of use and, in practice; it is difficult to return the same results for the same site. The research conceptualized and developed an improved DRASTIC method using Mamdani Adaptive Neural Fuzzy Inference System (M-ANFIS-DRASTIC). DRASTIC and M-ANFIS-DRASTIC were applied in the Jorf aquifer, southeastern Tunisia, and results were compared...
January 23, 2018: Ground Water
Wilfried Klingert, Jörg Peter, Christian Thiel, Karolin Thiel, Wolfgang Rosenstiel, Kathrin Klingert, Christian Grasshoff, Alfred Königsrainer, Martin Schenk
BACKGROUND: Automated systems are available in various application areas all over the world for the purpose of reducing workload and increasing safety. However, such support systems that would aid caregivers are still lacking in the medical sector. With respect to workload and safety, especially, the intensive care unit appears to be an important and challenging application field. Whereas many closed-loop subsystems for single applications already exist, no comprehensive system covering multiple therapeutic aspects and interactions is available yet...
January 16, 2018: Intensive Care Medicine Experimental
Muyun Qian, Youlong Yu, Naikui Ren, Jie Wang, Xiawen Jin
A sliding sensor based on a fiber Bragg grating (FBG) was proposed to enable mechanical fingers to softly grasp an object. FBG strain sensors are embedded in a polymeric material as a sensing element to obtain sliding information. This study expounded the structural design of the sliding sensor and the mechanism of sliding sensation, which were verified using the finite element simulation. The static and dynamic performances of the sliding sensor were studied experimentally. Finally, the sensing signals were processed using fuzzy logic...
January 8, 2018: Optics Express
Miroslava Cuperlovic-Culf
Machine learning uses experimental data to optimize clustering or classification of samples or features, or to develop, augment or verify models that can be used to predict behavior or properties of systems. It is expected that machine learning will help provide actionable knowledge from a variety of big data including metabolomics data, as well as results of metabolism models. A variety of machine learning methods has been applied in bioinformatics and metabolism analyses including self-organizing maps, support vector machines, the kernel machine, Bayesian networks or fuzzy logic...
January 11, 2018: Metabolites
Jiuping Xu, Rui Qiu, Zhimiao Tao, Heping Xie
Carbon emissions in air passenger transport have become increasing serious with the rapidly development of aviation industry. Combined with a tripartite equilibrium strategy, this paper proposes a multi-level multi-objective model for an air passenger transport carbon tax setting problem (CTSP) among an international organization, an airline and passengers with the fuzzy uncertainty. The proposed model is simplified to an equivalent crisp model by a weighted sum procedure and a Karush-Kuhn-Tucker (KKT) transformation method...
January 8, 2018: Environmental Science and Pollution Research International
Debjyoti Bhattacharjee, Wonjoo Kim, Anupam Chattopadhyay, Rainer Waser, Vikas Rana
Among emerging non-volatile storage technologies, redox-based resistive switching Random Access Memory (ReRAM) is a prominent one. The realization of Boolean logic functionalities using ReRAM adds an extra edge to this technology. Recently, 7-state ReRAM devices were used to realize ternary arithmetic circuits, which opens up the computing space beyond traditional binary values. In this manuscript, we report realization of multi-valued and fuzzy logic operators with a representative application using ReRAM devices...
January 8, 2018: Scientific Reports
Juan Albino Mendez, Ana Leon, Ayoze Marrero, Jose M Gonzalez-Cava, Jose Antonio Reboso, Jose Ignacio Estevez, José F Gomez-Gonzalez
OBJECTIVE: The main objective of this research is the design and implementation of a new fuzzy logic tool for automatic drug delivery in patients undergoing general anesthesia. The aim is to adjust the drug dose to the real patient needs using heuristic knowledge provided by clinicians. A two-level computer decision system is proposed. The idea is to release the clinician from routine tasks so that he can focus on other variables of the patient. METHODS: The controller uses the Bispectral Index (BIS) to assess the hypnotic state of the patient...
January 5, 2018: Artificial Intelligence in Medicine
Nicola Amoroso, Domenico Diacono, Annarita Fanizzi, Marianna La Rocca, Alfonso Monaco, Angela Lombardi, Cataldo Guaragnella, Roberto Bellotti, Sabina Tangaro
BACKGROUND: Early diagnosis of Alzheimer's disease (AD) and its onset in subjects affected by mild cognitive impairment (MCI) based on structural MRI features is one of the most important open issues in neuroimaging. Accordingly, a scientific challenge has been promoted, on the international Kaggle platform, to assess the performance of different classification methods for prediction of MCI and its conversion to AD. NEW METHOD: This work presents a classification strategy based on Random Forest feature selection and Deep Neural Network classification using a mixed cohort including the four classes of classification problem, that is HC, AD, MCI, cMCI, to train the model...
December 26, 2017: Journal of Neuroscience Methods
Fenglei Fan, Wenxiang Cong, Ge Wang
The artificial neural network is a popular framework in machine learning. To empower individual neurons, we recently suggested that the current type of neurons could be upgraded to 2nd order counterparts, in which the linear operation between inputs to a neuron and the associated weights is replaced with a nonlinear quadratic operation. A single 2nd -order neurons already has a strong nonlinear modeling ability, such as implementing basic fuzzy logic operations. In this paper, we develop a general backpropagation (BP) algorithm to train the network consisting of 2nd -order neurons...
December 26, 2017: International Journal for Numerical Methods in Biomedical Engineering
Kun You, Lijiang Wei, Kai Jiang
Diesel engines have dominated in the heavy-duty vehicular and marine power source. However, the induced air pollution is a big problem. As people's awareness of environmental protection increasing, the emission regulations of diesel-engine are becoming more stringent. In order to achieve the emission regulations, the after-treatment system is a necessary choice. Specifically, the selective catalytic reduction (SCR) system has been widely applied to reduce the NOX emissions of diesel engine. Different from single-cell SCR systems, the two-cell systems have various benefits from the modeling and control perspective...
December 22, 2017: ISA Transactions
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