Search results for "Fuzzy Logic."

showing 10 items of 449 documents

Towards human cell simulation

2019

The faithful reproduction and accurate prediction of the phe-notypes and emergent behaviors of complex cellular systems are among the most challenging goals in Systems Biology. Although mathematical models that describe the interactions among all biochemical processes in a cell are theoretically feasible, their simulation is generally hard because of a variety of reasons. For instance, many quantitative data (e.g., kinetic rates) are usually not available, a problem that hinders the execution of simulation algorithms as long as some parameter estimation methods are used. Though, even with a candidate parameterization, the simulation of mechanistic models could be challenging due to the extr…

Constraint-based modelingAgent-based simulation; Big data; Biochemical simulation; Computational intelligence; Constraint-based modeling; Fuzzy logic; High-performance computing; Model reduction; Multi-scale modeling; Parameter estimation; Reaction-based modeling; Systems biology; Theoretical Computer Science; Computer Science (all)Computer scienceBiochemical simulationDistributed computingSystems biologyBig dataComputational intelligenceContext (language use)ING-INF/05 - SISTEMI DI ELABORAZIONE DELLE INFORMAZIONITheoretical Computer ScienceReduction (complexity)Big dataParameter estimationHigh-performance computingComputational intelligenceAgent-based simulationMathematical modelbusiness.industryModel reductionComputer Science (all)Multi-scale modelingINF/01 - INFORMATICASupercomputerVariety (cybernetics)Fuzzy logicReaction-based modelingbusinessSystems biology
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Partial spatial equilibria with fuzzy constraints

1981

It is implicitly accepted by spatial economic analysis that the economic behaviour of agents located in given spaces (market areas, regions, etc.) is precise, that is to say, their behaviour is such that a possible action (consumption, production) is, or is not, preferable to another. In otherwords, economic agents are assumed to make accurate economic calculations and optimise the objective functions under strict constraints of resource limitation. These objective functions have clearly defined arguments and well-controlled parameters.

Consumption (economics)Economic behaviorMathematical optimizationEnvironmental Science (miscellaneous)Development[SHS.ECO]Humanities and Social Sciences/Economics and FinanceFuzzy logicConsumer behaviorResource (project management)Action (philosophy)EconomicsProduction (economics)Economic analysisFuzzy number[ SHS.ECO ] Humanities and Social Sciences/Economies and finances[SHS.ECO] Humanities and Social Sciences/Economics and FinanceMathematical economicsConsumer behaviour
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Support Vector Machines for Crop Classification Using Hyperspectral Data

2003

In this communication, we propose the use of Support Vector Machines (SVM) for crop classification using hyperspectral images. SVM are benchmarked to well–known neural networks such as multilayer perceptrons (MLP), Radial Basis Functions (RBF) and Co-Active Neural Fuzzy Inference Systems (CANFIS). Models are analyzed in terms of efficiency and robustness, which is tested according to their suitability to real–time working conditions whenever a preprocessing stage is not possible. This can be simulated by considering models with and without a preprocessing stage. Four scenarios (128, 6, 3 and 2 bands) are thus evaluated. Several conclusions are drawn: (1) SVM yield better outcomes than neura…

Contextual image classificationArtificial neural networkbusiness.industryComputer scienceHyperspectral imagingFuzzy control systemPerceptronMachine learningcomputer.software_genreFuzzy logicSupport vector machineComputingMethodologies_PATTERNRECOGNITIONRobustness (computer science)Radial basis functionArtificial intelligencebusinesscomputer
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Fuzzy logic approach to predict vehicle crash severity from acceleration data

2015

Vehicle crash is a complex behavior to be investigated as a challenging topic in terms of dynamical modeling. On this aim, fuzzy logic can be utilized to analyze the crash dynamics rapidly and simply. In this paper, the experimental data of the frontal crash is recorded using an accelerometer located at the centre of the gravity of the vehicle. The acceleration signal was the raw data from which the collision intensity expressed by the kinetic energy and the jerk were derived. The fuzzy logic model was then developed from the two inputs namely kinetic energy and jerk. The output variable is the crash severity expressed as the dynamic crash. The result shows that the jerk contributes much to…

Control and OptimizationComputer scienceSIGNAL (programming language)CrashAccelerometerCollisionFuzzy logicFuzzy logic; Jerk and Kinetic energy; vehicle crash severity; Artificial Intelligence; Control and Optimization; Discrete Mathematics and CombinatoricsFuzzy logicJerk and Kinetic energyAccelerationVariable (computer science)JerkArtificial IntelligenceDiscrete Mathematics and CombinatoricsSimulationvehicle crash severity2015 International Conference on Fuzzy Theory and Its Applications (iFUZZY)
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On the Evaluation of Images Complexity: A Fuzzy Approach

2006

The inherently multidimensional problem of evaluating the complexity of an image is of a certain relevance in both computer science and cognitive psychology. Computer scientists usually analyze spatial dimensions, to deal with automatic vision problems, such as feature-extraction. Psychologists seem more interested in the temporal dimension of complexity, to explore attentional models. Is it possible, by merging both approaches, to define an more general index of visual complexity? We have defined a fuzzy mathematical model of visual complexity, using a specific entropy function; results obtained by applying this model to pictorial images have a strong correlation with ones from an experime…

CorrelationBinary entropy functionbusiness.industryComputer scienceFuzzy setEntropy (information theory)Artificial intelligencebusinessMachine learningcomputer.software_genreFuzzy logiccomputerVisual complexity
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A BDI agent system for credit risk assessment based on fuzzy logic

2007

Credit risk has always been an important issue for banks and other financial intermediaries. A reliable and consistent computing system is necessary to simplify the decision making process in uncertain domains such as the assessment of credit risk. In recent years fuzzy logic techniques have been in their wide-ranging use in modeling of uncertainties, vagueness, impreciseness and the human thought process. Therefore in this paper we present a fuzzy logic based intelligent system for the assessment of credit risk. It aims at efficiently and intelligently managing the process, handling its complexity, and monitoring large amounts of dynamic information in a distributed way, by using a society…

Credit risk assessment Fuzzy logic Intelligent agents Practical reasoning
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Critical path analysis in the network with fuzzy activity times

2001

A natural generalization of the criticality notion in a network with fuzzy activity times is given. It consists in direct application of the extension principle of Zadeh to the notion of criticality of a path (an activity, an event) treated as a function of the activities duration times in the network. There are shown some relations between the notion of fuzzy criticality, introduced in the paper, and the notion of interval criticality (criticality in the network with interval activity times) proposed by the authors in another paper. Two methods of calculation of the path degree of criticality (according to the proposed concept of fuzzy criticality) are presented.

CriticalityArtificial IntelligenceLogicGeneralizationEvent (relativity)Path (graph theory)Function (mathematics)Interval (mathematics)TopologyAlgorithmCritical path methodFuzzy logicMathematicsFuzzy Sets and Systems
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Criticality in the Network with Imprecise Activity Times

2002

A review of the results obtained in the area of fuzzy network analysis is presented. The main approaches to the concept of criticality in a network with fuzzy activity times are described and classified. Against the background of this review some new results, obtained by the authors recently, are presented. The paper is an extended version of the work presented in IPMU'2000 (see [8]).

CriticalityWork (electrical)business.industryFuzzy numberArtificial intelligencebusinessCritical path methodFuzzy logicMathematicsNetwork analysis
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Fuzzy technique for microcalcifications clustering in digital mammograms

2012

Abstract Background Mammography has established itself as the most efficient technique for the identification of the pathological breast lesions. Among the various types of lesions, microcalcifications are the most difficult to identify since they are quite small (0.1-1.0 mm) and often poorly contrasted against an images background. Within this context, the Computer Aided Detection (CAD) systems could turn out to be very useful in breast cancer control. Methods In this paper we present a potentially powerful microcalcifications cluster enhancement method applicable to digital mammograms. The segmentation phase employs a form filter, obtained from LoG filter, to overcome the dependence from …

Databases FactualMicrocalcificationsBreast NeoplasmsContext (language use)CADcomputer.software_genreSensitivity and SpecificityFuzzy logicClusteringBreast cancerSegmentationBreast cancerC-meansImage Processing Computer-AssistedmedicineCluster AnalysisHumansMammographyRadiology Nuclear Medicine and imagingSegmentationCluster analysisSpatial filtersmedicine.diagnostic_testMultimediabusiness.industryCalcinosisPattern recognitionmedicine.diseaseSettore FIS/07 - Fisica Applicata(Beni Culturali Ambientali Biol.e Medicin)Computer aided detectionFuzzy logicRadiology Nuclear Medicine and imagingFemaleArtificial intelligencebusinesscomputerAlgorithmsMammographyResearch ArticleBreast cancer Microcalcifications Spatial filters Clustering Fuzzy logic C-means Mammography SegmentationBMC Medical Imaging
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A Fuzzy Inference Expert System to Support the Decision of Deploying a Military Naval Unit to a Mission

2009

Naval military units are complex systems required to operate in fixed time frames in offshore tasks where maintenance operations are drastically limited. A failure during a mission is a critical event that can drastically influence the mission success. The decision of switching a unit to a mission hence requires complex judgments involving information about the health status of machineries and the environmental conditions. The present procedure aims to support the decision about switching a unit to a mission considering the vagueness and uncertainty of information by means of fuzzy theory and emulates the decision process of a human expert by means of a rule-based inference engine. A numeri…

Decision support systemOperations researchComputer scienceIntelligent decision support systemComplex systemComputerApplications_COMPUTERSINOTHERSYSTEMSVaguenesscomputer.software_genreFuzzy logicExpert systemUnit (housing)fuzzy inference decision support system mission reliabilityiSettore ING-IND/17 - Impianti Industriali MeccaniciInference enginecomputer
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