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检索条件"任意字段=2024 IEEE International Conference on Cognitive Computing and Complex Data"

共 1578 条记录，以下是1481-1490 订阅

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Enabling Transparent Access to Heterogeneous Architectures for IS-ENES Climate4Impact using the DARE Platform

Enabling Transparent Access to Heterogeneous Architectures f...

引用

ieee international conference on e-Science and Grid computing

作者： Christian Pagé Wim Som de Cerff Maarten Plieger Alessandro Spinuso Xavier Pivan Universite de Toulouse Toulouse France Koninklijk Nederlands Meteorologisch Instituut De Bilt Netherlands KNMI Koninklijk Nederlands Meteorologisch Instituut De Bilt Netherlands France

ISBN: (数字)9781728124513

ISBN: (纸本)9781728124520

Access to Climate data is crucial to sustain research and climate change impact assessments. It has a strong societal impact as those changes will have to be mitigated as much as possible. The whole climate data archive is expected to reach a volume of 30 PB in 2019 and up to 2000 PB in 2024 (estimated), evolving from 30 TB in 2007 and 2 PB in 2014. data processing and analysis must now happen remotely for the users: they now have to rely on heterogeneous infrastructures and services between the data and their location. Developers of Research Infrastructures have to provide services to those users, hence having to define standards and generic services to fulfill those requirements. It will be shown how the DARE eScience Platform (http://***) will help developers to develop more rapidly needed services for a large range of scientific researchers. The platform is designed for efficient and traceable development of complex experiments and domain-specific services on the Cloud. It will be also shown how the integration of the DARE platform together with the climate IS-ENES (https://***) Research Infrastructure front-end climate4impact (C4I: https://***/) will help developers leverage heterogeneous architectures transparently for the benefit of researchers.

关键词： Meteorology Prototypes Europe data processing Climate change Standards Software

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Strategy of complex Systems Development Based on the Synthesis of Foresight and cognitive Modelling Methodologies

Strategy of Complex Systems Development Based on the Synthes...

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ieee international conference on System Analysis & Intelligent computing (SAIC)

作者： Galina Gorelova Nataliya D. Pankratova “ITA SFEDU” Engineering and Technology Academy of the Southern Federal University Taganrog Russia Institute for Applied System Analysis Igor Sikorsky Kyiv Polytechnic Institute Kyiv Ukraine

ISBN: (纸本)9781538671979

The need for qualitatively new, systematically agreed principles, approaches, methods for identifying opportunities and assessing perspectives and trends of the complex systems development is discussed. The strategy of complex systems development based on the synthesis of foresight and cognitive modelling methodologies is proposed. The possibilities of such integration are illustrated by an example of cognitive modelling of the complex systems interaction.

关键词： Biological system modeling complex systems Analytical models data models Economics Mathematical model complexity theory

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An Innovative Framework for Supporting cognitive-Based Big data Analytics for Frequent Pattern Mining

An Innovative Framework for Supporting Cognitive-Based Big D...

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ieee international conference on cognitive computing (ICCC)

作者： Deyu Deng Carson K. Leung Bryan H. Wodi Jialiang Yu Hao Zhang Alfredo Cuzzocrea Department of Computer Science University of Manitoba Winnipeg MB Canada DIA Department University of Triste Trieste TS Italy

The increasing size of modern applications and services produces huge volumes of a wide variety of valuable data of different veracity at a high velocity, which in turn leads to a new challenge to big data analytics. Researchers often use these 5V's (volume, variety, value, veracity, and velocity) to describe the features of big data. The interest of discovering patterns from a large collection of data has risen in business for transforming goods into services. Rich sources of big data include complex sensing-centered service systems. Embedded in these big data are useful information and knowledge. In this paper, we present an innovative framework for supporting cognitive-based big data analytics for frequent pattern mining. Evaluation results show the applicability of our framework to support cognitive computing for big data analytics of frequent patterns.

关键词： Big data data mining Itemsets cognitive systems Sensors Uncertainty

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Improved Behavioral Analysis of Fuzzy cognitive Map Models 17th

Improved Behavioral Analysis of Fuzzy Cognitive Map Models

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17th international conference on Artificial Intelligence and Soft computing (ICAISC)

作者： Hatwagner, Miklos F. Vastag, Gyula Niskanen, Vesa A. Koczy, Laszlo T. Szechenyi Istvan Univ Dept Informat Technol Gyor Hungary Szechenyi Istvan Univ Dept Leadership & Org Commun Gyor Hungary Univ Helsinki Dept Econ & Management Helsinki Finland Szechenyi Istvan Univ Dept Informat Technol Gyor Hungary Budapest Univ Technol & Econ Dept Telecommun & Media Informat Budapest Hungary

ISBN: (纸本)9783319912622;9783319912615

Fuzzy cognitiveMaps (FCMs) are widely applied for describing the major components of complex systems and their interconnections. The popularity of FCMs ismostly based on their simple system representation, easy model creation and usage, and its decision support capabilities. The preferable way of model construction is based on historical, measured data of the investigated system and a suitable learning technique. Such data are not always available, however. In these cases experts have to define the strength and direction of causal connections among the components of the system, and their decisions are unavoidably affected by more or less subjective elements. Unfortunately, even a small change in the estimated strength may lead to significantly different simulation outcome, which could pose significant decision risks. Therefore, the preliminary exploration of model `sensitivity' to subtle weight modifications is very important to decision makers. This way their attention can be attracted to possible problems. This paper deals with the advanced version of a behavioral analysis. Based on the experiences of the authors, their method is further improved to generate more life-like, slightly modified model versions based on the original one suggested by experts. The details of the method is described, its application and the results are presented by an example of a banking application. The combination of Pareto-fronts and Bacterial Evolutionary Algorithm is a novelty of the approach.

关键词： Banking Fuzzy cognitive Maps Model uncertainty Multi-objective optimization Bacterial Evolutionary Algorithm

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Combined Control of Impulse Processes in complex Systems' cognitive Maps with Multirate Sampling 9

Combined Control of Impulse Processes in Complex Systems' Co...

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9th ieee international conference on Intelligent data Acquisition and Advanced computing Systems - Technology and Applications (IDAACS)

作者： Romanenko, Victor Milyavsky, Yuriy NTUU KPI Inst Appl Syst Anal 37 Peremohy Ave Kiev Ukraine

ISBN: (纸本)9781538606971

This report considers new principle of impulse processes control in complex systems' cognitive maps (CM) based on varying vertices coordinates and weighting coefficients for control design in closed-loop system. In addition, CM vertices coordinates and edges weighting coefficients evolve in discrete time with multirate sampling.

关键词： cognitive map impulse processes models multirate sampling optimality criterion slow and fast controls

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Fuzzy cognitive Maps designing through large dataset and experts' knowledge balancing

Fuzzy Cognitive Maps designing through large dataset and exp...

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ieee international conference on Fuzzy Systems

作者： Giovanni Mazzuto Filippo E. Ciarapica Chrysostomos Stylios Voula C. Georgopoulos Dipartimento Ingegneria Industriale e Scienze Matematiche Università Politecnica delle Marche Ancona Italy Laboratory of Knowledge and Intelligent Computing (KIC) Educational Institute of Epirus Arta Greece INTERACT Lab School of Health & Welfare Professions Technological Educational Institute of Western Greece Patras Greece

This paper presents an extension of a hybrid method for modelling Fuzzy cognitive Maps (FCMs), which combines human expert knowledge with existing recorded information and historical data. The proposed approach at first step extracts information from any type of dataset, extracts useful information and transforms it into knowledge in a form suitable to stracture a FCM. The proposed approach is still dependent on experts' knowledge but it support them by providing the information and supportive data inferred from the dataset. Moreover, the approach highlights, through a supportive numerical example, that experts' knowledge and information from the dataset cannot be considered separately, since their combined use compensates possible errors in knowledge. In particular, it can be used to model a complex Decision Support Systems, and it also allows to identify the accuracy of the considered models.

关键词： Computational modeling Mathematical model Fuzzy cognitive maps data models Numerical models complex systems Cognition

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The Tornadogenesis Optimization Algorithm 16

The Tornadogenesis Optimization Algorithm

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ieee 16th international conference on cognitive Informatics and cognitive computing (ICCI*CC)

作者： Saidala, Ravi Kumar Devarakonda, Nagaraju Acharya Nagarjuna Univ Dept Comp Sci & Engn Nagarjuna Nagar 522510 Guntur India LBR Coll Engn Dept Informat Technol Mylavaram 521230 AP India

ISBN: (纸本)9781538607718

The Tornadogenesis Optimization Algorithm (TOA), a new air mass population based meta-heuristic optimization (MHO) algorithm is devised in this paper. Implementation of TOA has taken its root from the formation of tornadoes, particularly at Oklahoma State of United States. The inspiration and the mathematical formulation along with a flowchart, the proposed algorithm was explained in this paper. The comparable and evidential investigations have been conducted on 23 standard mathematical benchmark functions. To test the numerical efficiency and clustering quality of TOA, clustering experiments also have been conducted on 10 real data clustering problems. The obtained results are compared with the other state-of-the-art algorithms, recently developed optimization technique WOA and its variants IWOA and NPMOA. Simulation results with the statistical significance confirm that the TOA outperform in complex function optimization problems.

关键词： Nature Inspired Algorithms Meta-heuristic optimization techniques Tornadoes Tornadogenesis data Cluster Problems

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Constructing the Knowledge Base for cognitive IT Service Management 14

Constructing the Knowledge Base for Cognitive IT Service Man...

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ieee international conference on Services computing (SCC)

作者： Wang, Qing Zhou, Wubai Zeng, Chunqiu Li, Tao Shwartz, Larisa Grabarnik, Genady Ya. Florida Int Univ Sch Comp & Informat Sci Miami FL 33199 USA IBM TJ Watson Res Ctr Yorktown Hts NY USA St Johns Univ Dept Math & Comp Sci Queens NY USA

ISBN: (纸本)9781538620052

The increasing complexity of IT environments dictates the usage of intelligent automation driven by cognitive technologies, aiming at providing higher quality and more complex services. Inspired by cognitive computing, an integrated framework is proposed for a problem resolution. In order to improve the efficiency of the problem resolution process, it is crucial to formalize problem records and discover relationships between elements of the records, records overall and other technical information. In the proposed framework, the domain knowledge is modeled using ontology. The key contribution of the framework is a novel domain specific approach for extracting useful phrases, that enables an automation improvement through resolution recommendation utilizing the ontology modeling technique. The effectiveness and efficiency of our framework are evaluated by an extensive empirical study of a large scale real ticket data.

关键词： knowledge base cognitive computing ontology IT service management

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Early diagnosis of mild cognitive impairment: A case study in approaches to inductive-logic programming 16

Early diagnosis of mild cognitive impairment: A case study i...

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16th ieee international conference on cognitive Informatics and cognitive computing, ICCI*CC 2017

作者： Martono, Niken Prasasti Yamaguchi, Takehiko Ohwada, Hayato Department of Industrial Administration Tokyo University of Science Japan Department of Applied Electronics Tokyo University of Science Japan School of Business and Management Bandung Institute of Technology Indonesia

ISBN: (纸本)9781538607701

Recent rapid advances in data collection routines in clinical science have led to a trend of storing patient data in a heterogeneous database. The lack of existing computing tools to enable operability to use machine learning on these heterogeneous data sources is a barrier to the healthcare sciences. Healthcare data is usually complex and highly context-dependent, and it requires modern computational tools to handle the complexity of such data. This study sought to utilize the data collected from virtual reality (VR)-based software and a leap-motion device used for learning in mild cognitive impairment (MCI) cases to enable early detection of MCI by analyzing the classification rules for errors (action slips) based on finger-action transitions when performing instrumental activities of daily living (IADL). Finger motion was recorded as a time-series database. An induction technique known as Inductive-Logic Programming (ILP), which uses logical and clausal language to represent the training data, was then used to discover a concise classification rule using logical programming. We were able to generate rules on how action transitions of the finger in the experiments were related to the pattern of micro-errors that indicate the difference of error regarding the length of the no-motion state of the finger. © 2017 ieee.

关键词： Machine learning

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A Framework for Designing cognitive Assistants to Support Agricultural Production Systems

A Framework for Designing Cognitive Assistants to Support Ag...

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ieee international Workshop on Enabling Technologies: Infrastructure for Collaborative Enterprises (WET ICE)

作者： Julio Cesar dos Reis Rodrigo Bonacin Andreiwid Correa Francisco Edeneziano D. Pereira Ivo Pierozzi Sergio A. Torquato Jarbas L. Cardoso Katia R. E. Jesus Olga Fernanda N. Araujo Institute of Computing University of Campinas Campinas SP Brazil UNIFACCAMP and CTI Renato Archer Campinas SP Brazil Informatics Department Federal Institute of São Paulo Campinas SP Brazil Technological Innovation Division CTI Renato Archer Campinas SP Brazil Embrapa Agricultural Informatics Campinas SP Brazil Institute of Agricultural Economics São Paulo SP Brazil Information Systems Group CTI Renato Archer Campinas SP Brazil Embrapa Environment Jaguariuna SP Brazil CTI Renato Archer Campinas SP Brazil

cognitive assistants bring new opportunities to strengthen the coupling of data, information and knowledge aiming to collective intelligence. This technology can boost decision making on complex issues, such as Sustainability and Bioeconomy on agricultural production systems. However, the design of collaborative systems that explore cognitive assistants is an open research question. This challenge deals with meaning interpretation and involves semantic formal models to represent, in a systemic view, knowledge related to the structures, competencies, responsibilities, policies, and culture of a production system. In this paper, we propose a design framework for the development of solutions based on cognitive assistant technology. This framework contributes to a novel view of the design process by integrating a method for modeling complex system with formal semantic models, collective intelligent systems, and cognitive assistant development technologies. A scenario in a sugarcane production system illustrates the proposed framework.

关键词： Production systems Semantics Computational modeling Biological system modeling data models Decision making

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