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COMPARATIVE STUDY OF DATA SHARPER AND FUZZY IN DATA STRUCTURES

rolo_619_cardena Español

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COMPARATIVE STUDY OF DATA SHARPER AND FUZZY IN DATA STRUCTURES

  1. INTRODUCTION

    • Today the internet,, DataWarehouse, client-server systems, simulators and other operating systems have become part of everyday life.
    • Here, have a common denominator, require intensive data structures for store, manipulate and organize information with which they work.
    • Data structures are implemented by programming languages ​​and are a model that characterizes and to store and use a specific data organization.
  2. DEVELOPMENT

    • methodology
      • This study responds to documentary research which shows systematically reflects on realities (theoretical or otherwise) for it using different types of documents.
      • This research investigates, interprets, presents data and informaThis research investigates, interprets, presents data and information on a given topic from any area of ​​knowledgetion on a given topic from any area of ​​knowledge.
  3. RESULTS

    • some definitions
      • The data structures are sets of variables, possibly of different types, associated (connected) with one another in various ways and a set of operations
      • Marzal presents some examples of data structures that can be found in many areas, from mathematics
      • Data structure or group is any collection of data organized in such a way that they have associated a set of operations to manipulate them.
      • basic functions
        • constructor function
          • Create the structure, ie, define the characteristics, delimitation, relationships and the space allocated
        • destructor function
          • Return to system resources allocated to the data structure so that they are available to it.
  4. Standard fuzzy logic operations.

    • Some properties of the standard fuzzy logic
      • P and q are two propositions in fuzzy logic standard (U, g). We say that P and q are equivalent if and only if the degrees of truth of both propositions are equal.
      • All sets are crisp bivalent membership functions; however, there are fuzzy sets with membership functions whose ranges are uncountable infinite sets of real numbers.
  5. DISCUSSION OF RESULTS

    • The importance of data is vital in any activity, so they must represent reality and allow them to be viewed quickly and easily.
  6. CONCLUSIONS

    • Data structures are critical to search, store, process, implement, disseminate and manage information.

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Mapa Mental sobre COMPARATIVE STUDY OF DATA SHARPER AND FUZZY IN DATA STRUCTURES, creado por rolo_619_cardena el 30/05/2014.
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