18 resultados para driver information systems, genetic algorithms, prediction theory, transportation

em Bulgarian Digital Mathematics Library at IMI-BAS


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This article describes the approach, which allows to develop information systems without taking into consideration details of physical storage of the relational model and type database management system. Described in terms of graph model, this approach allows to construct several algorithms, for example, for verification application domain. This theory was introduced into operation testing as a part of CASE-system METAS.

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This paper present a technique based on genetic algorithms for generating online adaptive services. Online adaptive systems provide flexible services to a mass of clients/users for maximising some system goals, they dynamically adapt the form and the content of the issued services while the population of clients evolve over time. The idea of online genetic algorithms (online GAs) is to use the online clients response behaviour as a fitness function in order to produce the next generation of services. The principle implemented in online GAs, “the application environment is the fitness”, allow modelling highly evolutionary domains where both services providers and clients change and evolve over time. The flexibility and the adaptive behaviour of this approach seems to be very relevant and promising for applications characterised by highly dynamical features such as in the web domain (online newspapers, e- markets, websites and advertising engines). Nevertheless the proposed technique has a more general aim for application environments characterised by a massive number of anonymous clients/users which require personalised services, such as in the case of many new IT applications.

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In this paper it is explained how to solve a fully connected N-City travelling salesman problem (TSP) using a genetic algorithm. A crossover operator to use in the simulation of a genetic algorithm (GA) with DNA is presented. The aim of the paper is to follow the path of creating a new computational model based on DNA molecules and genetic operations. This paper solves the problem of exponentially size algorithms in DNA computing by using biological methods and techniques. After individual encoding and fitness evaluation, a protocol of the next step in a GA, crossover, is needed. This paper also shows how to make the GA faster via different populations of possible solutions.

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* This work has been partially supported by Spanish Project TIC2003-9319-c03-03 “Neural Networks and Networks of Evolutionary Processors”.

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In this paper we propose a model of encoding data into DNA strands so that this data can be used in the simulation of a genetic algorithm based on molecular operations. DNA computing is an impressive computational model that needs algorithms to work properly and efficiently. The first problem when trying to apply an algorithm in DNA computing must be how to codify the data that the algorithm will use. In a genetic algorithm the first objective must be to codify the genes, which are the main data. A concrete encoding of the genes in a single DNA strand is presented and we discuss what this codification is suitable for. Previous work on DNA coding defined bond-free languages which several properties assuring the stability of any DNA word of such a language. We prove that a bond-free language is necessary but not sufficient to codify a gene giving the correct codification.

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The problem of transit points arrangement is presented in the paper. This issue is connected with accuracy of tariff distance calculation and it is the urgent problem at present. Was showed that standard method of tariff distance discovering is not optimal. The Genetic Algorithms are used in optimization problem resolution. The UML application class diagram and class content are showed. In the end the example of transit points arrangement is represented.

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A description of architecture and approaches to the implementation of a protection system of metadatabased adaptable information systems is suggested. Various protection means are examined. The system described is a multilevel complex based on a multiagent system combining IDS functional abilities with structure and logics protection means.

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This article describes architecture and implementation of subsystem intended for working with queries and reports in adaptive dynamically extended information systems able to dynamically extending. The main features of developed approach are application universality, user orientation and opportunity to integrate with external information systems. Software implementation is based on multilevel metadata approach.

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This article is dedicated to the vital problem of the creation of GIS-systems for the monitoring, prognostication and control of technogenic natural catastrophes. The decrease of risks, the protection of economic objects, averting the human victims, caused by the dynamism of avalanche centers, depends on the effectiveness of the prognostication procedures of avalanche danger used. In the article the structure of a prognostication subsystem information input is developed and the technology for the complex forecast of avalanche-prone situations is proposed.

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The information domain is a recognised sphere for the influence, ownership, and control of information and it's specifications, format, exploitation and explanation (Thompson, 1967). The article presents a description of the financial information domain issues related to the organisation and operation of a stock market. We review the strategic, institutional and standards dimensions of the stock market information domain in relation to the current semantic web knowledge and how and whether this could be used in modern web based stock market information systems to provide the quality of information that their stakeholders want. The analysis is based on the FINE model (Blanas, 2003). The analysis leads to a number of research questions for future research.

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All information systems have to be protected. As the number of information objects and the number of users increase the task of information system’s protection becomes more difficult. One of the most difficult problems is access rights assignment. This paper describes the graph model of access rights inheritance. This model takes into account relations and dependences between different objects and between different users. The model can be implemented in the information systems controlled by the metadata, describing information objects and connections between them, such as the systems based on CASE-technology METAS.

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An automated cognitive approach for the design of Information Systems is presented. It is supposed to be used at the very beginning of the design process, between the stages of requirements determination and analysis, including the stage of analysis. In the context of the approach used either UML or ERD notations may be used for model representation. The approach provides the opportunity of using natural language text documents as a source of knowledge for automated problem domain model generation. It also simplifies the process of modelling by assisting the human user during the whole period of working upon the model (using UML or ERD notations).

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The demands towards the contemporary information systems are constantly increasing. In a dynamic business environment an organization has to be prepared for sudden growth, shrinking or other type of reorganization. Such change would bring the need of adaptation of the information system, servicing the company. The association of access rights to parts of the system with users, groups of users, user roles etc. is of great importance to defining the different activities in the company and the restrictions of the access rights for each employee, according to his status. The mechanisms for access rights management in a system are taken in account during the system design. In most cases they are build in the system. This paper offers an approach in user rights framework development that is applicable in information systems. This work presents a reusable extendable mechanism that can be integrated in information systems.

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In this paper a genetic algorithm (GA) is applied on Maximum Betweennes Problem (MBP). The maximum of the objective function is obtained by finding a permutation which satisfies a maximal number of betweenness constraints. Every permutation considered is genetically coded with an integer representation. Standard operators are used in the GA. Instances in the experimental results are randomly generated. For smaller dimensions, optimal solutions of MBP are obtained by total enumeration. For those instances, the GA reached all optimal solutions except one. The GA also obtained results for larger instances of up to 50 elements and 1000 triples. The running time of execution and finding optimal results is quite short.

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Fermentation processes as objects of modelling and high-quality control are characterized with interdependence and time-varying of process variables that lead to non-linear models with a very complex structure. This is why the conventional optimization methods cannot lead to a satisfied solution. As an alternative, genetic algorithms, like the stochastic global optimization method, can be applied to overcome these limitations. The application of genetic algorithms is a precondition for robustness and reaching of a global minimum that makes them eligible and more workable for parameter identification of fermentation models. Different types of genetic algorithms, namely simple, modified and multi-population ones, have been applied and compared for estimation of nonlinear dynamic model parameters of fed-batch cultivation of S. cerevisiae.