In this paper, we apply point-tree structured genetic programming (PTGP) to identify a discontinuous parameter of parabolic system. The discontinuous parameter can be decomposed into several subcomponents. Each subcom...
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Multilevel security (MLS) is the application of a computer system to process information with different sensitivities (i.e., at different security levels), permit simultaneous access by users with different security c...
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This is a paper on disease prediction using machine learning through a python graphical user interface application. The motivation behind this application is the pandemic (Covid- Situation) faced by the whole world an...
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Novice Java programmers often cannot make well structured program, so that the program does not have much maintainability. Inappropriate dependency between fields and methods in classes often causes such inappropriate...
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This study involves the development of Maximal Independent Set (MIS) for an arbitrary input graph G. Here we investigate the polynomial-time algorithm using various techniques like greedy, random, divide and conquer a...
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Nonlinear programming problems (NLP) solvers require some level of flexibility. This flexibility must be supported on the method choice, on the parameters specification and on the problem modelling. Few of the tools c...
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ISBN:
(纸本)9789639799455
Nonlinear programming problems (NLP) solvers require some level of flexibility. This flexibility must be supported on the method choice, on the parameters specification and on the problem modelling. Few of the tools currently available can address this level of flexibility. This paper presents an open-source, complete and easy tool, named NLPToolbox, to achieve this purpose. Given its open-source characteritics, it offers the opportunity to study nonlinear programming in an iterative way: by showing how the methods works and allowing all kinds of specifications: methods and parameters. Altough being a work continually in progress, it is already usable. It is currently used in teaching nonlinear programming and solving some kinds of NLP problems, like clustering and Support Vector Machine classification. Its future lies on the optimization of the tool itself, improving the precision of the numeric algorithms and integrating new methods.
This research study investigates the impact of parallel programming techniques on the performance of searching and sorting algorithms. Traditional sequential algorithms have been the foundation of data processing for ...
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In the field of combinatorial optimization, numerous methods have been developed to address complex problems, including assignment, scheduling, and resource allocation. This paper presents a comparative analysis of se...
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In this paper, we study the frequency coexistence problem between NGSO constellation systems of global distributed earth stations, and propose a specific method to mitigate uplink interference of NGSO constellation sy...
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The purpose of this paper is to analyze several algorithm design paradigms applied to single problem - 0/1 Knapsack Problem. The Knapsack Problem is a combinatorial optimization problem where one has to maximize the b...
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