Wyniki wyszukiwania - BazTech

1

Fuzzy-based firefly and ACO algorithm for densely deployed WSN

Sharma Tripti, Mohapatra Amar Kumar, Tomar Geetam

Computer Assisted Methods in Engineering and Science

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2023

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Vol. 30, no. 2

223--246

EN

Most of the wireless sensor networks (WSNs) used in healthcare and security sectors are affected by the battery constraints, which cause a low network lifetime problem and prevents these networks from achieving their maximum performance. It is anticipated that by combining fuzzy logic (FL) approximation reasoning approach with WSN, the complex behavior of WSN will be easier to handle. In healthcare, WSNs are used to track activities of daily living (ADL) and collect data for longitudinal studies. It is easy to understand how such WSNs could be used to violate people’s privacy. The main aim of this research is to address the issues associated with battery constraints for WSN and resolve these issues. Such an algorithm could be successfully applied to environmental monitoring for healthcare systems where a dense sensor network is required and the stability period should be high.

2

A relaying scheme for detection and classification of shunt faults in six-phase transmission system based on DFT-FIS approach

Ashok V., Yadav A.

Journal of Power Technologies

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2018

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Vol. 98, nr 2

202--211

EN

Hitherto many schemes based on the fuzzy system have been protected by a three-phase transmission system, but not by a six-phase transmission system. This paper sets out a novel protection scheme based on DFT-FIS approach for detection/classification of shunt faults in a six-phase transmission system. In this scheme, two separate DFT-FIS modules have been designed to detect the presence of fault in any of the six-phase(s) and to identify the presence of ground in the fault loop, thus classifying all 120 types of fault in a six-phase transmission line. The six-phase voltage and current signals are collected at one end of the transmission line only, thus circumvent dependence on a communication link for remote end data. A widerange of fault simulation studies were carried out in MATLAB/Simulink environment for all possible shunt fault combinations by varying fault locations, fault inception angle, fault resistance, short circuit capacity (SCC) of the source and at various fault conditions such as: close-in faults, remote-end faults, high resistance faults, including CT saturation. Furthermore, the relay operation time in fault detection/classification is less than one-cycle (<16.67ms) and since the scheme does not experience any malfunction it is deemed reliable and adaptable.

3

Artificial neural networks and fuzzy inference systems for line simplification with extended WEA metric

Olszewski R., Gnat M., Fiedukowicz A.

Geodesy and Cartography

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2018

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Vol. 67, no. 2

255--269

EN

The issue of line simplification is one of the fundamental problems of generalisation of geographical information, and the proper parameterisation of simplification algorithms is essential for the correctness and cartographic quality of the results. The authors of this study have attempted to apply computational intelligence methods in order to create a cartographic knowledge base that would allow for non-standard parameterisation of WEA (Weighted Effective Area) simplification algorithm. The aim of the conducted research was to obtain two independent methods of non-linear weighting of multi-dimensional regression function that determines the “importance” of specific points on the line and their comparison to each other. The first proposed approach consisted in the preparation of a set of cartographically correct examples constituting a basis for teaching a neural network, while the other one consisted in defining inference rules using fuzzy logic. The obtained results demonstrate that both methods have great potential, although the proposed solutions require detailed parameterisation taking into account the specificity of geometric variety of the source data.

4

Koncepcja systemu wspomagającego Żeglugę Śródlądową – studium przypadku dla dolnego odcinka Wisły

Jerzyło P., Wawrzyńska A.

Zeszyty Naukowe Akademii Morskiej w Gdyni

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2017

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nr 102

21--32

PL

Artykuł przedstawia wyniki prowadzonych badań, dotyczących aktualnych warunków żeglugowo-nawigacyjnych, intensywności ruchu statków, wypadków i incydentów dla dolnego odcinka Wisły jako uzasadnienie do wprowadzenia systemu wspomagającego żeglugę śródlądową na Dolnej Wiśle. Przedstawiono i scharakteryzowano dwa warianty wdrożenia systemu informacji rzecznej.

EN

The article presents the results of conducted research on actual navigation conditions, traffic intensity, accidents and incidents for the part of the Vistula River as a justification for introducing the inland waterway navigation system in the Lower Vistula . Two variants of the implementation of the river information system were presented and characterized.

5

Performance comparison of hybrid electromagnetism-like mechanism algorithms with descent method

Miyajima H., Shigei N., Miyajima H.

Journal of Artificial Intelligence and Soft Computing Research

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2015

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Vol. 5, No. 4

271--282

EN

Electromagnetism-like Mechanism (EM) method is known as one of metaheuristics. The basic idea is one that a set of parameters is regarded as charged particles and the strength of particles is corresponding to the value of the objective function for the optimization problem. Starting from any set of initial assignment of parameters, the parameters converge to a value including the optimal or semi-optimal parameter based on EM method. One of its drawbacks is that it takes too much time to the convergence of the parameters like other meta-heuristics. In this paper, we introduce hybrid methods combining EM and the descent method such as BP, k-means and FIS and show the performance comparison among some hybrid methods. As a result, it is shown that the hybrid EM method is superior in learning speed and accuracy to the conventional methods.

6

Systemy wnioskowania rozmytego (FIS) jako narzędzie nieliniowej generalizacji numerycznego modelu terenu

Olszewski R.

Polski Przegląd Kartograficzny

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2006

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T. 38, nr 4

316-325

PL

W artykule omówiono zagadnienie zastosowania systemów generalizacji danych przestrzennych opartych na logice rozmytej do modelowania rzeźby terenu na różnym poziomie uogólnienia.

EN

Classic filtering methods of raster data (e.g. digital terrain model), such as median or gaussian filtering level the result surface, and consequently flatten the end results. A significant modification of results' range, understood as narrowing of the scope of relative altitudes in the test area, is not the only side effect of the process of DTM generalization. Gaussian filtering, and especially non-linear median filtering leads to non-linear morphometric modifications of generalized terrain relief. Structural forms common for high mountain relief, such as ridge lines and deeply cut river valleys are flattened more than other forms. In the article the author attempts to elaborate a non-linear method of raster data filtering by defining the objective generalization rules of local character. These rules determine the global process of cartographic generalization of raster-type data. In order to build a database which would enable the realization of the process of spatial data generalization, fuzzy inference systems (FIS) are applied. Application of fuzzy logic makes it possible to define generalization rules for non-linear filtering of a digital terrain model recorded in the form of an altitude matrix. In the discussed context FIS can be interpreted as a non-linear digital terrain model transformation. Compared to other non-linear modeling techniques FIS has many advantages: - it keeps the parameters of source data distribution (slant, range, etc.,) - enables open and easy to interpret definition of rules in the data base (in relation to scale, purpose, cartographic school, etc.), - it bases on linguistic variables, which facilitates the understanding of the generalization process, - it facilitates scalability of the results through parametrization of the membership function. Application of fuzzy logic and generalization systems using fuzzy inference makes it possible to automatize the generalization process while preserving subjectivity of cartographic generalization. The final effects depend on the FIS database created by the researcher.