Neural network classifier for automatic course-keeping based on fuzzy logic

Sedova, Nelly; Sedov, Viktor A.; Баженов, Руслан Иванович; Богатенков, С. А.

doi:10.3233/jifs-201495

Cited by 5 publications

(3 citation statements)

References 9 publications

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“…:(0123456789) www.nature.com/scientificreports/ Note that control methods based on fuzzy logic are currently being actively developed 22,23 . There are known works, in which such methods are proposed to be used for correcting the course of ships 24 .…”

Section: Let Us Form the Following Polynomialmentioning

confidence: 99%

Improving the efficiency of using multivalued logic tools

Сулейменов

Vitulyova

Kabdushev

et al. 2023

Sci Rep

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Multivalued logics are becoming one of the most important tools of information technology. They are in great demand for creation of artificial intelligence systems that are close to human intelligence, since the functioning of the latter cannot be reduced to the operations of binary logic. At the same time, the problem of improving the efficiency of using the results of research in multivalued logics, as well as the problem of interpreting variables of multivalued logic, is acute. These problems create certain interdisciplinary barriers and make it difficult to implement the results of research in the field of multivalued logics in other fields of knowledge. It is shown that the problem of interpreting multivalued logic variables can be removed by establishing correspondence with fuzzy logic variables. Improving the efficiency of using of operations of multivalued logics and their variables can be provided by using their close connection to Galois fields. This connection, among other things, makes it possible to reduce any operations of multivalued logics, the number of variables in which is equal to a prime number, to algebraic functions whose arguments take values in Galois fields. This allows, among other things, to eliminate the very cumbersome constructions used in works on multivalued logic and make its apparatus convenient for use in related scientific disciplines in information technology. Direct verification of the adequacy of algorithms based on the use of Galois fields can be carried out by means of radio-electronic circuits, examples of which are presented in the present paper.

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Section: Let Us Form the Following Polynomialmentioning

confidence: 99%

Improving the efficiency of using multivalued logic tools

Сулейменов

Vitulyova

Kabdushev

et al. 2023

Sci Rep

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“…In nature, ants can find the optimal value through cooperation. When they look for food, they will leave pheromone, and the ant colony will find the pheromone intensity in the direction to find the path, and the ant colony will strengthen the original pheromone in the process of moving, that is, increase the concentration [6]. So far, this phenomenon is called an iteration of the ant colony algorithm.…”

Section: Ant Colony Optimizationmentioning

confidence: 99%

Neural Network Classifier Improvements Based on Ant Colony Algorithm

2022

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Compared with other classifiers, neural network (NN) classifiers are faster and have more advantages. However, the NN classifier is unique, because the number of features often changes when selecting features and the classifier is classified by the number of hidden layer nodes, and a NN with a fixed number of hidden layer nodes is used to evaluate different types of feature subsets obviously inappropriate. Therefore, the NN classifier is optimized, and the ant colony optimization (ACO) algorithm is introduced to obtain a diverse solution, which will be faster than the NN classifier to avoid it falling into the problem of local solutions. As a classic feedforward NN, BP neural network (BPNN) is currently the most widely used NN for classification problems. Therefore, this paper constructs a BPNN classifier. By comparing the traditional BPNN classifier and the improved ACO-BPNN classifier on malicious web page detection and classification effects of different sizes of data sets, the results show that, compared with the traditional BPNN classification model, ACO-BPNN The classification accuracy of the BPNN classification model is higher and the classification effect is better.

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“…Another approach to solving this problem is the use of fuzzy logic to optimize the fuzzy controller and genetic algorithms, such as in [8], but in which authors are focusing on the control of the ship. Similarly, an adaptive fuzzy controller is used for trajectory control purposes in [9], but with a limitation to its application in ship control.…”

Section: Literature Reviewmentioning

confidence: 99%

Optimization of Fuzzy Logic Based Virtual Pilot for Wargaming

Štefek

Františ

2021

Mathematics

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This paper deals with the design of an autopilot based on a set of fuzzy controllers. The model of the aircraft that the autopilot controls is defined as a model with 6 degrees of freedom, where the inputs to this model are the settings of the engine thrust (DX), rudder rotation (Dl) and elevators (Dm and Dn). The fuzzy controllers are of the Mamdani type, where the set of parameters defining the controller allow the derivation of membership functions of the input variables and membership functions of the output variables. The parameters of fuzzy controllers are determined by the optimization process. For the purpose of optimization, a fitness function is defined, which derives the simulation parameters from its parameter (vector), and the simulation subsequently performed and evaluated determines whether it is a feasible solution in addition the value of this solution. By this optimization process, the sub-optimal solution is found and is then used to define the settings of the fuzzy controllers and, therefore, the autopilot. This paper contains a description of each step of the solution of the described problem, and with the help of the obtained results, it is determined that the presented procedure allows us to find an autopilot capable of controlling the defined model of the aircraft. In addition, there is a brief description regarding the misconceptions explored during the development of the experiment.

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Neural network classifier for automatic course-keeping based on fuzzy logic

Cited by 5 publications

References 9 publications

Improving the efficiency of using multivalued logic tools

Improving the efficiency of using multivalued logic tools

Neural Network Classifier Improvements Based on Ant Colony Algorithm

Optimization of Fuzzy Logic Based Virtual Pilot for Wargaming

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