Temat: adaptive clustering - Katalog OPAC zbiorów

Skocz do pozycji: 1.

Tytuł:: Fuzzy adaptive control of a class of MISO nonlinear systems
Autorzy:: Lagrat, I.
Ouakka, H.
Boutnhidi, I.
Powiązania:: https://bibliotekanauki.pl/articles/971004.pdf
Data publikacji:: 2008
Wydawca:: Polska Akademia Nauk. Instytut Badań Systemowych PAN
Tematy:: identyfikacja
sterowanie adaptacyjne
układ nieliniowy
MISO systems
identification
fuzzy clustering
Takagi-Sugeno fuzzy model
adaptive control
nonlinear system
Opis:: This paper presents a fuzzy adaptive control of a class of MISO nonlinear systems. The dynamic behaviour of each MISO systems is composed of a nonlinear term, interactions effect between the inputs, and disturbances. In these circumstances, adaptive control becomes very difficult to implement and not always an evident task. Thus, the MISO system is approximated by the Takagi-Sugeno fuzzy model. The advantage of this approximation is beneficial in the sense that it allows for converting the nonlinear problem into a linear one. In this respect, the coupling, nonlinearity and unmodeled dynamics are easily compensated. The identification and the control are conducted at the level of each local linear model based on fuzzy approach. The computational load and the complexity of nonlinear approach are reduced and permit wide applicability. The validity and the performance are tested numerically.
Źródło:: Control and Cybernetics; 2008, 37, 1; 177-190
0324-8569
Pojawia się w:: Control and Cybernetics
Dostawca treści:: Biblioteka Nauki

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Skocz do pozycji: 2.

Tytuł:: An Effective and Fast Iranian License Plate Detection Using Statistical and Geometrical Approaches
Autorzy:: Poursiyah, Saman
Salami, Hosian
Mohebbi, Mohamad Reza
Tabatabaee, Hamid
Powiązania:: https://bibliotekanauki.pl/articles/102715.pdf
Data publikacji:: 2018
Wydawca:: Stowarzyszenie Inżynierów i Techników Mechaników Polskich
Tematy:: determine location of license plate
adaptive contrast stretch
character analysis and clustering
tablica rejestracyjna
określanie lokalizacji
zastosowanie kontrastu
Opis:: The first step in the process of detection a license plate is to determine the location of the plate. The output of this stage should be accurate enough and calculations will be completed within a short time. The reason for this is that the output of this stage is as input in the next steps. If the step to determine the location is encountered error, then the operation of the next steps will also be interrupted. In this paper, a new method is used to improve the contrast of the image, delete non-numeric characters, analysis and clustering of plain characters in order to determine the location of an Iranian car license plate with dark characters, a clear background is provided. The proposed method reduces the overall complexity of the algorithm and in addition to its ease of implementation, the system’s speed and efficiency improve the location of the plate. The proposed algorithm is independent of the number of vehicle plates in the image, image size, complete unread plate and in contrast to brightness variations, it is largely resistant. The results of the test on two different data sets with 67 and 492 images, to an accuracy of 100 and 99.59 percent with an error rate of 1.5 and 1.63 and the runtime of 109 and 17.5 milliseconds averaged, were achieved.
Źródło:: Advances in Science and Technology. Research Journal; 2018, 12, 4; 115-125
2299-8624
Pojawia się w:: Advances in Science and Technology. Research Journal
Dostawca treści:: Biblioteka Nauki

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Skocz do pozycji: 3.

Tytuł:: Development of C-Means clustering based adaptive fuzzy controller for a flapping wing micro air vehicle
Autorzy:: Ferdaus, Md Meftahul
Anavatti, Sreenatha G.
Garratt, Matthew A.
Pratama, Mahardhika
Powiązania:: https://bibliotekanauki.pl/articles/91692.pdf
Data publikacji:: 2019
Wydawca:: Społeczna Akademia Nauk w Łodzi. Polskie Towarzystwo Sieci Neuronowych
Tematy:: adaptive fuzzy
clustering
flapping wing
micro air vehicle
Opis:: Advanced and accurate modelling of a Flapping Wing Micro Air Vehicle (FW MAV) and its control is one of the recent research topics related to the field of autonomous MAVs. Some desiring features of the FW MAV are quick flight, vertical take-off and landing, hovering, and fast turn, and enhanced manoeuvrability contrasted with similar-sized fixed and rotary wing MAVs. Inspired by the FW MAV’s advanced features, a four-wing Natureinspired (NI) FW MAV is modelled and controlled in this work. The Fuzzy C-Means (FCM) clustering algorithm is utilized to construct the data-driven NIFW MAV model. Being model free, it does not depend on the system dynamics and can incorporate various uncertainties like sensor error, wind gust etc. Furthermore, a Takagi-Sugeno (T-S) fuzzy structure based adaptive fuzzy controller is proposed. The proposed adaptive controller can tune its antecedent and consequent parameters using FCM clustering technique. This controller is employed to control the altitude of the NIFW MAV, and compared with a standalone Proportional Integral Derivative (PID) controller, and a Sliding Mode Control (SMC) theory based advanced controller. Parameter adaptation of the proposed controller helps to outperform it static PID counterpart. Performance of our controller is also comparable with its advanced and complex counterpart namely SMC-Fuzzy controller.
Źródło:: Journal of Artificial Intelligence and Soft Computing Research; 2019, 9, 2; 99-109
2083-2567
2449-6499
Pojawia się w:: Journal of Artificial Intelligence and Soft Computing Research
Dostawca treści:: Biblioteka Nauki

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Skocz do pozycji: 4.

Tytuł:: An Innovative Multiple Attribute Based Distributed Clustering with Sleep/Wake Scheduling Mechanism for WSN
Autorzy:: Chavan, Shankar D.
Jagdale, Shahaji R.
Kulkarni, Dhanashree A.
Jadhav, Sneha R.
Powiązania:: https://bibliotekanauki.pl/articles/1844582.pdf
Data publikacji:: 2021
Wydawca:: Polska Akademia Nauk. Czytelnia Czasopism PAN
Tematy:: advanced distributed
energy efficient
adaptive clustering
clustering
lifetime
sleep-wake cluster head scheduling
throughput
wireless sensor network
Opis:: Wireless sensor network is a dynamic field of networking and communication because of its increasing demand in critical Industrial and Robotics applications. Clustering is the technique mainly used in the WSN to deal with large load density for efficient energy conservation. Formation of number of duplicate clusters in the clustering algorithm decreases the throughput and network lifetime of WSN. To deal with this problem, advance distributive energy-efficient adaptive clustering protocol with sleep/wake scheduling algorithm (DEACP-S/W) for the selection of optimal cluster head is presented in this paper. The presented sleep/wake cluster head scheduling along with distributive adaptive clustering protocol helps in reducing the transmission delay by properly balancing of load among nodes. The performance of algorithm is evaluated on the basis of network lifetime, throughput, average residual energy, packet delivered to the base station (BS) and CH of nodes. The results are compared with standard LEACH and DEACP protocols and it is observed that the proposed protocol performs better than existing algorithms. Throughput is improved by 8.1% over LEACH and by 2.7% over DEACP. Average residual energy is increased by 6.4% over LEACH and by 4% over DEACP. Also, the network is operable for nearly 33% more rounds compared to these reference algorithms which ultimately results in increasing lifetime of the Wireless Sensor Network.
Źródło:: International Journal of Electronics and Telecommunications; 2021, 67, 3; 437-443
2300-1933
Pojawia się w:: International Journal of Electronics and Telecommunications
Dostawca treści:: Biblioteka Nauki

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