In this paper, the memorization capability of a multilayer interpolative neural network is exploited to estimate a mobile position based on three angles of arrival. The neural network is trained with ideal angles-position patterns distributed uniformly throughout the region. This approach is compared with two other analytical methods, the average-position method which relies on finding the average position of the vertices of the uncertainty triangular region and the optimal position method which relies on finding the nearest ideal angles-position pattern to the measured angles. Simulation results based on estimations of the mobile position of particles moving along a nonlinear path show that the interpolative neural network approach outperforms the two other methods in its estimations for different noise conditions.
APDBN Rashid, International Journal of Humanities and Social Sciences/ RIMAK, 2023
Increasing world demand for renewable energy resources as wind energy was one of the goals behind research optimization of energy production from wind farms. Wake is one of the important phenomena in this field. This paper focuses on understanding the effect of angle of attack (α) on wake characteristics behind single horizontal axis wind turbines (HAWT). This was done by design three rotors different from each other in value of α used in the rotor design process. Values of α were (4.8˚,9.5˚,19˚). The numerical simulations were conducted using Ansys Workbench 19- Fluent code; the used turbulence model was (k-ω SST). The results showed that best value for extracted wind energy was at α=19˚, spread distance of wak
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The present work aims to investigate the aerodynamic characteristics of the winglet cant angle of Boeing 737-800 wing numerically and experimentally. The wing contain two swept angles 38.3o and 29.13o respectively, taper ratio 0.15 and aspect ratio 8.04. The wing involves three types of airfoils sections. Four cant angles for blended winglet have been considered (0o, 34o, 60o, 83.3o). The winglet has been analyzed to find the best cant angle for the wing without and with winglet. These models have been tested theoretically at Reynolds number of 2.06 x106 in order to study the winglet aerodynamic characteristics which consist of coefficient of Drag, coefficient of lift and Lift to drag ratio, pitching moment coefficient and bending moment co
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A three-stage learning algorithm for deep multilayer perceptron (DMLP) with effective weight initialisation based on sparse auto-encoder is proposed in this paper, which aims to overcome difficulties in training deep neural networks with limited training data in high-dimensional feature space. At the first stage, unsupervised learning is adopted using sparse auto-encoder to obtain the initial weights of the feature extraction layers of the DMLP. At the second stage, error back-propagation is used to train the DMLP by fixing the weights obtained at the first stage for its feature extraction layers. At the third stage, all the weights of the DMLP obtained at the second stage are refined by error back-propagation. Network structures an
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Vehicular ad hoc networks (VANETs) are considered an emerging technology in the industrial and educational fields. This technology is essential in the deployment of the intelligent transportation system, which is targeted to improve safety and efficiency of traffic. The implementation of VANETs can be effectively executed by transmitting data among vehicles with the use of multiple hops. However, the intrinsic characteristics of VANETs, such as its dynamic network topology and intermittent connectivity, limit data delivery. One particular challenge of this network is the possibility that the contributing node may only remain in the network for a limited time. Hence, to prevent data loss from that node, the information must reach the destina
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This paper describes a new proposed structure of the Proportional Integral Derivative (PID) controller based on modified Elman neural network for the DC-DC buck converter system which is used in battery operation of the portable devices. The Dolphin Echolocation Optimization (DEO) algorithm is considered as a perfect on-line tuning technique therefore, it was used for tuning and obtaining the parameters of the modified Elman neural-PID controller to avoid the local minimum problem during learning the proposed controller. Simulation results show that the best weight parameters of the proposed controller, which are taken from the DEO, lead to find the best action and unsaturated state that will stabilize the Buck converter system performan
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Any software application can be divided into four distinct interconnected domains namely, problem domain, usage domain, development domain and system domain. A methodology for assistive technology software development is presented here that seeks to provide a framework for requirements elicitation studies together with their subsequent mapping implementing use-case driven object-oriented analysis for component based software architectures. Early feedback on user interface components effectiveness is adopted through process usability evaluation. A model is suggested that consists of the three environments; problem, conceptual, and representational environments or worlds. This model aims to emphasize on the relationship between the objects
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