Ashvini Kulkarni^1,2, P. Augusta Sophy Beulet^1,*

Intelligent Automation & Soft Computing, Vol.37, No.1, pp. 127-146, 2023, DOI:10.32604/iasc.2023.035144 - 29 April 2023

Abstract It is widely acknowledged that navigation is a significant source of between sites. The Global Positioning System (GPS) has numerous navigational advancements, and hence it is used widely. GPS navigation can be compromised at any level between position, location, and estimation, to the detriment of the user. Consequently, a navigation system requires the precise location and underpinning tracking of an object without signal loss. The objective of a hybrid environment prediction system is to foresee the location of the user and their territory by employing a variety of sensors for position estimation and monitoring navigation.… More >

Mohamed Hassan Essai Ali^1,*, Fahad Alraddady², Mo’ath Y. Al-Thunaibat³, Shaima Elnazer²

CMES-Computer Modeling in Engineering & Sciences, Vol.135, No.1, pp. 755-778, 2023, DOI:10.32604/cmes.2022.022246 - 29 September 2022

Abstract For a 5G wireless communication system, a convolutional deep neural network (CNN) is employed to synthesize a robust channel state estimator (CSE). The proposed CSE extracts channel information from transmit-and-receive pairs through offline training to estimate the channel state information. Also, it utilizes pilots to offer more helpful information about the communication channel. The proposed CNN-CSE performance is compared with previously published results for Bidirectional/long short-term memory (BiLSTM/LSTM) NNs-based CSEs. The CNN-CSE achieves outstanding performance using sufficient pilots only and loses its functionality at limited pilots compared with BiLSTM and LSTM-based estimators. Using three different More >

Giovanny Morocho, Diego Carrión¹

Revista Internacional de Métodos Numéricos para Cálculo y Diseño en Ingeniería, Vol.38, No.1, pp. 1-17, 2022, DOI:10.23967/j.rimni.2022.03.010 - 30 March 2022

Abstract The present research proposes to design and apply a state estimator algorithm in electrical power systems, applying the Weighted Least Squares methodology, through a process called non-linear hybrid estimator, the same one that uses measurements from PMUs and conventional measurements. in addition, to find the optimal PMU locations respecting the observability and redundancy restrictions for the Electric Power Systems, through mixed integer linear programming, considering the N-1 contingencies in the SEP. The proposed state estimator is adjusted to the measurements obtained, in the presence of contingencies in the SEP. The simulations obtained as a result More >