Search Results - (( based estimation method algorithm ) OR ( using simulation learning algorithm ))

Adaptive beamforming algorithm based on Simulated Kalman Filter by Kelvin Lazarus, Lazarus

“…Zakwan, applies Opposition-Based Learning method to improve the exploration capabilities of SKF algorithm. …”
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Opposition- based simulated kalman filters and their application in system identification by Kamil Zakwan, Mohd Azmi

“…Among the various kinds of optimization algorithms, Simulated Kalman Filter (SKF) is a new population-based optimization algorithm inspired by the estimation capability of Kalman Filter. …”
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Active force control with iterative learning control algorithm for a vehicle suspension by Rosmazi, Rosli

“…ILC algorithm is implemented into AFC-based control scheme to reduce its complexity and hence faster response, by replacing the use of artificial intelligence (Al) method as proposed by previous researcher. …”
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A comparative study and simulation of object tracking algorithms by Ji, Yuanfa, Yin, Pan, Sun, Xiyan, Kamarul Hawari, Ghazali, Guo, Ning

“…This article introduces the popular object tracking algorithms, from common problems in object tracking to the classification of algorithms: Early classic trackingalgorithms, tracking algorithms based on kernel correlation filtering, and tracking algorithms based on deep learning. …”
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Parameter characterization of PEM fuel cell mathematical models using an orthogonal learning-based GOOSE algorithm by Manoharan P., Ravichandran S., Kavitha S., Tengku Hashim T.J., Alsoud A.R., Sin T.C.

“…The orthogonal learning mechanism improves the performance of the original GOOSE algorithm. …”

An intelligent framework for modelling and active vibration control of flexible structures by Mohd. Hashim, Siti Zaiton

“…Dynamic characterisations of one-dimensional flexible beam and two-dimensional flexible plate structures are presented and simulation algorithms characterising the behaviour of each structure is developed using finite difference methods. …”
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Deep Reinforcement Learning For Control by Bakar, Nurul Asyikin Abu

“…In essence, the method is to use a reward-based learning environment to watch how the agent makes decisions. …”
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Simultaneous computation of model order and parameter estimation for system identification based on opposition-based simulated Kalman filter by Badaruddin, Muhammad, Kamil Zakwan, Mohd Azmi, Zuwairie, Ibrahim, Ahmad Afif, Mohd Faudzi, Pebrianti, Dwi

“…However, the performance was worse than conventional ARX method. Current optimum opposition-based simulated Kalman filter (COOBSKF) is an improved version of simulated Kalman filter (SKF) which employs the concept of current optimum opposition-based learning (COOBL). …”
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Information Theoretic-based Feature Selection for Machine Learning by Muhammad Aliyu, Sulaiman

“…The second test evaluates IFS in a controlled study using simulated datasets. Moreover, the third test used ten natural domain datasets obtained from UCI Repository, in about fifteen different experiments, using three to four different Machine Learning Algorithms for performance evaluation. …”
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Autonomous person-following telepresence robot using monocular camera and deep learning YOLO by Mat Lazim, Izzuddin, Sakri, Ahmad Amin Firdaus, Mauzi, Suffian At-Tsauri, Sahrim, Musab, Ramli, Liyana, Noordin, Aminurrashid

“…To compensate for the monocular camera's inability to provide depth information, a novel distance estimation algorithm based on focal length and person width is introduced. …”
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A new hybrid deep neural networks (DNN) algorithm for Lorenz chaotic system parameter estimation in image encryption by Nurnajmin Qasrina Ann, Ayop Azmi

“…The first research objective is to develop a new deep learning algorithm by a hybrid of DNN and K-Means Clustering algorithms for estimating the Lorenz chaotic system. …”
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Long-term electrical energy consumption: Formulating and forecasting via optimized gene expression programming / Seyed Hamidreza Aghay Kaboli by Seyed Hamidreza , Aghay Kaboli

“…To assess the applicability and accuracy of the proposed method for long-term electrical energy consumption, its estimates are compared with those obtained from artificial neural network (ANN), support vector regression (SVR), adaptive neuro-fuzzy inference system (ANFIS), rule-based data mining algorithm, GEP, linear, quadratic and exponential models optimized by particle swarm optimization (PSO), cuckoo search algorithm (CSA), artificial cooperative search (ACS) algorithm and backtracking search algorithm (BSA). …”
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Estimation of Information Measures for Power-Function Distribution in Presence of Outliers and Their Applications by Hassan, Amal Soliman, Elsherpieny, Elsayed Ahmed, Mohamed, Rokaya Elmorsy

“…The Bayesian estimators were computed empirically using a Monte Carlo simulation based on the Gibbs sampling algorithm. …”
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Autonomous Person-following Telepresence Robot Using Monocular Camera And Deep Learning Yolo by Ahmad Amin Firdaus Sakri, Noor Hanis Izzuddin Mat Lazim, Suffian At-Tsauri Mauzi, Mus’ab Sahrim, Liyana Ramli, Aminurrashid Noordin

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A Novel Hybrid Deep Learning Model Based on Simulated Annealing and Cuckoo Search Algorithms for Automatic Radiomics-Based COVID-19 Diagnosis by Saleh, Basma Jumaa, Omar, Zaid, As’ari, Muhammad Amir, Bhateja, Vikrant, Izhar, Lila Iznita

“…To further enhance COVID-19 lesion estimation, novel optimization strategies, including a hybrid simulated annealing-cuckoo search (SA-CS) algorithm, are introduced alongside the original SA method. …”
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Comparative analysis of three approaches of antecedent part generation for an IT2 TSK FLS by Hassan, S., Khanesar, M.A., Jaafar, J., Khosravi, A.

“…Since extreme learning machine is a non-iterative estimation procedure, it is faster than gradient-based algorithms which are iterative. …”
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Physics-guided deep neural network to characterize non-Newtonian fluid flow for optimal use of energy resources by Kumar, A., Ridha, S., Narahari, M., Ilyas, S.U.

“…In this research, a novel algorithm (Herschel Bulkley Network) is introduced to simulate the non-Newtonian fluid flow in a pipe using data redundant deep neural network (DNN) for fully developed, laminar, and incompressible flow conditions. …”
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Machine Learning Based Optimal Design of On-Road Charging Lane for Smart Cities Applications by Shanmugam Y., Narayanamoorthi R., Ramachandaramurthy V.K., Bernat P., Shrestha N., Son J., Williamson S.S.

“…The algorithm not only aids in estimating the infrastructure cost of the charging lane but also predicts optimal design parameters using trained data. …”

Speed control of separately excited dc motor using artificial intelligent approach by Bernard, Albinus

“…A neural network controller with learning technique based on back propagation algorithm is developed. …”
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Enhancing the QoS performance for mobile station over LTE and WiMAX networks / Mhd Nour Hindia by Hindia, Mhd Nour

“…The selection is based on the user preferences since it uses a self-learning algorithm to determine triggers and handover thresholds dynamically. …”
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