Search Results - (( sequence optimization _ algorithm ) OR ( using optimization sensor algorithm ))

A reinforcement learning-based energy-efficient spectrum-aware clustering algorithm for cognitive radio wireless sensor network by Mustapha, Ibrahim

“…Simulation results show convergence, learning and adaptability of the RL based algorithms to dynamic environment toward achieving the optimal solutions. …”
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Development of self-learning algorithm for autonomous system utilizing reinforcement learning and unsupervised weightless neural network / Yusman Yusof by Yusof, Yusman

“…In the simulation the robot is equipped with thirteen distance sensing sensors. From the simulation result, by using these sensors information the AUTOWiSARD algorithm can successfully differentiate and classify states without supervision, while the Q-learning algorithm is able to produce and optimized states-actions policy. …”
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Supervised deep learning algorithms for process fault detection and diagnosis under different temporal subsequence length of process data by Terence Chia Yi Kai, Agus Saptoro, Zulfan Adi Putra, King Hann Lim, Wan Sieng Yeo, Jaka Sunarso

“…Deep learning algorithms were widely used among all the data-driven algorithms. …”
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Simulated Kalman Filter with modified measurement, substitution mutation and hamming distance calculation for solving traveling salesman problem by Suhazri Amrin, Rahmad, Zuwairie, Ibrahim, Zulkifli, Md. Yusof

“…There were also attempts to hybridize SKF with other famous algorithms such as Particle Swarm Optimization (PSO), Gravitational Search Algorithm (GSA), and Sine Cosine Algorithm (SCA) to improve its performance. …”
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Global Algorithms for Nonlinear Discrete Optimization and Discrete-Valued Optimal Control Problems by Woon, Siew Fang

“…These problems are known as discrete-valued optimal control problems. Most practical discrete-valued optimal control problems have multiple local minima and thus require global optimization methods to generate practically useful solutions. …”
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Vector evaluated particle swarm optimization approach to solve assembly sequence planning problem by A. Mukred, Jameel A., A. Rahim, Ruzairi, Mohamad, Elmy Johana, Salh, Adeeb, Ashyap, Adel Y. I., Abdullah, Qazwan, AL-Fadhali, Najib, Al-Ameri, S., Al-Ashwal, Rania

“…Simulated Annealing (SA) is used where search is done in sequence basis and to solve optimization problems. …”
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A sequential handwriting recognition model based on a dynamically configurable CRNN by Al-Saffar, Ahmed, Suryanti, Awang, Al-Saiagh, Wafaa, Al-Khaleefa, Ahmed Salih, Abed, Saad Adnan

“…Inspired by the neuroevolutionary technique, this paper proposes a Dynamically Configurable Convolutional Recurrent Neural Network (DC-CRNN) for the handwriting recognition sequence modeling task. The proposed DC-CRNN is based on the Salp Swarm Optimization Algorithm (SSA), which generates the optimal structure and hyperparameters for Convolutional Recurrent Neural Networks (CRNNs). …”
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Direct Adaptive Predictive Control For Wastewater Treatment Plant by Shair, Ezreen Farina, Abu Bakar, Norazhar, Mohd Nor, Arfah Syahida, Mohd Azam, Sazuan Nazrah, Mohd Sobran, Nur Maisarah, Zainal Abidin, Amar Faiz

“…This N4SID plays the role of the software sensor for on-line estimation of prediction matrices and control matrices of the bioprocess, joint together with model predictive control (MPC) in order to obtain the optimal control sequence. …”
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Clarity-optimized wavelet with autoencoder-ReliefF ranking for enhanced UHF PD signal feature extraction by Azam, Kayser M.K., Othman, Mohamadariff, Hossain, A K M Zakir, Kumar, Dhruba, Wong, Jee Keen Raymond, Illias, Hazlee Azil, Abdul Latef, Tarik, Mat Ibrahim, Masrullizam

“…This article investigates advanced signal processing methodologies, with a focus on wavelet-based techniques, for the analysis of time-domain partial discharge (PD) signals captured using ultra-high frequency (UHF) sensors. The raw signals are systematically processed through a sequence of operations including bandpass filtering, wavelet-based denoising, DC offset removal, and pulse extraction. …”
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Application of genetic algorithm methods to optimize flowshop sequencing problem by Mohd Fadil, Md Sairi

“…Application of genetic algorithm method to optimize flow shop sequencing problem as the title of this project is the study about the method used in order to optimize flow shop sequencing problem. …”
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Assembly sequence optimization using the bees algorithm by Kamaruddin, Shafie, Azmi, Nabilah, Sukindar, Nor Aiman

“…As a result, the Bees Algorithm outperforms other algorithms in dealing with the multi-modal optimization problem of assembly sequence optimization.…”
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A centralized localization algorithm for prolonging the lifetime of wireless sensor networks using particle swarm optimization in the existence of obstacles by Abdulhasan Al-Jarah, Ali Husam

“…Particle Swarm Optimization has been used in the proposed algorithm to minimize the fitness function. …”
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An enhanced swap sequence-based particle swarm optimization algorithm to solve TSP by Bibi Aamirah Shafaa Emambocus, Muhammed Basheer Jasser, Muzaffar Hamzah, Aida Mustapha, Angela Amphawan

“…To evaluate the proposed algorithm, the solutions to the TSP problem obtained from the proposed algorithm and swap sequence based PSO are compared in terms of the best solution, mean solution, and time taken to converge to the optimal solution. …”
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Simulated Kalman Filter optimization algorithm for maximization of wireless sensor networks coverage by Nor Azlina, Ab. Aziz, Zuwairie, Ibrahim, Kamarulzaman, Ab Aziz, Nor Hidayati, Abdul Aziz

“…It had been successfully used for optimization of many engineering problems. …”
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Node placement optimization using extended virtual force and cuckoo search algorithm in wireless sensor network by Puteri Azwa, Ahmad

“…This study proposed Extended Virtual Force and Cuckoo Search (EVFCS) algorithm with a combination of EVFA and CS algorithm to find an optimal node placement. …”
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Cluster head selection optimization in wireless sensor network via genetic-based evolutionary algorithm by Vincent Chung, Hamzarul Alif Hamzah, Norah Tuah, Kit, Guan Lim, Min, Keng Tan, Kenneth Tze Kin Teo

“…Genetic-based evolutionary algorithms such as Genetic Algorithm (GA) and Differential Evolution (DE) have been popularly used to optimize cluster head selection in WSN to improve energy efficiency for the extension of network lifetime. …”
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Comparative Analysis of Low Discrepancy Sequence-Based Initialization Approaches Using Population-Based Algorithms for Solving the Global Optimization Problems by Waqas Haider Bangyal, Kashif Nisar, Ag. Asri Bin Ag. Ibrahim, Muhammad Reazul Haque, Joel J. P. C. Rodrigues, Danda B. Rawat

“…These algorithms can influence the convergence to find an efficient optimal solution. …”
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Assessment of integrated assembly sequence planning and line balancing optimization using metaheuristic algorithms by Mohd Fadzil Faisae, Ab Rashid, Ullah, Wasif, Muhammad Ammar, Nik Mu’tasim

“…These algorithms include Genetic Algorithm (GA), Ant Colony Optimization (ACO), and Particle Swarm Optimization (PSO). …”
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Gravitational Search Algorithm for Assembly Sequence Planning by Ismail, Ibrahim, Zuwairie, Ibrahim, Hamzah, Ahmad, Mohd Falfazli, Mat Jusof, Zulkifli, Md. Yusof, Sophan Wahyudi, Nawawi, Marizan, Mubin

“…Thus, it is needed to find the optimal sequence from the feasible assembly sequences. …”
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Global optimization method for continuous - Time sensor scheduling by Woon, Siew Fang, Rehbock, Volker, Loxton, Ryan C.

“…We consider a situation in which several sensors are used to collect data for signal processing since operating multiple sensors simultaneously canses system interference, only one sensor can be active at any one time.The problem of scheduling a discrete-valued optimal control problem.This problem cannot be solved using conventional optimization problem.The Transformed problem is then decomposed into a bi-level optimization problem, which is solved using a discreate filled function method in conjunction with a conventional optimal control algorithm.Numerical results show that our algorithm is robust, efficient, and reliable in attaining a near globally optimal solution.…”
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