Search Results - (( storage optimization path algorithm ) OR ( sequence optimization sensor algorithm ))
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Robotic indoor path planning using dijkstra's algorithm with multi-layer dictionaries
Published 2016“…The adjacency matrix is the naive storage structure of the algorithm. This storage structure has limited the use of the algorithm as it expands large storage space. …”
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An energy efficient reinforcement learning based cooperative channel sensing for cognitive radio sensor networks
Published 2017“…Simulation results show convergence and adaptability of the algorithm to dynamic environment in achieving optimal solutions. …”
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A reinforcement learning-based energy-efficient spectrum-aware clustering algorithm for cognitive radio wireless sensor network
Published 2016“…Simulation results show convergence, learning and adaptability of the RL based algorithms to dynamic environment toward achieving the optimal solutions. …”
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Modeling and multi-objective optimal sizing of standalone photovoltaic system based on evolutionary algorithms
Published 2020“…The IEM algorithm uses the attraction-repulsion mechanism to change the positions of solutions towards the optimality. …”
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Development of self-learning algorithm for autonomous system utilizing reinforcement learning and unsupervised weightless neural network / Yusman Yusof
Published 2019“…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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Comprehensive review of drones collision avoidance schemes: challenges and open issues
Published 2024“…We explore collision avoidance methods for UAVs from various perspectives, categorizing them into four main groups: obstacle detection and avoidance, collision avoidance algorithms, drone swarm, and path optimization. Additionally, our analysis delves into machine learning techniques, discusses metrics and simulation tools to validate collision avoidance systems, and delineates local and global algorithmic perspectives. …”
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Supervised deep learning algorithms for process fault detection and diagnosis under different temporal subsequence length of process data
Published 2025“…Current FDD technologies mostly rely on data-driven solutions by making full use of abundant process data collected by the state-of-the-art distributed process instruments and sensors. 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
Published 2022“…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
Published 2009“…We then consider the task of determining near globally optimal solutions of discrete-valued optimal control problems. …”
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An Evolutionary Stream Clustering Technique for Outlier Detection
Published 2020“…Later, this algorithm will be extended to optimize the model in detecting outlier on data streams. …”
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Direct Adaptive Predictive Control For Wastewater Treatment Plant
Published 2012“…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
Published 2025“…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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