Search Results - (( sequence optimization sensor algorithm ) OR ( based optimization _ algorithm ))
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1
An energy efficient reinforcement learning based cooperative channel sensing for cognitive radio sensor networks
Published 2017“…The results also indicate that with optimal channel sensing sequence and optimal sets of channels, sensing energy cost savings of 15.14% per channel sensing cycle can be achieved while improving PU detection accuracy and channel utilization compared to the sensing sequence based on Greedy search approach. …”
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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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3
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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5
Global Algorithms for Nonlinear Discrete Optimization and Discrete-Valued Optimal Control Problems
Published 2009“…Due to the high complexity of these problems, metaheuristic based global optimization techniques are usually required. …”
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6
Vector evaluated particle swarm optimization approach to solve assembly sequence planning problem
Published 2022“…Simulated Annealing (SA) is used where search is done in sequence basis and to solve optimization problems. Ref. [6] used (SA) approach, which is based on searching via all the feasible sequences. …”
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7
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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8
A sequential handwriting recognition model based on a dynamically configurable CRNN
Published 2021“…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
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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10
Clarity-optimized wavelet with autoencoder-ReliefF ranking for enhanced UHF PD signal feature extraction
Published 2025“…To address the challenge of identifying the most discriminative features, this work integrates advanced feature ranking algorithms, namely, auto-encoder-based ranking and the ReliefF method. …”
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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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12
Simulated Kalman Filter algorithms for solving optimization problems
Published 2019“…Applications and improvements to the HKA algorithm suggest that optimization algorithm based on estimation principle has a huge potential in solving a wide variety of optimization problems. …”
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13
Opposition-based Whale Optimization Algorithm
Published 2018“…In order to improve solution accuracy and reliability, this paper proposes a new algorithm based on WOA. The new algorithm called Opposition-based Whale Optimization (OWOA). …”
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Hybrid firefly and particle swarm optimization algorithm for multi-objective optimal power flow with distributed generation
Published 2022“…Finally, a crowding distance and non-dominated-sorting-based multi-objective hybrid firefly & particle swarm optimization (MOHFPSO) algorithm is designed for MOOPF problems. …”
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15
Rule-Based Multi-State Gravitational Search Algorithm for Discrete Optimization Problem
Published 2015“…In this study, rule-based multi-state gravitational search algorithm (RBMSGSA) algorithm is proposed to solve discrete combinatorial optimization problems. …”
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Metaheuristic multi-hop clustering optimization for energy-efficient wireless sensor network
Published 2020“…Based on the performance evaluation, GACS outperforms both Genetic Algorithm (GA)-based cluster optimization algorithm and Cuckoo Search (CS)-based multi-hop optimization algorithm.…”
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Sizing optimization of large-scale grid connected photovoltaic system using dolphin echolocation algorithm / Muhammad Zakyizzuddin Rosselan
Published 2018“…Later, an Iterative-based Sizing Algorithm (ISA) was developed to determine the optimal sizing solution which was later used as benchmark for sizing algorithms using optimization methods. …”
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18
Fuzzy adaptive teaching learning-based optimization for solving unconstrained numerical optimization problems
Published 2022“…To overcome these drawbacks and to achieve an appropriate percentage of exploitation and exploration, this study presents a new modified teaching learning-based optimization algorithm called the fuzzy adaptive teaching learning-based optimization algorithm. …”
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An enhanced swap sequence-based particle swarm optimization algorithm to solve TSP
Published 2021“…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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Optimization of cost-based hybrid flowshop scheduling using teaching-learning-based optimization algorithm
Published 2024“…This paper investigates the optimization of a CHFS problem using the Teaching Learning-Based Optimization (TLBO) algorithm. …”
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