Search Results - (( sequence optimization sensor algorithm ) OR ( parameter optimization steam algorithm ))
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Combining Genetic Algorithm and Artificial Neural Network to optimize biomass steam power plant emission / Ahmad Razlan Yusoff and Ishak Abdul Aziz
Published 2008“…A parametric study of Genetic Algorithms (GA) parameters such as population size, mutation rates and crossover rates are carried out to get optimal parameters for a GAANN model. …”
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Neuro-Fuzzy and Particle Swarm Optimization based Model for the Steam and Cooling sections of a Cogeneration and Cooling Plant
Published 2009“…Neuro-fuzzy approach trained by a sequence of optimization algorithms-Particle Swarm Optimization (PSO) followed by Back-Propagation (BP)-is used to develop models for the steam drum pressure, steam drum water level, steam flow rate and chilled water supply temperature. …”
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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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SYSTEMATIC DESIGN ALGORITHM FOR ENERGY EFFICIENT AND COST EFFECTIVE HYDROGEN PRODUCTION FROM PALM WASTE
Published 2012“…In the current study, a systematic autonomous algorithm incorporating reaction kinetics model, flowsheet calculations, heat integration analysis and economic evaluation, has been developed to calculate optimum parameters giving minimum hydrogen production cost using optimization strategies. …”
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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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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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Improving the environmental impact of palm kernel shell through maximizing its production of hydrogen and syngas using advanced artificial intelligence
Published 2019“…The main target of this research is to improve the production of hydrogen and syngas from palm kernel shell (PKS) steam gasification through defining the optimal operating parametersâ�� using a modern optimization algorithm. …”
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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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Temperature control of a pilot plant reactor system using a genetic algorithm model‐based control approach
Published 2007“…The work described in this paper aims at exploring the use of an artificial intelligence technique, i.e. genetic algorithm (GA), for designing an optimal model-based controller to regulate the temperature of a reactor. …”
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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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Development of optimized maintenance scheduling model for coal-fired power plant boiler
Published 2023“…The optimal schedules obtained were compared with the actual based on parameters and judgement from power plant planning team. …”
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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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