Search Results - (( parameter optimization steam algorithm ) OR ( gram extraction methods 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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3
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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4
Classification of gram-positive and gram-negative bacterial images based on machine learning algorithm
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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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Effective query structuring with ranking using named entity categories for XML retrieval
Published 2016“…The method employs Semantic Tags Extraction (STSE) algorithm to extract semantic tags of an element and Element Enrichment (EERM) algorithm to enrich the elements. …”
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8
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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Reduced Set Kernel Principal Component Analysis (Rskpca) Algorithm for Palm Print Based Mobile Biometric System
Published 2015“…A new approach in feature extraction called Reduced-Set Kernel Principal Component Analysis (RSKPCA) is proposed to speed up the processing in feature extraction. …”
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10
Intelligent deep machine learning cyber phishing URL detection based on BERT features extraction
Published 2022“…Next, a deep convolutional neural network method was utilised to detect phishing URLs. It was used to constitute words or n-grams in order to extract higher-level features. …”
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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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Improvement on rooftop classification of worldview-3 imagery using object-based image analysis
Published 2019“…Therefore, the LiDAR derived data were combined with WV-3 image using different fusion methods such as layer stacking (LS), Gram–Schmidt (GS), and PC spectral sharpening (PCSS). …”
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Prediction of cause of death from forensic autopsy reports using text classification techniques: A comparative study
Published 2018“…Methods: For experiments, the autopsy reports belonging to eight different causes of death were collected, preprocessed and converted into 43 master feature vectors using various schemes for feature extraction, representation, and reduction. …”
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Semi-supervised learning for sentiment classification with ensemble multi-classifier approach
Published 2022“…The research went through pre-processing, vectorization, and feature extraction using TF-IDF and n-grams. Support Vector Machine (SVM) or Random Forest for tokenization was used to separate unigram, bigram, and trigram in model generation. …”
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Design and simulation of hyperspectral lens system for a flood monitoring CubeSat
Published 2026“…However, current optical remote sensing methods to monitor floods, particularly multispectral imaging (MSI), are limited by low spectral resolution and rely heavily on complex post-processing algorithms to extract accurate flood information, leading to higher computational costs and reduced efficiency. …”
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