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Intelligent classification algorithms in enhancing the performance of support vector machine
Published 2019“…The difference between the algorithms is the size of the solution archive. The size of the archive in ACOMV is fixed while in IACOMV, the size of solution archive increases as the optimization procedure progress. …”
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Combining Recursive Least Square and Principal Component Analysis for Assisted History Matching
Published 2014“…History matching is a process of altering parameters in a reservoir simulator in order to match production performance with observed historical data. …”
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Artificial neural network and inverse solution method for assisted history matching of a reservoir model
Published 2017“…A typical inverse problem encountered in petroleum industries is referred to as history matching. In the early days, history matching was undertaken by manually changing sensitive reservoir parameters until a reasonable match between observed and simulated pressure and production data are obtained. …”
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Abnormalities and fraud electric meter detection using hybrid support vector machine & genetic algorithm
Published 2023Subjects:Conference Paper -
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Refinement of Tuned Mass Damper parameters on machine support structure using dynamic Cuckoo Search algorithm
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Estimation of optimal machining control parameters using artificial bee colony
Published 2013“…This research employed ABC algorithm to optimize the machining control parameters that lead to a minimum surface roughness (R a) value for AWJ machining. …”
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An Improved Hybrid of Particle Swarm Optimization and the Gravitational Search Algorithm to Produce a Kinetic Parameter Estimation of Aspartate Biochemical Pathways
Published 2017“…Although the model itself can potentially match a set of experimental data, a high-performance estimation algorithm is required to improve the quality of the solutions. …”
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Development of cell formation algorithm and model for cellular manufacturing system
Published 2011“…Therefore, for this proposes good benchmarked algorithm, bacteria foraging algorithm is selected and developed to solve multiobjective cell formation model and traced constraints satisfaction handling to produce feasible optimal solution. …”
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Deep learning model for predicting and detecting overlapping symptoms of cardiovascular diseases in hospitals of UAE
Published 2012“…DL strengths comprises of its potential to automatically diagnose clinical appearances, enhance decision-making, recognizing the phenotypes, and effectively select treatment methodology to complex diseases. The DL algorithm that can be well matched to chemistry is the hemodynamic and electrophysiological parameters catalogues that are effectively captured over continuous periods by wearable machines, as well as the division of images into captured images or pictures (Nagueh, 2016). …”
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Optimization of cnc turning parameters for minimizing temperature rise in aluminum using a genetic algorithm
Published 2024“…Thus, an optimization process is important to obtain optimized machining outcomes by optimizing machining parameters. …”
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RSA Encryption & Decryption using JAVA
Published 2006“…References and theories to support the research of 'RSA Encryption/Decryption using Java' have been disclosed in Literature Review section. …”
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Final Year Project -
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LINGUISTIC FUZZY MODELING IN LASER MACHINING QUALITY EVALUATION
Published 2007“…In this research, the inputs are the key variables of the design parameters which generates the singleton output to evaluate the cut edge quality in laser machining. …”
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Multi-objectives process optimization in end milling process of aluminium alloy 6061-T6 using genetic algorithm
Published 2024“…For future study, other methods or algorithms can be applied in other machining processes to obtain optimum machining parameters.…”
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Different mutation and crossover set of genetic programming in an automated machine learning
Published 2020“…The function of Genetic Programming is to optimize the best combination of solutions from the possible pipelines of machine learning modelling, including selection of algorithms and parameters optimization of the selected algorithm. …”
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Different mutation and crossover set of genetic programming in an automated machine learning
Published 2020“…The function of Genetic Programming is to optimize the best combination of solutions from the possible pipelines of machine learning modelling, including selection of algorithms and parameters optimization of the selected algorithm. …”
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Measuring height of high-voltage transmission poles using unmanned aerial vehicle (UAV) imagery
Published 2017“…Results were compared with well-known algorithms; including, for example, global and local stereo matching algorithms. …”
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Provider independent cryptographic tools
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