Search Results - (( intelligence based training algorithm ) OR ( intelligence based drops algorithm ))
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A multi-nets ANN model for real-time performance-based automatic fault diagnosis of industrial gas turbine engines
Published 2017“…In recent years, a new discipline, known as artificial intelligence-based methods, has emerged, which allows the behavior of the system to be studied using operational data. …”
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IOT Based Smart Wastewater Treatment Model for Industry 4.0 Using Artificial Intelligence
Published 2022“…To anticipate COD levels in influential and effluent areas, two ANN-based techniques have been presented. The proper structure for the neural network models was identified via a variety of training and model testing methods. …”
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Intelligent Examination Timetabling System Using Hybrid Intelligent Water Drops Algorithm
Published 2024“…Intelligent Water Drops algorithm (IWD) is a population-based algorithm where each drop represents a solution and the sharing between the drops during the search lead to better drops. …”
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Intelligent examination timetabling system using hybrid intelligent water drops algorithm
Published 2015“…This paper proposes Hybrid Intelligent Water Drops (HIWD) algorithm to solve Tamhidi programs uncapacitated examination timetabling problem in Universiti Sains Islamic Malaysia (USIM).Intelligent Water Drops algorithm (IWD) is a population-based algorithm where each drop represents a solution and the sharing between the drops during the search lead to better drops.The results of this study prove that the proposed algorithm can produce a high quality examination timetable in shorter time in comparison with the manual timetable.…”
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Solving university examination timetabling problem using intelligent water drops algorithm
Published 2024Subjects: “…Intelligent water drops algorithm…”
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Modified And Ensemble Intelligent Water Drop Algorithms And Their Applications
Published 2015“…Pertama, algoritma TAC yang diubahsuai, diperkenalkan. The Intelligent Water Drop (IWD) algorithm is a swarm-based model that is useful for undertaking optimization problems. …”
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Solving University Examination Timetabling Problem Using Intelligent Water Drops Algorithm
Published 2024“…IWD is a recent metaheuristic population-based algorithm belonging to swarm intelligent category which simulate river system. …”
Proceedings Paper -
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Enhanced Intelligent Water Drops Algorithm for University Examination Timetabling Problems
Published 2024“…This thesis presents an investigation of using the Intelligent Water Drops (IWD) algorithm to construct and produce good quality solutions for the UETP. …”
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Optimization and discretization of dragonfly algorithm for solving continuous and discrete optimization problems
Published 2024“…The ANNs trained by the optimized DA also achieve higher accuracy than those trained by some other swarm intelligence algorithms. …”
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Integration of dual intelligent algorithms in shunt active power filter
Published 2013“…This paper presents an integration of dual intelligent algorithms: artificial neural network (ANN) based fundamental component extraction algorithm and fuzzy logic based DC-link voltage self-charging algorithm (fuzzy self-charging algorithm), in a three-phase three-wire shunt active power filter (SAPF). …”
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Effect of input variables selection on energy demand prediction based on intelligent hybrid neural networks
Published 2015“…The efficacy of these models depends upon many factors such as, neural network architecture, type of training algorithm, input training and testing data set and initial values of synaptic weights. …”
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Development of Machine Learning Algorithm for Acquiring Machining Data in Turning Process
Published 2004“…The design network is trained by presenting several target machining data that the network must learn according to a learning rule (algorithm). …”
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Optimising neural network training efficiency through spectral parameter-based multiple adaptive learning rates
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Intelligent grading of agarwood essential oil quality using artificial neural network (ANN) / Noratikah Zawani Mahabob
Published 2022“…The training and validation of the ANN was based on optimization of its training parameters and guided by the convergence of the mean squared errors (MSE). …”
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