Search Results - (( intelligence based costing algorithm ) OR ( intelligence based training algorithm ))
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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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Hybrid Intelligent Warning System for Boiler tube Leak Trips
Published 2017“…The first intelligent warning system (IWS-1) represents the use of pure artificial neural network system whereas the second intelligent warning system (IWS-2) represents merging of genetic algorithms and artificial neural networks as a hybrid intelligent system. …”
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Development of Machine Learning Algorithm for Acquiring Machining Data in Turning Process
Published 2004“…Artificial Neural Network (ANN) was selected from Machine Learning Algorithms to be the learning algorithm. ANN is a computer-based simulation of the living nervous system which works quite differently from conventional programming. …”
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Knowledge base processing method based on text classification algorithm
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An adaptive neuro-fuzzy inference system employed cuk converter for PV applications
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Water level forecasting using feed forward neural networks optimized by African Buffalo Algorithm (ABO)
Published 2019“…This research proposed a swarm intelligence training algorithm, Improved African Buffalo Optimization algorithm (IABO) based on the Metaheuristic method called the African Buffalo Optimization algorithm (ABO). …”
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Intelligent image noise types recognition and denoising system using deep learning / Khaw Hui Ying
Published 2019“…In order to reduce the training time and computational cost of the algorithm, Principal Components Analysis (PCA) pretraining strategy is deployed to obtain data adaptive filter banks. …”
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Optimization of neural network architecture using genetic algorithm for load forecasting
Published 2014“…In this paper, a computational intelligent technique genetic algorithm (GA) is implemented for the optimization of artificial neural network (ANN) architecture. …”
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Identification of transformer fault based on dissolved gas analysis using hybrid support vector machine-modified evolutionary particle swarm optimisation
Published 2018“…It was found that the proposed hybrid SVM-Modified EPSO (MEPSO)-Time Varying Acceleration Coefficient (TVAC) technique results in the highest correct identification percentage of faults in a power transformer compared to other PSO algorithms. Thus, the proposed technique can be one of the potential solutions to identify the transformer fault type based on DGA data on site.…”
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Machine-learning-based adaptive distance protection relay to eliminate zone-3 protection under-reach problem on statcom-compensated transmission lines
Published 2020“…The BayesNet provides the best integrated MLADR fault classifier model better at a 5 % significance level than other deployed algorithms in the intelligent supervised learning model realization. …”
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Development of vehicle counting system by using background subtraction technique / Muhammad Fadhli Md Azemin
Published 2018“…Vehicle classification and counting has been voice require issue of intelligent traffic control system (ITS). Before this, the conventional method counting vehicles is based on manually counting using a worker. …”
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Student Project -
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A Reinforced Active Learning Algorithm for Semantic Segmentation in Complex Imaging
Published 2021“…Semantic segmentation annotation helps train computer vision based Artificial Intelligence models where each image pixel is assigned to a specific object class. …”
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A Dijkstra’s Mobile Web Application Engine for Generating Integrated Light Rail Transit Route
Published 2010“…Currently, our research is focusing on Dijkstra’s algorithms to provide more effective and intelligent shortest path system to provide the solution for traveler to reach the desired destination. …”
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Identification and predictive control of spray tower system using artificial neural network and differential evolution algorithm
Published 2015“…This includes the use of an artificial neural network (ANN) based predictive control strategy and differential evolution (DE) optimization algorithm to determines the optimal control signal, uk (liquid droplet size, dD) by minimizing the cost function such that the output is set below the allowable PM concentration. …”
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Proceeding Paper
