Search Results - (( java application optimized algorithm ) OR ( parameters variation learning algorithm ))
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Optimization of blood vessel detection in retina images using multithreading and native code for portable devices
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Performance evaluation of real-time multiprocessor scheduling algorithms
Published 2016“…These results suggests that optimal algorithms may turn to be non-optimal when practically implemented, unlike USG which reveals far less scheduling overhead and hence could be practically implemented in real-world applications. …”
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Route Optimization System
Published 2005“…After much research into the many algorithms available, and considering some, including Genetic Algorithm (GA), the author selected Dijkstra's Algorithm (DA). …”
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Final Year Project -
4
Optimal variational mode decomposition and integrated extreme learning machine for network traffic prediction
Published 2021“…However, most of the existing evolutionary algorithms have some adjustable parameters which depend on subjective experience or prior knowledge. …”
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Attribute reduction based scheduling algorithm with enhanced hybrid genetic algorithm and particle swarm optimization for optimal device selection
Published 2022“…Enhance hybrid genetic algorithm and particle Swarm optimization are developed to select the optimal device in either fog or cloud. …”
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The effect of adaptive parameters on the performance of back propagation
Published 2012“…The results show that the proposed algorithm extensively improves the learning process of conventional Back Propagation algorithm.…”
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Thesis -
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Ant colony optimization algorithm for load balancing in grid computing
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Monograph -
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Optimisation of fed-batch fermentation process using deep reinforcement learning
Published 2023“…Fed-batch fermentation process has always been a challenge for optimisation because it is highly non-linear and complex. Deep reinforcement learning is a self-learning algorithm through trial and error and experience, without any prior knowledge. …”
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10
Data Analysis and Machine Learning Algorithms Evaluation for Bioliq AI-based Predictive Tool
Published 2019“…This final year project identified relevant parameters through literature research, analysis and expert interview, and evaluated different machine learning algorithms and identified linear regression as the most applicable and efficient with its R-square of 0.8015, qualifying it to be used for the development of a hybrid model for the AI-based tool for predictive process optimization for chemical plants.…”
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Final Year Project -
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Characterisation of pineapple cultivars under different storage conditions using infrared thermal imaging coupled with machine learning algorithms
Published 2022“…A total of 14 features from the thermal images were obtained to determine the variation in terms of image parameters among the different pineapple cultivars. …”
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Computer Lab Timetabling Using Genetic Algorithm Case Study - Unit ICT
Published 2006“…Genetic Algorithm is one of the most popular optimization solutions used in various applications such as scheduling. …”
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Deep Learning Based Face Attributes Recognition
Published 2018“…Combined-algorithm based optimizers plays an important role in optimizing the training algorithm. …”
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Monograph -
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Examination timetabling using genetic algorithm case study: KUiTTHO
Published 2005“…Genetic Algorithm (GA) is one of the most popular optimization solutions. …”
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A decomposed streamflow non-gradientbased artificial intelligence forecasting algorithm with factoring in aleatoric and epistemic variables / Wei Yaxing
Published 2024“…Given the multitude of components to manage, streamflow forecasting is preferable to employ an algorithm with low sensitivity to parameter variations. …”
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Examination Timetabling Using Genetic Algorithm Case Study : KUiTTHO
Published 2005“…Genetic Algorithm (GA) is one of the most popular optimization solutions. …”
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Building detection using object-based Image analysis (OBIA) and machine learning (ML) algorithms / Hanani Mohd Shahar
Published 2020“…In order to obtain a good classification accuracy, the suitable segmentation parameters (scale, shape and compactness) and features selection have been determined and Machine learning (ML) algorithms, namely Support Vector Machine (SVM) and Decision Tree (DT) classifiers have been applied to categorized five different classes which are water, forest, green area, building, and road. …”
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Multivariate Based Analysis of Methane Adsorption Correlated to Toc and Mineralogy Impact from Different Shale Fabrics
Published 2021“…The analysis from machine learning SVR method shows the good predictability of the adsorption in the variation with shale fabric parameters. …”
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