Search Results - (( data generation learning algorithm ) OR ( java applications optimization algorithm ))
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Features selection for intrusion detection system using hybridize PSO-SVM
Published 2016“…Hybridize Particle Swarm Optimization (PSO) as a searching algorithm and support vector machine (SVM) as a classifier had been implemented to cope with this problem. …”
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Thesis -
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Optimization of blood vessel detection in retina images using multithreading and native code for portable devices
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Conference or Workshop Item -
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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 -
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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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Article -
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New Learning Models for Generating Classification Rules Based on Rough Set Approach
Published 2000“…Also, the proposed models for learning in data sets generated the classification rules faster than other methods. …”
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Ant colony optimization algorithm for load balancing in grid computing
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Monograph -
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Prediction of hydropower generation via machine learning algorithms at three Gorges Dam, China
Published 2024“…Therefore, this study investigates the capability of various machine learning algorithms in predicting the power production of a reservoir located in China using data from 1979 to 2016. …”
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Unsupervised learning of image data using generative adversarial network
Published 2020“…Based on the results obtained, the GAN algorithm can learn the internal representation of data without labels and can act as good features extractor. …”
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Proceedings -
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Small Dataset Learning In Prediction Model Using Box-Whisker Data Transformation
Published 2020“…From the previous studies, there are solutions to improve learning accuracy and predictive capability where some artificial data will be added to the system using artificial data generation approach. …”
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An optimized variant of machine learning algorithm for datadriven electrical energy efficiency management (D2EEM)
Published 2024“…The scope of this study is tri folded, First, an exhaustive and parametric comparative study on a wide variety of machine learning algorithms is presented to evaluate the performance of machine learning algorithms in energy load prediction. …”
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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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Graph-Based Algorithm With Self-Weighted And Adaptive Neighbours Learning For Multi-View Clustering
Published 2024“…Although the swmcan algorithm solves the noise problem in multi-view data, its initial and final graphs are independent and cannot learn from each other. …”
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Pairwise Test Suite Generation Using Adaptive Teaching Learning-Based Optimization Algorithm with Remedial Operator
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Conference or Workshop Item -
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A Denoising Generative Adversarial Network Based On Enhanced Feature Mapping Of Data Augmentation For Image Synthesis
Published 2024“…This requires the generator to learn how to generate images from partially damaged data, leading to better representations learned from the data. …”
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Multi-step time series prediction using recurrent kernel online sequential extreme learning machine / Liu Zongying
Published 2019“…Recent years, Machine correlation and potential non stationary of the data can be automatically analyzed. However, the problems with traditional offline and online learning algorithms in machine learning algorithms are usually faced with parameter dependency, concept drift handling problem, connectionless of neural net and unfixed reservoir. …”
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