Search Results - (( variables reduction data algorithm ) OR ( java application optimization 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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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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Ant colony optimization algorithm for load balancing in grid computing
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Monograph -
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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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Thesis -
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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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Thesis -
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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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Thesis -
12
Improving Class Timetabling using Genetic Algorithm
Published 2006“…We have targeted the research on class timetabling problem. Hence, Genetic Algorithm (GA) is used as one of the most popular optimization solutions. …”
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Thesis -
13
Hyper-heuristic approaches for data stream-based iIntrusion detection in the Internet of Things
Published 2022“…The experimental results showed that the accuracy of the algorithm over the NSL-KDD dataset was 99.72%, with a memory reduction of 10%. …”
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Thesis -
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Parallel distributed genetic algorithm development based on microcontrollers framework
Published 2023Conference paper -
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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 -
17
Optimizing lossless compression by normalized data length in Huffman Algorithm
Published 2022“…Huffman Algorithms is currently still very effective at compressing 8-bit data, which can be grouped into Static, Dynamic, and Adaptive extensions, however its performance cannot be determined if it is performed on data that has several variables and probabilities. …”
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Thesis -
18
Cleansing of inconsistent sample in linear regression model based on rough sets theory
Published 2023“…In the implementation, these aspects also performed better than before data reduction. The results from both simulations and implementations demonstrate that the data reduction of rough sets is a viable strategy in cleansing of the inconsistent samples in the linear regression models. …”
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Article -
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Cleansing of inconsistent sample in linear regression model based on rough sets theory
Published 2023“…In the implementation, these aspects also performed better than before data reduction. The results from both simulations and implementations demonstrate that the data reduction of rough sets is a viable strategy in cleansing of the inconsistent samples in the linear regression models. …”
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Article -
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Cleansing of inconsistent sample in linear regression model based on rough sets theory
Published 2023“…In the implementation, these aspects also performed better than before data reduction. The results from both simulations and implementations demonstrate that the data reduction of rough sets is a viable strategy in cleansing of the inconsistent samples in the linear regression models. …”
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