Search Results - (( developing variable selection algorithm ) OR ( java applications optimized 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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Article -
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Variable block based motion estimation using hexagon diamond full search algorithm (HDFSA) via block subtraction technique
Published 2015“…The variable block matching developed based on four stages which is the video and frame selection, threshold calculation, block size selection and search pattern. …”
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Thesis -
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A meta-heuristics based input variable selection technique for hybrid electrical energy demand prediction models
Published 2017“…The significance of the selected input variable vectors is studied to analyze their effects on the prediction process. …”
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Ant colony optimization algorithm for load balancing in grid computing
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Monograph -
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SURE-Autometrics algorithm for model selection in multiple equations
Published 2016“…Thus, this study aims to develop an algorithm for model selection in multiple equations focusing on seemingly unrelated regression equations (SURE) model. …”
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Thesis -
10
Robust variable selection methods for large- scale data in the presence of multicollinearity, autocorrelated errors and outliers
Published 2016“…Hence, Robust Non- Grouped variable selection(RNGVS.RFCH) in the presence of high multicollinearity problem and outliers is developed. …”
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11
Dynamic Bayesian networks and variable length genetic algorithm for designing cue-based model for dialogue act recognition
Published 2010“…In the second stage, the developed variable length genetic algorithm is used to select different sets of lexical cues to constitute the dynamic Bayesian networks' random variables. …”
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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 -
14
Taguchi?s T-method with Normalization-Based Binary Bat Algorithm
Published 2025“…Therefore, a variable selection technique using a swarm-based Binary Bat algorithm is proposed. …”
Conference paper -
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Development of genetic algorithm for optimization of yield models in oil palm production
Published 2018“…This research concludes that the GA method is a user-friendly variable selection tool with excellent results because it can choose variables correctly.…”
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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 -
18
Effect of input variables selection on energy demand prediction based on intelligent hybrid neural networks
Published 2015“…Multiple cases are developed using different optimally selected input variable vectors to train and test the back propagation neural network (BP-NN) and the hybrid model. …”
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Article -
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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 -
20
Robust diagnostics and variable selection procedure based on modified reweighted fast consistent and high breakdown estimator for high dimensional data
Published 2022“…However, in practice, high leverage points may lead to misleading results in solving variable selection problems. Therefore, a robust sure independence screening procedure based on the weighted correlation algorithm of MRFCH for high dimensional data is developed to address this problem. …”
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