Search Results - (( variable enhancing learning algorithm ) OR ( parallel optimization path algorithm ))
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Tool path generation of contour parallel based on ant colony optimisation
Published 2016“…An Ant Colony Optimisation (ACO) method is used to optimize the tool path length because of its capability to find the shortest tool path length. …”
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Minimizing machining airtime motion with an ant colony algorithm
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Restoration planning strategy of transmission system based on optimal energizing time of sectionalizing islands / Dian Najihah Abu Talib
Published 2019“…There are two discrete optimization techniques used in this work, which are the Artificial Bee Colony algorithm and Evolutionary Programming. …”
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Enhanced Adaptive Confidence-Based Q Routing Algorithms For Network Traffic
Published 2004“…Two new adaptive routing algorithms named Enhanced Confidence-based Q (ECQ) and Enhanced Confidence-based Dual Reinforcement Q (ECDRQ) Routing Algorithms are proposed in this thesis. …”
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A novel large-bit-size architecture and microarchitecture for the implementation of Superscalar Pipeline VLIW microprocessors
Published 2008“…Different adder architectures are investigated for suitability on synthesis implementation of large data bus size adder for efficient usage within the ALU. An adder algorithm using repetitive constructs in a parallel algorithm that allows for efficient and optimal synthesis for large data bus size is proposed as a suitable implementation for the adder within the ALU. …”
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A decomposed streamflow non-gradientbased artificial intelligence forecasting algorithm with factoring in aleatoric and epistemic variables / Wei Yaxing
Published 2024“…However, not all accepted metaheuristic algorithms are compatible with enhancing the ANN for streamflow forecasting, demanding a thorough analysis due to performance differences across cases. …”
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Application of Decision Trees in Athlete Selection: A Cart Algorithm Approach
Published 2023“…Notably, weight, and Body Mass Index (BMI) exhibit the highest significance among the other variables. Looking ahead, future research could explore enhancing DTs' predictive capabilities in athlete selection by incorporating more variables or employing ensemble learning techniques. …”
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Feasibility analysis for predicting the compressive and tensile strength of concrete using machine learning algorithms
Published 2024“…However, in predicting the compressive strength, an increase in the number of input variables lead to an enhancement in the performance metrics. …”
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Algorithm enhancement for host-based intrusion detection system using discriminant analysis
Published 2004“…This thesis expects an enhancement algorithm to be able to reduce a false positive alarm and misclassification rate. …”
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A 'snowflake' geometrical representation for optimised degree six 3-modified chordal ring networks
Published 2016“…A tree visualisation was constructed based on its connectivity to enable the generation of formulae for optimal diameter and average optimal path lengths. …”
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Detection of black hole nodes in mobile ad hoc network using hybrid trustworthiness and energy consumption techniques
Published 2017“…In this thesis, a hybrid detection algorithm mechanism has been proposed which combines two detection algorithms based on nodes’ trustworthiness and energy consumption in a parallel manner in order to detect the black hole nodes. …”
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A New Quadratic Binary Harris Hawk Optimization For Feature Selection
Published 2019“…In this study, twenty-two datasets collected from the UCI machine learning repository are used to validate the performance of proposed algorithms. …”
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Random forest algorithm for co2 water alternating gas incremental recovery factor prediction
Published 2020“…Predictive tools based on machine learning are gaining in popularity in the E&P industry by enhancing conventional procedures and reducing operational cost under current unstable oil market. …”
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Applying machine learning and particle swarm optimization for predictive modeling and cost optimization in construction project management
Published 2024“…Particle Swarm Optimization (PSO) has demonstrated its efficacy in addressing the issue of construction waste reduction and enhancing the accuracy of cost estimation through the identification of optimal combinations of variables. …”
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Parameter characterization of PEM fuel cell mathematical models using an orthogonal learning-based GOOSE algorithm
Published 2025“…The orthogonal learning mechanism improves the performance of the original GOOSE algorithm. …”
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The impact of the combat method on radiomics feature compensation and analysis of scanners from different manufacturers
Published 2024“…Conclusions: The Combat algorithm has reduced variability in radiomic features from different scanners. …”
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